chore: update docs/dyn , add static discovery files to discovery_cache/documents (#1111)
This PR was generated using Autosynth. :rainbow:
Synth log will be available here:
https://source.cloud.google.com/results/invocations/78f53313-0c78-4a29-8841-f031665a4c6a/targets
- [ ] To automatically regenerate this PR, check this box.
Source-Link: https://github.com/googleapis/synthtool/commit/c2de32114ec484aa708d32012d1fa8d75232daf5
diff --git a/docs/dyn/dataflow_v1b3.projects.jobs.html b/docs/dyn/dataflow_v1b3.projects.jobs.html
index 5931bc9..7a306eb 100644
--- a/docs/dyn/dataflow_v1b3.projects.jobs.html
+++ b/docs/dyn/dataflow_v1b3.projects.jobs.html
@@ -90,7 +90,7 @@
<p class="firstline">Returns the workItems Resource.</p>
<p class="toc_element">
- <code><a href="#aggregated">aggregated(projectId, pageSize=None, location=None, view=None, filter=None, pageToken=None, x__xgafv=None)</a></code></p>
+ <code><a href="#aggregated">aggregated(projectId, filter=None, pageToken=None, location=None, view=None, pageSize=None, x__xgafv=None)</a></code></p>
<p class="firstline">List the jobs of a project across all regions.</p>
<p class="toc_element">
<code><a href="#aggregated_next">aggregated_next(previous_request, previous_response)</a></code></p>
@@ -102,13 +102,13 @@
<code><a href="#create">create(projectId, body=None, location=None, view=None, replaceJobId=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a Cloud Dataflow job. To create a job, we recommend using `projects.locations.jobs.create` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.create` is not recommended, as your job will always start in `us-central1`.</p>
<p class="toc_element">
- <code><a href="#get">get(projectId, jobId, view=None, location=None, x__xgafv=None)</a></code></p>
+ <code><a href="#get">get(projectId, jobId, location=None, view=None, x__xgafv=None)</a></code></p>
<p class="firstline">Gets the state of the specified Cloud Dataflow job. To get the state of a job, we recommend using `projects.locations.jobs.get` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.get` is not recommended, as you can only get the state of jobs that are running in `us-central1`.</p>
<p class="toc_element">
- <code><a href="#getMetrics">getMetrics(projectId, jobId, location=None, startTime=None, x__xgafv=None)</a></code></p>
+ <code><a href="#getMetrics">getMetrics(projectId, jobId, startTime=None, location=None, x__xgafv=None)</a></code></p>
<p class="firstline">Request the job status. To request the status of a job, we recommend using `projects.locations.jobs.getMetrics` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.getMetrics` is not recommended, as you can only request the status of jobs that are running in `us-central1`.</p>
<p class="toc_element">
- <code><a href="#list">list(projectId, location=None, pageSize=None, filter=None, view=None, pageToken=None, x__xgafv=None)</a></code></p>
+ <code><a href="#list">list(projectId, view=None, pageSize=None, location=None, pageToken=None, filter=None, x__xgafv=None)</a></code></p>
<p class="firstline">List the jobs of a project. To list the jobs of a project in a region, we recommend using `projects.locations.jobs.list` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). To list the all jobs across all regions, use `projects.jobs.aggregated`. Using `projects.jobs.list` is not recommended, as you can only get the list of jobs that are running in `us-central1`.</p>
<p class="toc_element">
<code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
@@ -121,19 +121,11 @@
<p class="firstline">Updates the state of an existing Cloud Dataflow job. To update the state of an existing job, we recommend using `projects.locations.jobs.update` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.update` is not recommended, as you can only update the state of jobs that are running in `us-central1`.</p>
<h3>Method Details</h3>
<div class="method">
- <code class="details" id="aggregated">aggregated(projectId, pageSize=None, location=None, view=None, filter=None, pageToken=None, x__xgafv=None)</code>
+ <code class="details" id="aggregated">aggregated(projectId, filter=None, pageToken=None, location=None, view=None, pageSize=None, x__xgafv=None)</code>
<pre>List the jobs of a project across all regions.
Args:
projectId: string, The project which owns the jobs. (required)
- pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit.
- location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- view: string, Level of information requested in response. Default is `JOB_VIEW_SUMMARY`.
- Allowed values
- JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information.
- JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details.
- JOB_VIEW_ALL - Request all information available for this job.
- JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment.
filter: string, The kind of filter to use.
Allowed values
UNKNOWN - The filter isn't specified, or is unknown. This returns all jobs ordered on descending `JobUuid`.
@@ -141,6 +133,14 @@
TERMINATED - Filters the jobs that have a terminated state, ordered on the termination timestamp. Example terminated states: `JOB_STATE_STOPPED`, `JOB_STATE_UPDATED`, `JOB_STATE_DRAINED`, etc.
ACTIVE - Filters the jobs that are running ordered on the creation timestamp.
pageToken: string, Set this to the 'next_page_token' field of a previous response to request additional results in a long list.
+ location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ view: string, Level of information requested in response. Default is `JOB_VIEW_SUMMARY`.
+ Allowed values
+ JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information.
+ JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details.
+ JOB_VIEW_ALL - Request all information available for this job.
+ JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment.
+ pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
@@ -150,301 +150,301 @@
An object of the form:
{ # Response to a request to list Cloud Dataflow jobs in a project. This might be a partial response, depending on the page size in the ListJobsRequest. However, if the project does not have any jobs, an instance of ListJobsResponse is not returned and the requests's response body is empty {}.
+ "jobs": [ # A subset of the requested job information.
+ { # Defines a job to be run by the Cloud Dataflow service.
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
+ },
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
+ },
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
+ "A String",
+ ],
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
+ },
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
+ "A String",
+ ],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
+ },
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
+ },
+ },
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
+ },
+ ],
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
+ },
+ ],
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+ },
+ ],
"failedLocation": [ # Zero or more messages describing the [regional endpoints] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond.
{ # Indicates which [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) failed to respond to a request for data.
"name": "A String", # The name of the [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond.
},
],
"nextPageToken": "A String", # Set if there may be more results than fit in this response.
- "jobs": [ # A subset of the requested job information.
- { # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- },
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
- },
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "A String",
- ],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
- },
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
- "A String",
- ],
- },
- },
- },
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
- },
- ],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
- },
- ],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- },
- ],
}</pre>
</div>
@@ -477,292 +477,292 @@
The object takes the form of:
{ # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
},
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
},
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
"A String",
],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
},
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
"A String",
],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
},
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
},
},
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
},
],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
},
],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- }
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+}
location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
view: string, The level of information requested in response.
@@ -781,308 +781,308 @@
An object of the form:
{ # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
},
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
},
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
"A String",
],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
},
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
"A String",
],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
},
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
},
},
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
},
],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
},
],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- }</pre>
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+ }</pre>
</div>
<div class="method">
- <code class="details" id="get">get(projectId, jobId, view=None, location=None, x__xgafv=None)</code>
+ <code class="details" id="get">get(projectId, jobId, location=None, view=None, x__xgafv=None)</code>
<pre>Gets the state of the specified Cloud Dataflow job. To get the state of a job, we recommend using `projects.locations.jobs.get` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.get` is not recommended, as you can only get the state of jobs that are running in `us-central1`.
Args:
projectId: string, The ID of the Cloud Platform project that the job belongs to. (required)
jobId: string, The job ID. (required)
+ location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
view: string, The level of information requested in response.
Allowed values
JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information.
JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details.
JOB_VIEW_ALL - Request all information available for this job.
JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment.
- location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
@@ -1092,303 +1092,303 @@
An object of the form:
{ # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
},
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
},
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
"A String",
],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
},
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
"A String",
],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
},
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
},
},
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
},
],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
},
],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- }</pre>
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+ }</pre>
</div>
<div class="method">
- <code class="details" id="getMetrics">getMetrics(projectId, jobId, location=None, startTime=None, x__xgafv=None)</code>
+ <code class="details" id="getMetrics">getMetrics(projectId, jobId, startTime=None, location=None, x__xgafv=None)</code>
<pre>Request the job status. To request the status of a job, we recommend using `projects.locations.jobs.getMetrics` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.getMetrics` is not recommended, as you can only request the status of jobs that are running in `us-central1`.
Args:
projectId: string, A project id. (required)
jobId: string, The job to get metrics for. (required)
- location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains the job specified by job_id.
startTime: string, Return only metric data that has changed since this time. Default is to return all information about all metrics for the job.
+ location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains the job specified by job_id.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
@@ -1400,22 +1400,22 @@
{ # JobMetrics contains a collection of metrics describing the detailed progress of a Dataflow job. Metrics correspond to user-defined and system-defined metrics in the job. This resource captures only the most recent values of each metric; time-series data can be queried for them (under the same metric names) from Cloud Monitoring.
"metrics": [ # All metrics for this job.
{ # Describes the state of a metric.
+ "kind": "A String", # Metric aggregation kind. The possible metric aggregation kinds are "Sum", "Max", "Min", "Mean", "Set", "And", "Or", and "Distribution". The specified aggregation kind is case-insensitive. If omitted, this is not an aggregated value but instead a single metric sample value.
+ "internal": "", # Worker-computed aggregate value for internal use by the Dataflow service.
+ "meanSum": "", # Worker-computed aggregate value for the "Mean" aggregation kind. This holds the sum of the aggregated values and is used in combination with mean_count below to obtain the actual mean aggregate value. The only possible value types are Long and Double.
"meanCount": "", # Worker-computed aggregate value for the "Mean" aggregation kind. This holds the count of the aggregated values and is used in combination with mean_sum above to obtain the actual mean aggregate value. The only possible value type is Long.
- "cumulative": True or False, # True if this metric is reported as the total cumulative aggregate value accumulated since the worker started working on this WorkItem. By default this is false, indicating that this metric is reported as a delta that is not associated with any WorkItem.
+ "gauge": "", # A struct value describing properties of a Gauge. Metrics of gauge type show the value of a metric across time, and is aggregated based on the newest value.
+ "distribution": "", # A struct value describing properties of a distribution of numeric values.
"name": { # Identifies a metric, by describing the source which generated the metric. # Name of the metric.
"context": { # Zero or more labeled fields which identify the part of the job this metric is associated with, such as the name of a step or collection. For example, built-in counters associated with steps will have context['step'] = . Counters associated with PCollections in the SDK will have context['pcollection'] = .
"a_key": "A String",
},
- "origin": "A String", # Origin (namespace) of metric name. May be blank for user-define metrics; will be "dataflow" for metrics defined by the Dataflow service or SDK.
"name": "A String", # Worker-defined metric name.
+ "origin": "A String", # Origin (namespace) of metric name. May be blank for user-define metrics; will be "dataflow" for metrics defined by the Dataflow service or SDK.
},
- "gauge": "", # A struct value describing properties of a Gauge. Metrics of gauge type show the value of a metric across time, and is aggregated based on the newest value.
- "kind": "A String", # Metric aggregation kind. The possible metric aggregation kinds are "Sum", "Max", "Min", "Mean", "Set", "And", "Or", and "Distribution". The specified aggregation kind is case-insensitive. If omitted, this is not an aggregated value but instead a single metric sample value.
"scalar": "", # Worker-computed aggregate value for aggregation kinds "Sum", "Max", "Min", "And", and "Or". The possible value types are Long, Double, and Boolean.
- "meanSum": "", # Worker-computed aggregate value for the "Mean" aggregation kind. This holds the sum of the aggregated values and is used in combination with mean_count below to obtain the actual mean aggregate value. The only possible value types are Long and Double.
"updateTime": "A String", # Timestamp associated with the metric value. Optional when workers are reporting work progress; it will be filled in responses from the metrics API.
- "distribution": "", # A struct value describing properties of a distribution of numeric values.
- "internal": "", # Worker-computed aggregate value for internal use by the Dataflow service.
+ "cumulative": True or False, # True if this metric is reported as the total cumulative aggregate value accumulated since the worker started working on this WorkItem. By default this is false, indicating that this metric is reported as a delta that is not associated with any WorkItem.
"set": "", # Worker-computed aggregate value for the "Set" aggregation kind. The only possible value type is a list of Values whose type can be Long, Double, or String, according to the metric's type. All Values in the list must be of the same type.
},
],
@@ -1424,26 +1424,26 @@
</div>
<div class="method">
- <code class="details" id="list">list(projectId, location=None, pageSize=None, filter=None, view=None, pageToken=None, x__xgafv=None)</code>
+ <code class="details" id="list">list(projectId, view=None, pageSize=None, location=None, pageToken=None, filter=None, x__xgafv=None)</code>
<pre>List the jobs of a project. To list the jobs of a project in a region, we recommend using `projects.locations.jobs.list` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). To list the all jobs across all regions, use `projects.jobs.aggregated`. Using `projects.jobs.list` is not recommended, as you can only get the list of jobs that are running in `us-central1`.
Args:
projectId: string, The project which owns the jobs. (required)
- location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit.
- filter: string, The kind of filter to use.
- Allowed values
- UNKNOWN - The filter isn't specified, or is unknown. This returns all jobs ordered on descending `JobUuid`.
- ALL - Returns all running jobs first ordered on creation timestamp, then returns all terminated jobs ordered on the termination timestamp.
- TERMINATED - Filters the jobs that have a terminated state, ordered on the termination timestamp. Example terminated states: `JOB_STATE_STOPPED`, `JOB_STATE_UPDATED`, `JOB_STATE_DRAINED`, etc.
- ACTIVE - Filters the jobs that are running ordered on the creation timestamp.
view: string, Level of information requested in response. Default is `JOB_VIEW_SUMMARY`.
Allowed values
JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information.
JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details.
JOB_VIEW_ALL - Request all information available for this job.
JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment.
+ pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit.
+ location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
pageToken: string, Set this to the 'next_page_token' field of a previous response to request additional results in a long list.
+ filter: string, The kind of filter to use.
+ Allowed values
+ UNKNOWN - The filter isn't specified, or is unknown. This returns all jobs ordered on descending `JobUuid`.
+ ALL - Returns all running jobs first ordered on creation timestamp, then returns all terminated jobs ordered on the termination timestamp.
+ TERMINATED - Filters the jobs that have a terminated state, ordered on the termination timestamp. Example terminated states: `JOB_STATE_STOPPED`, `JOB_STATE_UPDATED`, `JOB_STATE_DRAINED`, etc.
+ ACTIVE - Filters the jobs that are running ordered on the creation timestamp.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
@@ -1453,301 +1453,301 @@
An object of the form:
{ # Response to a request to list Cloud Dataflow jobs in a project. This might be a partial response, depending on the page size in the ListJobsRequest. However, if the project does not have any jobs, an instance of ListJobsResponse is not returned and the requests's response body is empty {}.
+ "jobs": [ # A subset of the requested job information.
+ { # Defines a job to be run by the Cloud Dataflow service.
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
+ },
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
+ },
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
+ "A String",
+ ],
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
+ },
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
+ "A String",
+ ],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
+ },
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
+ },
+ },
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
+ },
+ ],
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
+ },
+ ],
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+ },
+ ],
"failedLocation": [ # Zero or more messages describing the [regional endpoints] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond.
{ # Indicates which [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) failed to respond to a request for data.
"name": "A String", # The name of the [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond.
},
],
"nextPageToken": "A String", # Set if there may be more results than fit in this response.
- "jobs": [ # A subset of the requested job information.
- { # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- },
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
- },
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "A String",
- ],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
- },
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
- "A String",
- ],
- },
- },
- },
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
- },
- ],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
- },
- ],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- },
- ],
}</pre>
</div>
@@ -1776,10 +1776,10 @@
The object takes the form of:
{ # Request to create a snapshot of a job.
- "snapshotSources": True or False, # If true, perform snapshots for sources which support this.
"ttl": "A String", # TTL for the snapshot.
"location": "A String", # The location that contains this job.
"description": "A String", # User specified description of the snapshot. Maybe empty.
+ "snapshotSources": True or False, # If true, perform snapshots for sources which support this.
}
x__xgafv: string, V1 error format.
@@ -1793,19 +1793,19 @@
{ # Represents a snapshot of a job.
"pubsubMetadata": [ # PubSub snapshot metadata.
{ # Represents a Pubsub snapshot.
- "expireTime": "A String", # The expire time of the Pubsub snapshot.
- "topicName": "A String", # The name of the Pubsub topic.
"snapshotName": "A String", # The name of the Pubsub snapshot.
+ "topicName": "A String", # The name of the Pubsub topic.
+ "expireTime": "A String", # The expire time of the Pubsub snapshot.
},
],
- "state": "A String", # State of the snapshot.
- "sourceJobId": "A String", # The job this snapshot was created from.
- "ttl": "A String", # The time after which this snapshot will be automatically deleted.
- "diskSizeBytes": "A String", # The disk byte size of the snapshot. Only available for snapshots in READY state.
- "projectId": "A String", # The project this snapshot belongs to.
"creationTime": "A String", # The time this snapshot was created.
"id": "A String", # The unique ID of this snapshot.
+ "diskSizeBytes": "A String", # The disk byte size of the snapshot. Only available for snapshots in READY state.
+ "projectId": "A String", # The project this snapshot belongs to.
+ "state": "A String", # State of the snapshot.
+ "ttl": "A String", # The time after which this snapshot will be automatically deleted.
"description": "A String", # User specified description of the snapshot. Maybe empty.
+ "sourceJobId": "A String", # The job this snapshot was created from.
}</pre>
</div>
@@ -1820,292 +1820,292 @@
The object takes the form of:
{ # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
},
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
},
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
"A String",
],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
},
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
"A String",
],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
},
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
},
},
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
},
],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
},
],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- }
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+}
location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
x__xgafv: string, V1 error format.
@@ -2117,292 +2117,292 @@
An object of the form:
{ # Defines a job to be run by the Cloud Dataflow service.
- "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
- "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
- "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
- { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
- "kind": "A String", # Type of tranform this stage is executing.
- "componentTransform": [ # Transforms that comprise this execution stage.
- { # Description of a transform executed as part of an execution stage.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
- },
- ],
- "id": "A String", # Dataflow service generated id for this stage.
- "name": "A String", # Dataflow service generated name for this stage.
- "componentSource": [ # Collections produced and consumed by component transforms of this stage.
- { # Description of an interstitial value between transforms in an execution stage.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- "userName": "A String", # Human-readable name for this transform; may be user or system generated.
- },
- ],
- "inputSource": [ # Input sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- "prerequisiteStage": [ # Other stages that must complete before this stage can run.
- "A String",
- ],
- "outputSource": [ # Output sources for this stage.
- { # Description of an input or output of an execution stage.
- "userName": "A String", # Human-readable name for this source; may be user or system generated.
- "sizeBytes": "A String", # Size of the source, if measurable.
- "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
- "name": "A String", # Dataflow service generated name for this source.
- },
- ],
- },
- ],
- "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
- { # Description of the type, names/ids, and input/outputs for a transform.
- "kind": "A String", # Type of transform.
- "displayData": [ # Transform-specific display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
- "name": "A String", # User provided name for this transform instance.
- "inputCollectionName": [ # User names for all collection inputs to this transform.
- "A String",
- ],
- "outputCollectionName": [ # User names for all collection outputs to this transform.
- "A String",
- ],
- "id": "A String", # SDK generated id of this transform instance.
- },
- ],
- "displayData": [ # Pipeline level display data.
- { # Data provided with a pipeline or transform to provide descriptive info.
- "boolValue": True or False, # Contains value if the data is of a boolean type.
- "label": "A String", # An optional label to display in a dax UI for the element.
- "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
- "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
- "javaClassValue": "A String", # Contains value if the data is of java class type.
- "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
- "int64Value": "A String", # Contains value if the data is of int64 type.
- "timestampValue": "A String", # Contains value if the data is of timestamp type.
- "floatValue": 3.14, # Contains value if the data is of float type.
- "durationValue": "A String", # Contains value if the data is of duration type.
- "url": "A String", # An optional full URL.
- "strValue": "A String", # Contains value if the data is of string type.
- },
- ],
+ "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
+ { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
+ "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
},
- "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
- "a_key": "A String",
+ ],
+ "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job.
+ "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
+ "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
+ "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "userAgent": { # A description of the process that generated the request.
+ "a_key": "", # Properties of the object.
},
- "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
+ "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
+ "experiments": [ # The list of experiments to enable.
"A String",
],
- "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
- "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
- "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
- "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
- "a_key": "", # Properties of the object.
- },
- "experiments": [ # The list of experiments to enable.
- "A String",
- ],
- "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
- "version": { # A structure describing which components and their versions of the service are required in order to run the job.
- "a_key": "", # Properties of the object.
- },
- "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity.
- "internalExperiments": { # Experimental settings.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY
- "userAgent": { # A description of the process that generated the request.
- "a_key": "", # Properties of the object.
- },
- "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
- "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
- "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
- { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
- "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
- "packages": [ # Packages to be installed on workers.
- { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
- "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
- "name": "A String", # The name of the package.
- },
- ],
- "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
- "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
- "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
- { # Defines a SDK harness container for executing Dataflow pipelines.
- "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
- "containerImage": "A String", # A docker container image that resides in Google Container Registry.
- },
- ],
- "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
- "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
- "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
- "workerId": "A String", # The ID of the worker running this pipeline.
- "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "reportingEnabled": True or False, # Whether to send work progress updates to the service.
- "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
- "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
- "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- },
- "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "harnessCommand": "A String", # The command to launch the worker harness.
- "vmId": "A String", # The ID string of the VM.
- "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
- "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
- "languageHint": "A String", # The suggested backend language.
- "streamingWorkerMainClass": "A String", # The streaming worker main class name.
- "logDir": "A String", # The directory on the VM to store logs.
- "workflowFileName": "A String", # The file to store the workflow in.
- "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
- "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
- "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
- "A String",
- ],
- "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
- "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
- "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
- "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
- "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers.
+ { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job.
+ "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
+ "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field.
+ "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
+ "workerId": "A String", # The ID of the worker running this pipeline.
+ "reportingEnabled": True or False, # Whether to send work progress updates to the service.
+ "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1".
+ "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects".
},
- "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
- "metadata": { # Metadata to set on the Google Compute Engine VMs.
- "a_key": "A String",
- },
- "ipConfiguration": "A String", # Configuration for VM IPs.
- "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
- "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default.
- "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
- "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
- "algorithm": "A String", # The algorithm to use for autoscaling.
- },
- "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
- "diskSourceImage": "A String", # Fully qualified source image for disks.
- "poolArgs": { # Extra arguments for this worker pool.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
- "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
- "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
- "dataDisks": [ # Data disks that are used by a VM in this workflow.
- { # Describes the data disk used by a workflow job.
- "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
- "mountPoint": "A String", # Directory in a VM where disk is mounted.
- "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
- },
- ],
- "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
- "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
- },
- ],
- },
- "currentStateTime": "A String", # The timestamp associated with the current state.
- "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
- "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
- { # Metadata for a BigTable connector used by the job.
- "tableId": "A String", # TableId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- },
- ],
- "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
- "versionDisplayName": "A String", # A readable string describing the version of the SDK.
- "version": "A String", # The version of the SDK used to run the job.
- "sdkSupportStatus": "A String", # The support status for this SDK version.
- },
- "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
- { # Metadata for a BigQuery connector used by the job.
- "dataset": "A String", # Dataset accessed in the connection.
- "table": "A String", # Table accessed in the connection.
- "projectId": "A String", # Project accessed in the connection.
- "query": "A String", # Query used to access data in the connection.
- },
- ],
- "fileDetails": [ # Identification of a File source used in the Dataflow job.
- { # Metadata for a File connector used by the job.
- "filePattern": "A String", # File Pattern used to access files by the connector.
- },
- ],
- "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
- { # Metadata for a Datastore connector used by the job.
- "projectId": "A String", # ProjectId accessed in the connection.
- "namespace": "A String", # Namespace used in the connection.
- },
- ],
- "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
- { # Metadata for a Spanner connector used by the job.
- "databaseId": "A String", # DatabaseId accessed in the connection.
- "instanceId": "A String", # InstanceId accessed in the connection.
- "projectId": "A String", # ProjectId accessed in the connection.
- },
- ],
- "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
- { # Metadata for a PubSub connector used by the job.
- "subscription": "A String", # Subscription used in the connection.
- "topic": "A String", # Topic accessed in the connection.
- },
- ],
- },
- "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
- "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
- "a_key": "A String",
- },
- "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
- "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
- "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
- "stages": { # A mapping from each stage to the information about that stage.
- "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
- "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console.
+ "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
+ "commandlinesFileName": "A String", # The file to store preprocessing commands in.
+ "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root".
+ "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API.
"A String",
],
+ "vmId": "A String", # The ID string of the VM.
+ "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/"
+ "workflowFileName": "A String", # The file to store the workflow in.
+ "languageHint": "A String", # The suggested backend language.
+ "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
+ "streamingWorkerMainClass": "A String", # The streaming worker main class name.
+ "harnessCommand": "A String", # The command to launch the worker harness.
+ "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "logDir": "A String", # The directory on the VM to store logs.
+ "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
+ "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel".
+ "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
},
+ "diskSourceImage": "A String", # Fully qualified source image for disks.
+ "metadata": { # Metadata to set on the Google Compute Engine VMs.
+ "a_key": "A String",
+ },
+ "dataDisks": [ # Data disks that are used by a VM in this workflow.
+ { # Describes the data disk used by a workflow job.
+ "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard
+ "mountPoint": "A String", # Directory in a VM where disk is mounted.
+ },
+ ],
+ "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "packages": [ # Packages to be installed on workers.
+ { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run.
+ "name": "A String", # The name of the package.
+ "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/
+ },
+ ],
+ "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries.
+ { # Defines a SDK harness container for executing Dataflow pipelines.
+ "containerImage": "A String", # A docker container image that resides in Google Container Registry.
+ "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed.
+ },
+ ],
+ "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported.
+ "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
+ "algorithm": "A String", # The algorithm to use for autoscaling.
+ "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
+ },
+ "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default.
+ "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default.
+ "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead.
+ "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language.
+ "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API.
+ "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK".
+ "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming).
+ "poolArgs": { # Extra arguments for this worker pool.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "ipConfiguration": "A String", # Configuration for VM IPs.
+ "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default.
+ "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default".
+ },
+ ],
+ "internalExperiments": { # Experimental settings.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region.
+ "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com".
+ "version": { # A structure describing which components and their versions of the service are required in order to run the job.
+ "a_key": "", # Properties of the object.
+ },
+ "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way.
+ "a_key": "", # Properties of the object.
+ },
+ "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset}
+ },
+ "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
+ "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job.
+ "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object}
+ "A String",
+ ],
+ "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated.
+ "stages": { # A mapping from each stage to the information about that stage.
+ "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed.
+ "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage.
+ "A String",
+ ],
},
},
- "type": "A String", # The type of Cloud Dataflow job.
- "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
- "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
- "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
- "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
- "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
- "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL.
- { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce.
- "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL.
- "a_key": "", # Properties of the object.
- },
- "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job.
- "kind": "A String", # The kind of step in the Cloud Dataflow job.
+ },
+ "currentStateTime": "A String", # The timestamp associated with the current state.
+ "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher.
+ "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
+ "sdkSupportStatus": "A String", # The support status for this SDK version.
+ "version": "A String", # The version of the SDK used to run the job.
+ "versionDisplayName": "A String", # A readable string describing the version of the SDK.
+ },
+ "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
+ { # Metadata for a BigQuery connector used by the job.
+ "query": "A String", # Query used to access data in the connection.
+ "projectId": "A String", # Project accessed in the connection.
+ "table": "A String", # Table accessed in the connection.
+ "dataset": "A String", # Dataset accessed in the connection.
},
],
- "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
- { # A message describing the state of a particular execution stage.
- "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
- "executionStageName": "A String", # The name of the execution stage.
- "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
+ { # Metadata for a Datastore connector used by the job.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ "namespace": "A String", # Namespace used in the connection.
},
],
- "stepsLocation": "A String", # The GCS location where the steps are stored.
- "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
- }</pre>
+ "fileDetails": [ # Identification of a File source used in the Dataflow job.
+ { # Metadata for a File connector used by the job.
+ "filePattern": "A String", # File Pattern used to access files by the connector.
+ },
+ ],
+ "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
+ { # Metadata for a Spanner connector used by the job.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "databaseId": "A String", # DatabaseId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
+ { # Metadata for a PubSub connector used by the job.
+ "topic": "A String", # Topic accessed in the connection.
+ "subscription": "A String", # Subscription used in the connection.
+ },
+ ],
+ "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
+ { # Metadata for a BigTable connector used by the job.
+ "tableId": "A String", # TableId accessed in the connection.
+ "instanceId": "A String", # InstanceId accessed in the connection.
+ "projectId": "A String", # ProjectId accessed in the connection.
+ },
+ ],
+ },
+ "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job.
+ "type": "A String", # The type of Cloud Dataflow job.
+ "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it.
+ { # A message describing the state of a particular execution stage.
+ "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
+ "executionStageName": "A String", # The name of the execution stage.
+ "currentStateTime": "A String", # The time at which the stage transitioned to this state.
+ },
+ ],
+ "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?`
+ "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job.
+ "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot.
+ "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service.
+ "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size.
+ "a_key": "A String",
+ },
+ "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service.
+ "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it.
+ "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state.
+ "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL.
+ "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
+ { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning.
+ "kind": "A String", # Type of tranform this stage is executing.
+ "id": "A String", # Dataflow service generated id for this stage.
+ "componentTransform": [ # Transforms that comprise this execution stage.
+ { # Description of a transform executed as part of an execution stage.
+ "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ },
+ ],
+ "prerequisiteStage": [ # Other stages that must complete before this stage can run.
+ "A String",
+ ],
+ "outputSource": [ # Output sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "inputSource": [ # Input sources for this stage.
+ { # Description of an input or output of an execution stage.
+ "name": "A String", # Dataflow service generated name for this source.
+ "sizeBytes": "A String", # Size of the source, if measurable.
+ "userName": "A String", # Human-readable name for this source; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ },
+ ],
+ "componentSource": [ # Collections produced and consumed by component transforms of this stage.
+ { # Description of an interstitial value between transforms in an execution stage.
+ "userName": "A String", # Human-readable name for this transform; may be user or system generated.
+ "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated.
+ "name": "A String", # Dataflow service generated name for this source.
+ },
+ ],
+ "name": "A String", # Dataflow service generated name for this stage.
+ },
+ ],
+ "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
+ { # Description of the type, names/ids, and input/outputs for a transform.
+ "inputCollectionName": [ # User names for all collection inputs to this transform.
+ "A String",
+ ],
+ "id": "A String", # SDK generated id of this transform instance.
+ "name": "A String", # User provided name for this transform instance.
+ "outputCollectionName": [ # User names for all collection outputs to this transform.
+ "A String",
+ ],
+ "kind": "A String", # Type of transform.
+ "displayData": [ # Transform-specific display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ ],
+ "displayData": [ # Pipeline level display data.
+ { # Data provided with a pipeline or transform to provide descriptive info.
+ "int64Value": "A String", # Contains value if the data is of int64 type.
+ "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system.
+ "label": "A String", # An optional label to display in a dax UI for the element.
+ "floatValue": 3.14, # Contains value if the data is of float type.
+ "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip.
+ "url": "A String", # An optional full URL.
+ "boolValue": True or False, # Contains value if the data is of a boolean type.
+ "javaClassValue": "A String", # Contains value if the data is of java class type.
+ "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering.
+ "strValue": "A String", # Contains value if the data is of string type.
+ "durationValue": "A String", # Contains value if the data is of duration type.
+ "timestampValue": "A String", # Contains value if the data is of timestamp type.
+ },
+ ],
+ },
+ "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job.
+ "a_key": "A String",
+ },
+ "stepsLocation": "A String", # The GCS location where the steps are stored.
+ }</pre>
</div>
</body></html>
\ No newline at end of file