site_utils/metadata_reporter.py

# Copyright 2015 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.

"""
This module is designed to report metadata in a separated thread to avoid the
performance overhead of sending data to Elasticsearch using HTTP.

"""

import logging
import Queue
import time
import threading

import common
from autotest_lib.client.common_lib.cros.graphite import autotest_es


# Number of seconds to wait before checking queue again for uploading data.
_REPORT_INTERVAL_SECONDS = 5

_MAX_METADATA_QUEUE_SIZE = 100000
# Queue to buffer metadata to be reported.
metadata_queue = Queue.Queue(_MAX_METADATA_QUEUE_SIZE)

_report_lock = threading.Lock()
_abort = threading.Event()
_queue_full = threading.Event()

def queue(data):
    """Queue metadata to be uploaded in reporter thread.

    If the queue is full, an error will be logged for the first time the queue
    becomes full. The call does not wait or raise Queue.Full exception, so
    there is no overhead on the performance of caller, e.g., scheduler.

    @param data: A metadata entry, which should be a dictionary.
    """
    try:
        metadata_queue.put_nowait(data)
        if _queue_full.is_set():
            logging.info('Metadata queue is available to receive new data '
                         'again.')
            _queue_full.clear()
    except Queue.Full:
        if not _queue_full.is_set():
            _queue_full.set()
            logging.error('Metadata queue is full, cannot report data. '
                          'Consider increasing the value of '
                          '_MAX_METADATA_QUEUE_SIZE. Its current value is set '
                          'to %d.', _MAX_METADATA_QUEUE_SIZE)


def _run():
    """Report metadata in the queue until being aborted.
    """
    try:
        while True:
            start_time = time.time()
            data_list = []
            while (not metadata_queue.empty() and
                   len(data_list) < _MAX_METADATA_QUEUE_SIZE):
                data_list.append(metadata_queue.get_nowait())
            if data_list:
                autotest_es.bulk_post(data_list=data_list)
                logging.info('%d entries of metadata uploaded in %s '
                             'seconds.', len(data_list),
                             time.time()-start_time)
            sleep_time = _REPORT_INTERVAL_SECONDS - time.time() + start_time
            if sleep_time < 0:
                sleep_time = 0.5
            _abort.wait(timeout=sleep_time)
    except Exception as e:
        logging.error('Metadata reporter thread failed with error: %s', e)
        raise
    finally:
        logging.info('Metadata reporting thread is exiting.')
        _abort.clear()
        _report_lock.release()


def start():
    """Start the thread to report metadata.
    """
    # The lock makes sure there is only one reporting thread working.
    if _report_lock.locked():
        logging.error('There is already a metadata reporter thread.')
        return

    _report_lock.acquire()
    reporting_thread = threading.Thread(target=_run)
    # Make it a daemon thread so it doesn't need to be closed explicitly.
    reporting_thread.setDaemon(True)
    reporting_thread.start()
    logging.info('Metadata reporting thread is started.')


def abort():
    """Abort the thread to report metadata.

    The call will wait up to 5 seconds for existing data to be uploaded.
    """
    if  not _report_lock.locked():
        logging.error('The metadata reporting thread has already exited.')
        return

    _abort.set()
    logging.info('Waiting up to %s seconds for metadata reporting thread to '
                 'complete.', _REPORT_INTERVAL_SECONDS)
    _abort.wait(_REPORT_INTERVAL_SECONDS)