Source code for apache_beam.runners.dataflow.test_dataflow_runner

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"""Wrapper of Beam runners that's built for running and verifying e2e tests."""

# pytype: skip-file

import logging
import time

from apache_beam.internal import pickler
from apache_beam.options.pipeline_options import GoogleCloudOptions
from apache_beam.options.pipeline_options import StandardOptions
from apache_beam.options.pipeline_options import TestOptions
from apache_beam.runners.dataflow.dataflow_runner import DataflowRunner
from apache_beam.runners.runner import PipelineState

__all__ = ['TestDataflowRunner']

# Dataflow take up to 10mins for the long tail of starting/stopping worker
# pool.

_LOGGER = logging.getLogger(__name__)

[docs]class TestDataflowRunner(DataflowRunner):
[docs] def run_pipeline(self, pipeline, options): """Execute test pipeline and verify test matcher""" test_options = options.view_as(TestOptions) on_success_matcher = test_options.on_success_matcher wait_duration = test_options.wait_until_finish_duration is_streaming = options.view_as(StandardOptions).streaming # [BEAM-1889] Do not send this to remote workers also, there is no need to # send this option to remote executors. test_options.on_success_matcher = None self.result = super().run_pipeline(pipeline, options) if self.result.has_job: # TODO(markflyhigh)( Use # print since Nose dosen't show logs in some cases. print('Worker logs: %s' % self.build_console_url(options))'Console log: ') try: self.wait_until_in_state(PipelineState.RUNNING) if is_streaming and not wait_duration: _LOGGER.warning('Waiting indefinitely for streaming job.') self.result.wait_until_finish(duration=wait_duration) if on_success_matcher: from hamcrest import assert_that as hc_assert_that hc_assert_that(self.result, pickler.loads(on_success_matcher)) finally: if not self.result.is_in_terminal_state(): self.result.cancel() self.wait_until_in_state(PipelineState.CANCELLED) return self.result
[docs] def build_console_url(self, options): """Build a console url of Dataflow job.""" project = options.view_as(GoogleCloudOptions).project region_id = options.view_as(GoogleCloudOptions).region job_id = self.result.job_id() return ( '' % (region_id, job_id, project))
[docs] def wait_until_in_state(self, expected_state, timeout=WAIT_IN_STATE_TIMEOUT): """Wait until Dataflow pipeline enters a certain state.""" consoleUrl = ( "Console URL:" f"<regionId>/{self.result.job_id()}?project=<projectId>") if not self.result.has_job: _LOGGER.error(consoleUrl) raise IOError('Failed to get the Dataflow job id.') start_time = time.time() while time.time() - start_time <= timeout: job_state = self.result.state if self.result.is_in_terminal_state() or job_state == expected_state: return job_state time.sleep(5) _LOGGER.error(consoleUrl) raise RuntimeError( 'Timeout after %d seconds while waiting for job %s ' 'enters expected state %s. Current state is %s.' % (timeout, self.result.job_id(), expected_state, self.result.state))