chore: Update discovery artifacts (#1516)
## Deleted keys were detected in the following stable discovery artifacts:
displayvideo v1 https://github.com/googleapis/google-api-python-client/commit/0ff4fae98fadd0e31eb09ff81656b87201d75d2b
file v1 https://github.com/googleapis/google-api-python-client/commit/ab13790877b89e112fd27b738462077c45408557
## Deleted keys were detected in the following pre-stable discovery artifacts:
compute alpha https://github.com/googleapis/google-api-python-client/commit/36050a3ad6fad1e5aec6c18085fbcad1564ceb1f
containeranalysis v1alpha1 https://github.com/googleapis/google-api-python-client/commit/e442b58fc9abfbbb37dc5b50cf17ba8dea508cba
file v1beta1 https://github.com/googleapis/google-api-python-client/commit/ab13790877b89e112fd27b738462077c45408557
## Discovery Artifact Change Summary:
fix(androidpublisher): update the api https://github.com/googleapis/google-api-python-client/commit/78ee7f700efa8d29a4a1ca3e23f1381c4d04c86a
feat(apigee): update the api https://github.com/googleapis/google-api-python-client/commit/59348e4809ff48906ffa356a0ecc867eb66376bd
feat(appengine): update the api https://github.com/googleapis/google-api-python-client/commit/a358ffd61a7671a7b3a90ccc329393feb80bc932
feat(bigquery): update the api https://github.com/googleapis/google-api-python-client/commit/fe54736e2583dd4f9efefa8fb5a6378741d6bf87
feat(cloudasset): update the api https://github.com/googleapis/google-api-python-client/commit/5b89c7b9eb3abee497fac27f2ba12208b257240f
feat(compute): update the api https://github.com/googleapis/google-api-python-client/commit/36050a3ad6fad1e5aec6c18085fbcad1564ceb1f
feat(contactcenterinsights): update the api https://github.com/googleapis/google-api-python-client/commit/c5bac63feeadd4cccc635d69af7e0f32a5df5bc3
feat(container): update the api https://github.com/googleapis/google-api-python-client/commit/3f4ac75311743c0b3e77647f3085374b5d898d01
feat(containeranalysis): update the api https://github.com/googleapis/google-api-python-client/commit/e442b58fc9abfbbb37dc5b50cf17ba8dea508cba
feat(displayvideo): update the api https://github.com/googleapis/google-api-python-client/commit/0ff4fae98fadd0e31eb09ff81656b87201d75d2b
feat(documentai): update the api https://github.com/googleapis/google-api-python-client/commit/4b0a7ed0cbef5031f7df162e8aa7629ba9073dc3
feat(file): update the api https://github.com/googleapis/google-api-python-client/commit/ab13790877b89e112fd27b738462077c45408557
feat(gkehub): update the api https://github.com/googleapis/google-api-python-client/commit/b168cc69436840e8c9a170863b13a4db253b9f5c
feat(iam): update the api https://github.com/googleapis/google-api-python-client/commit/88ebba5edbeb6dab547a6c57541f13dd13b95e23
feat(jobs): update the api https://github.com/googleapis/google-api-python-client/commit/eaffca049c02851d7c1b3a795d901e60616430df
feat(managedidentities): update the api https://github.com/googleapis/google-api-python-client/commit/ad3f2c91960b905126ae47c0777b27704aa02c64
feat(monitoring): update the api https://github.com/googleapis/google-api-python-client/commit/7317835fe784c723ed6e290ab3da515b68a25c5f
feat(prod_tt_sasportal): update the api https://github.com/googleapis/google-api-python-client/commit/ec0c06297952f922adfa6b4c265577846d2493d0
feat(recaptchaenterprise): update the api https://github.com/googleapis/google-api-python-client/commit/234d3f983a92fca973fcc42bf8e69e470f50fef5
feat(sqladmin): update the api https://github.com/googleapis/google-api-python-client/commit/f30d144526f01a5a69832166d4271b2288fdabad
diff --git a/docs/dyn/jobs_v4.projects.tenants.jobs.html b/docs/dyn/jobs_v4.projects.tenants.jobs.html
index 7337c8b..822f159 100644
--- a/docs/dyn/jobs_v4.projects.tenants.jobs.html
+++ b/docs/dyn/jobs_v4.projects.tenants.jobs.html
@@ -1532,9 +1532,9 @@
{ # The Request body of the `SearchJobs` call.
"customRankingInfo": { # Custom ranking information for SearchJobsRequest. # Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm).
"importanceLevel": "A String", # Required. Controls over how important the score of CustomRankingInfo.ranking_expression gets applied to job's final ranking position. An error is thrown if not specified.
- "rankingExpression": "A String", # Required. Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm). A combination of the ranking expression and relevance score is used to determine job's final ranking position. The syntax for this expression is a subset of Google SQL syntax. Supported operators are: +, -, *, /, where the left and right side of the operator is either a numeric Job.custom_attributes key, integer/double value or an expression that can be evaluated to a number. Parenthesis are supported to adjust calculation precedence. The expression must be < 100 characters in length. The expression is considered invalid for a job if the expression references custom attributes that are not populated on the job or if the expression results in a divide by zero. If an expression is invalid for a job, that job is demoted to the end of the results. Sample ranking expression (year + 25) * 0.25 - (freshness / 0.5)
+ "rankingExpression": "A String", # Required. Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm). A combination of the ranking expression and relevance score is used to determine job's final ranking position. The syntax for this expression is a subset of Google SQL syntax. Supported operators are: +, -, *, /, where the left and right side of the operator is either a numeric Job.custom_attributes key, integer/double value or an expression that can be evaluated to a number. Parenthesis are supported to adjust calculation precedence. The expression must be < 200 characters in length. The expression is considered invalid for a job if the expression references custom attributes that are not populated on the job or if the expression results in a divide by zero. If an expression is invalid for a job, that job is demoted to the end of the results. Sample ranking expression (year + 25) * 0.25 - (freshness / 0.5)
},
- "disableKeywordMatch": True or False, # Controls whether to disable exact keyword match on Job.title, Job.description, Job.company_display_name, Job.addresses, Job.qualifications. When disable keyword match is turned off, a keyword match returns jobs that do not match given category filters when there are matching keywords. For example, for the query "program manager," a result is returned even if the job posting has the title "software developer," which doesn't fall into "program manager" ontology, but does have "program manager" appearing in its description. For queries like "cloud" that don't contain title or location specific ontology, jobs with "cloud" keyword matches are returned regardless of this flag's value. Use Company.keyword_searchable_job_custom_attributes if company-specific globally matched custom field/attribute string values are needed. Enabling keyword match improves recall of subsequent search requests. Defaults to false.
+ "disableKeywordMatch": True or False, # This field is deprecated. Please use SearchJobsRequest.keyword_match_mode going forward. To migrate, disable_keyword_match set to false maps to KeywordMatchMode.KEYWORD_MATCH_ALL, and disable_keyword_match set to true maps to KeywordMatchMode.KEYWORD_MATCH_DISABLED. If SearchJobsRequest.keyword_match_mode is set, this field is ignored. Controls whether to disable exact keyword match on Job.title, Job.description, Job.company_display_name, Job.addresses, Job.qualifications. When disable keyword match is turned off, a keyword match returns jobs that do not match given category filters when there are matching keywords. For example, for the query "program manager," a result is returned even if the job posting has the title "software developer," which doesn't fall into "program manager" ontology, but does have "program manager" appearing in its description. For queries like "cloud" that don't contain title or location specific ontology, jobs with "cloud" keyword matches are returned regardless of this flag's value. Use Company.keyword_searchable_job_custom_attributes if company-specific globally matched custom field/attribute string values are needed. Enabling keyword match improves recall of subsequent search requests. Defaults to false.
"diversificationLevel": "A String", # Controls whether highly similar jobs are returned next to each other in the search results. Jobs are identified as highly similar based on their titles, job categories, and locations. Highly similar results are clustered so that only one representative job of the cluster is displayed to the job seeker higher up in the results, with the other jobs being displayed lower down in the results. Defaults to DiversificationLevel.SIMPLE if no value is specified.
"enableBroadening": True or False, # Controls whether to broaden the search when it produces sparse results. Broadened queries append results to the end of the matching results list. Defaults to false.
"histogramQueries": [ # An expression specifies a histogram request against matching jobs. Expression syntax is an aggregation function call with histogram facets and other options. Available aggregation function calls are: * `count(string_histogram_facet)`: Count the number of matching entities, for each distinct attribute value. * `count(numeric_histogram_facet, list of buckets)`: Count the number of matching entities within each bucket. Data types: * Histogram facet: facet names with format a-zA-Z+. * String: string like "any string with backslash escape for quote(\")." * Number: whole number and floating point number like 10, -1 and -0.01. * List: list of elements with comma(,) separator surrounded by square brackets, for example, [1, 2, 3] and ["one", "two", "three"]. Built-in constants: * MIN (minimum number similar to java Double.MIN_VALUE) * MAX (maximum number similar to java Double.MAX_VALUE) Built-in functions: * bucket(start, end[, label]): bucket built-in function creates a bucket with range of start, end). Note that the end is exclusive, for example, bucket(1, MAX, "positive number") or bucket(1, 10). Job histogram facets: * company_display_name: histogram by [Job.company_display_name. * employment_type: histogram by Job.employment_types, for example, "FULL_TIME", "PART_TIME". * company_size: histogram by CompanySize, for example, "SMALL", "MEDIUM", "BIG". * publish_time_in_day: histogram by the Job.posting_publish_time in days. Must specify list of numeric buckets in spec. * publish_time_in_month: histogram by the Job.posting_publish_time in months. Must specify list of numeric buckets in spec. * publish_time_in_year: histogram by the Job.posting_publish_time in years. Must specify list of numeric buckets in spec. * degree_types: histogram by the Job.degree_types, for example, "Bachelors", "Masters". * job_level: histogram by the Job.job_level, for example, "Entry Level". * country: histogram by the country code of jobs, for example, "US", "FR". * admin1: histogram by the admin1 code of jobs, which is a global placeholder referring to the state, province, or the particular term a country uses to define the geographic structure below the country level, for example, "CA", "IL". * city: histogram by a combination of the "city name, admin1 code". For example, "Mountain View, CA", "New York, NY". * admin1_country: histogram by a combination of the "admin1 code, country", for example, "CA, US", "IL, US". * city_coordinate: histogram by the city center's GPS coordinates (latitude and longitude), for example, 37.4038522,-122.0987765. Since the coordinates of a city center can change, customers may need to refresh them periodically. * locale: histogram by the Job.language_code, for example, "en-US", "fr-FR". * language: histogram by the language subtag of the Job.language_code, for example, "en", "fr". * category: histogram by the JobCategory, for example, "COMPUTER_AND_IT", "HEALTHCARE". * base_compensation_unit: histogram by the CompensationInfo.CompensationUnit of base salary, for example, "WEEKLY", "MONTHLY". * base_compensation: histogram by the base salary. Must specify list of numeric buckets to group results by. * annualized_base_compensation: histogram by the base annualized salary. Must specify list of numeric buckets to group results by. * annualized_total_compensation: histogram by the total annualized salary. Must specify list of numeric buckets to group results by. * string_custom_attribute: histogram by string Job.custom_attributes. Values can be accessed via square bracket notations like string_custom_attribute["key1"]. * numeric_custom_attribute: histogram by numeric Job.custom_attributes. Values can be accessed via square bracket notations like numeric_custom_attribute["key1"]. Must specify list of numeric buckets to group results by. Example expressions: * `count(admin1)` * `count(base_compensation, [bucket(1000, 10000), bucket(10000, 100000), bucket(100000, MAX)])` * `count(string_custom_attribute["some-string-custom-attribute"])` * `count(numeric_custom_attribute["some-numeric-custom-attribute"], [bucket(MIN, 0, "negative"), bucket(0, MAX, "non-negative")])`
@@ -1618,6 +1618,7 @@
"queryLanguageCode": "A String", # The language code of query. For example, "en-US". This field helps to better interpret the query. If a value isn't specified, the query language code is automatically detected, which may not be accurate. Language code should be in BCP-47 format, such as "en-US" or "sr-Latn". For more information, see [Tags for Identifying Languages](https://tools.ietf.org/html/bcp47).
},
"jobView": "A String", # The desired job attributes returned for jobs in the search response. Defaults to JobView.JOB_VIEW_SMALL if no value is specified.
+ "keywordMatchMode": "A String", # Controls what keyword match options to use. If both keyword_match_mode and disable_keyword_match are set, keyword_match_mode will take precedence. Defaults to KeywordMatchMode.KEYWORD_MATCH_ALL if no value is specified.
"maxPageSize": 42, # A limit on the number of jobs returned in the search results. Increasing this value above the default value of 10 can increase search response time. The value can be between 1 and 100.
"offset": 42, # An integer that specifies the current offset (that is, starting result location, amongst the jobs deemed by the API as relevant) in search results. This field is only considered if page_token is unset. The maximum allowed value is 5000. Otherwise an error is thrown. For example, 0 means to return results starting from the first matching job, and 10 means to return from the 11th job. This can be used for pagination, (for example, pageSize = 10 and offset = 10 means to return from the second page).
"orderBy": "A String", # The criteria determining how search results are sorted. Default is `"relevance desc"`. Supported options are: * `"relevance desc"`: By relevance descending, as determined by the API algorithms. Relevance thresholding of query results is only available with this ordering. * `"posting_publish_time desc"`: By Job.posting_publish_time descending. * `"posting_update_time desc"`: By Job.posting_update_time descending. * `"title"`: By Job.title ascending. * `"title desc"`: By Job.title descending. * `"annualized_base_compensation"`: By job's CompensationInfo.annualized_base_compensation_range ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_base_compensation desc"`: By job's CompensationInfo.annualized_base_compensation_range descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_total_compensation"`: By job's CompensationInfo.annualized_total_compensation_range ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_total_compensation desc"`: By job's CompensationInfo.annualized_total_compensation_range descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"custom_ranking desc"`: By the relevance score adjusted to the SearchJobsRequest.CustomRankingInfo.ranking_expression with weight factor assigned by SearchJobsRequest.CustomRankingInfo.importance_level in descending order. * Location sorting: Use the special syntax to order jobs by distance: `"distance_from('Hawaii')"`: Order by distance from Hawaii. `"distance_from(19.89, 155.5)"`: Order by distance from a coordinate. `"distance_from('Hawaii'), distance_from('Puerto Rico')"`: Order by multiple locations. See details below. `"distance_from('Hawaii'), distance_from(19.89, 155.5)"`: Order by multiple locations. See details below. The string can have a maximum of 256 characters. When multiple distance centers are provided, a job that is close to any of the distance centers would have a high rank. When a job has multiple locations, the job location closest to one of the distance centers will be used. Jobs that don't have locations will be ranked at the bottom. Distance is calculated with a precision of 11.3 meters (37.4 feet). Diversification strategy is still applied unless explicitly disabled in diversification_level.
@@ -1883,9 +1884,9 @@
{ # The Request body of the `SearchJobs` call.
"customRankingInfo": { # Custom ranking information for SearchJobsRequest. # Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm).
"importanceLevel": "A String", # Required. Controls over how important the score of CustomRankingInfo.ranking_expression gets applied to job's final ranking position. An error is thrown if not specified.
- "rankingExpression": "A String", # Required. Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm). A combination of the ranking expression and relevance score is used to determine job's final ranking position. The syntax for this expression is a subset of Google SQL syntax. Supported operators are: +, -, *, /, where the left and right side of the operator is either a numeric Job.custom_attributes key, integer/double value or an expression that can be evaluated to a number. Parenthesis are supported to adjust calculation precedence. The expression must be < 100 characters in length. The expression is considered invalid for a job if the expression references custom attributes that are not populated on the job or if the expression results in a divide by zero. If an expression is invalid for a job, that job is demoted to the end of the results. Sample ranking expression (year + 25) * 0.25 - (freshness / 0.5)
+ "rankingExpression": "A String", # Required. Controls over how job documents get ranked on top of existing relevance score (determined by API algorithm). A combination of the ranking expression and relevance score is used to determine job's final ranking position. The syntax for this expression is a subset of Google SQL syntax. Supported operators are: +, -, *, /, where the left and right side of the operator is either a numeric Job.custom_attributes key, integer/double value or an expression that can be evaluated to a number. Parenthesis are supported to adjust calculation precedence. The expression must be < 200 characters in length. The expression is considered invalid for a job if the expression references custom attributes that are not populated on the job or if the expression results in a divide by zero. If an expression is invalid for a job, that job is demoted to the end of the results. Sample ranking expression (year + 25) * 0.25 - (freshness / 0.5)
},
- "disableKeywordMatch": True or False, # Controls whether to disable exact keyword match on Job.title, Job.description, Job.company_display_name, Job.addresses, Job.qualifications. When disable keyword match is turned off, a keyword match returns jobs that do not match given category filters when there are matching keywords. For example, for the query "program manager," a result is returned even if the job posting has the title "software developer," which doesn't fall into "program manager" ontology, but does have "program manager" appearing in its description. For queries like "cloud" that don't contain title or location specific ontology, jobs with "cloud" keyword matches are returned regardless of this flag's value. Use Company.keyword_searchable_job_custom_attributes if company-specific globally matched custom field/attribute string values are needed. Enabling keyword match improves recall of subsequent search requests. Defaults to false.
+ "disableKeywordMatch": True or False, # This field is deprecated. Please use SearchJobsRequest.keyword_match_mode going forward. To migrate, disable_keyword_match set to false maps to KeywordMatchMode.KEYWORD_MATCH_ALL, and disable_keyword_match set to true maps to KeywordMatchMode.KEYWORD_MATCH_DISABLED. If SearchJobsRequest.keyword_match_mode is set, this field is ignored. Controls whether to disable exact keyword match on Job.title, Job.description, Job.company_display_name, Job.addresses, Job.qualifications. When disable keyword match is turned off, a keyword match returns jobs that do not match given category filters when there are matching keywords. For example, for the query "program manager," a result is returned even if the job posting has the title "software developer," which doesn't fall into "program manager" ontology, but does have "program manager" appearing in its description. For queries like "cloud" that don't contain title or location specific ontology, jobs with "cloud" keyword matches are returned regardless of this flag's value. Use Company.keyword_searchable_job_custom_attributes if company-specific globally matched custom field/attribute string values are needed. Enabling keyword match improves recall of subsequent search requests. Defaults to false.
"diversificationLevel": "A String", # Controls whether highly similar jobs are returned next to each other in the search results. Jobs are identified as highly similar based on their titles, job categories, and locations. Highly similar results are clustered so that only one representative job of the cluster is displayed to the job seeker higher up in the results, with the other jobs being displayed lower down in the results. Defaults to DiversificationLevel.SIMPLE if no value is specified.
"enableBroadening": True or False, # Controls whether to broaden the search when it produces sparse results. Broadened queries append results to the end of the matching results list. Defaults to false.
"histogramQueries": [ # An expression specifies a histogram request against matching jobs. Expression syntax is an aggregation function call with histogram facets and other options. Available aggregation function calls are: * `count(string_histogram_facet)`: Count the number of matching entities, for each distinct attribute value. * `count(numeric_histogram_facet, list of buckets)`: Count the number of matching entities within each bucket. Data types: * Histogram facet: facet names with format a-zA-Z+. * String: string like "any string with backslash escape for quote(\")." * Number: whole number and floating point number like 10, -1 and -0.01. * List: list of elements with comma(,) separator surrounded by square brackets, for example, [1, 2, 3] and ["one", "two", "three"]. Built-in constants: * MIN (minimum number similar to java Double.MIN_VALUE) * MAX (maximum number similar to java Double.MAX_VALUE) Built-in functions: * bucket(start, end[, label]): bucket built-in function creates a bucket with range of start, end). Note that the end is exclusive, for example, bucket(1, MAX, "positive number") or bucket(1, 10). Job histogram facets: * company_display_name: histogram by [Job.company_display_name. * employment_type: histogram by Job.employment_types, for example, "FULL_TIME", "PART_TIME". * company_size: histogram by CompanySize, for example, "SMALL", "MEDIUM", "BIG". * publish_time_in_day: histogram by the Job.posting_publish_time in days. Must specify list of numeric buckets in spec. * publish_time_in_month: histogram by the Job.posting_publish_time in months. Must specify list of numeric buckets in spec. * publish_time_in_year: histogram by the Job.posting_publish_time in years. Must specify list of numeric buckets in spec. * degree_types: histogram by the Job.degree_types, for example, "Bachelors", "Masters". * job_level: histogram by the Job.job_level, for example, "Entry Level". * country: histogram by the country code of jobs, for example, "US", "FR". * admin1: histogram by the admin1 code of jobs, which is a global placeholder referring to the state, province, or the particular term a country uses to define the geographic structure below the country level, for example, "CA", "IL". * city: histogram by a combination of the "city name, admin1 code". For example, "Mountain View, CA", "New York, NY". * admin1_country: histogram by a combination of the "admin1 code, country", for example, "CA, US", "IL, US". * city_coordinate: histogram by the city center's GPS coordinates (latitude and longitude), for example, 37.4038522,-122.0987765. Since the coordinates of a city center can change, customers may need to refresh them periodically. * locale: histogram by the Job.language_code, for example, "en-US", "fr-FR". * language: histogram by the language subtag of the Job.language_code, for example, "en", "fr". * category: histogram by the JobCategory, for example, "COMPUTER_AND_IT", "HEALTHCARE". * base_compensation_unit: histogram by the CompensationInfo.CompensationUnit of base salary, for example, "WEEKLY", "MONTHLY". * base_compensation: histogram by the base salary. Must specify list of numeric buckets to group results by. * annualized_base_compensation: histogram by the base annualized salary. Must specify list of numeric buckets to group results by. * annualized_total_compensation: histogram by the total annualized salary. Must specify list of numeric buckets to group results by. * string_custom_attribute: histogram by string Job.custom_attributes. Values can be accessed via square bracket notations like string_custom_attribute["key1"]. * numeric_custom_attribute: histogram by numeric Job.custom_attributes. Values can be accessed via square bracket notations like numeric_custom_attribute["key1"]. Must specify list of numeric buckets to group results by. Example expressions: * `count(admin1)` * `count(base_compensation, [bucket(1000, 10000), bucket(10000, 100000), bucket(100000, MAX)])` * `count(string_custom_attribute["some-string-custom-attribute"])` * `count(numeric_custom_attribute["some-numeric-custom-attribute"], [bucket(MIN, 0, "negative"), bucket(0, MAX, "non-negative")])`
@@ -1969,6 +1970,7 @@
"queryLanguageCode": "A String", # The language code of query. For example, "en-US". This field helps to better interpret the query. If a value isn't specified, the query language code is automatically detected, which may not be accurate. Language code should be in BCP-47 format, such as "en-US" or "sr-Latn". For more information, see [Tags for Identifying Languages](https://tools.ietf.org/html/bcp47).
},
"jobView": "A String", # The desired job attributes returned for jobs in the search response. Defaults to JobView.JOB_VIEW_SMALL if no value is specified.
+ "keywordMatchMode": "A String", # Controls what keyword match options to use. If both keyword_match_mode and disable_keyword_match are set, keyword_match_mode will take precedence. Defaults to KeywordMatchMode.KEYWORD_MATCH_ALL if no value is specified.
"maxPageSize": 42, # A limit on the number of jobs returned in the search results. Increasing this value above the default value of 10 can increase search response time. The value can be between 1 and 100.
"offset": 42, # An integer that specifies the current offset (that is, starting result location, amongst the jobs deemed by the API as relevant) in search results. This field is only considered if page_token is unset. The maximum allowed value is 5000. Otherwise an error is thrown. For example, 0 means to return results starting from the first matching job, and 10 means to return from the 11th job. This can be used for pagination, (for example, pageSize = 10 and offset = 10 means to return from the second page).
"orderBy": "A String", # The criteria determining how search results are sorted. Default is `"relevance desc"`. Supported options are: * `"relevance desc"`: By relevance descending, as determined by the API algorithms. Relevance thresholding of query results is only available with this ordering. * `"posting_publish_time desc"`: By Job.posting_publish_time descending. * `"posting_update_time desc"`: By Job.posting_update_time descending. * `"title"`: By Job.title ascending. * `"title desc"`: By Job.title descending. * `"annualized_base_compensation"`: By job's CompensationInfo.annualized_base_compensation_range ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_base_compensation desc"`: By job's CompensationInfo.annualized_base_compensation_range descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_total_compensation"`: By job's CompensationInfo.annualized_total_compensation_range ascending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"annualized_total_compensation desc"`: By job's CompensationInfo.annualized_total_compensation_range descending. Jobs whose annualized base compensation is unspecified are put at the end of search results. * `"custom_ranking desc"`: By the relevance score adjusted to the SearchJobsRequest.CustomRankingInfo.ranking_expression with weight factor assigned by SearchJobsRequest.CustomRankingInfo.importance_level in descending order. * Location sorting: Use the special syntax to order jobs by distance: `"distance_from('Hawaii')"`: Order by distance from Hawaii. `"distance_from(19.89, 155.5)"`: Order by distance from a coordinate. `"distance_from('Hawaii'), distance_from('Puerto Rico')"`: Order by multiple locations. See details below. `"distance_from('Hawaii'), distance_from(19.89, 155.5)"`: Order by multiple locations. See details below. The string can have a maximum of 256 characters. When multiple distance centers are provided, a job that is close to any of the distance centers would have a high rank. When a job has multiple locations, the job location closest to one of the distance centers will be used. Jobs that don't have locations will be ranked at the bottom. Distance is calculated with a precision of 11.3 meters (37.4 feet). Diversification strategy is still applied unless explicitly disabled in diversification_level.