| # |
| # Licensed to the Apache Software Foundation (ASF) under one or more |
| # contributor license agreements. See the NOTICE file distributed with |
| # this work for additional information regarding copyright ownership. |
| # The ASF licenses this file to You under the Apache License, Version 2.0 |
| # (the "License"); you may not use this file except in compliance with |
| # the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| """End-to-end test for the wordcount example.""" |
| |
| # pytype: skip-file |
| |
| import logging |
| import os |
| import time |
| import unittest |
| |
| import pytest |
| from hamcrest.core.core.allof import all_of |
| from nose.plugins.attrib import attr |
| |
| from apache_beam.examples import wordcount |
| from apache_beam.testing.load_tests.load_test_metrics_utils import InfluxDBMetricsPublisherOptions |
| from apache_beam.testing.load_tests.load_test_metrics_utils import MetricsReader |
| from apache_beam.testing.pipeline_verifiers import FileChecksumMatcher |
| from apache_beam.testing.pipeline_verifiers import PipelineStateMatcher |
| from apache_beam.testing.test_pipeline import TestPipeline |
| from apache_beam.testing.test_utils import delete_files |
| |
| |
| class WordCountIT(unittest.TestCase): |
| |
| # Enable nose tests running in parallel |
| _multiprocess_can_split_ = True |
| |
| # The default checksum is a SHA-1 hash generated from a sorted list of |
| # lines read from expected output. This value corresponds to the default |
| # input of WordCount example. |
| DEFAULT_CHECKSUM = '33535a832b7db6d78389759577d4ff495980b9c0' |
| |
| @attr('IT') |
| def test_wordcount_it(self): |
| self._run_wordcount_it(wordcount.run) |
| |
| @attr('IT') |
| @pytest.mark.it_validatescontainer |
| def test_wordcount_fnapi_it(self): |
| self._run_wordcount_it(wordcount.run, experiment='beam_fn_api') |
| |
| @pytest.mark.it_validatescontainer |
| def test_wordcount_it_with_prebuilt_sdk_container_local_docker(self): |
| self._run_wordcount_it( |
| wordcount.run, |
| experiment='beam_fn_api', |
| prebuild_sdk_container_engine='local_docker') |
| |
| @pytest.mark.it_validatescontainer |
| def test_wordcount_it_with_prebuilt_sdk_container_cloud_build(self): |
| self._run_wordcount_it( |
| wordcount.run, |
| experiment='beam_fn_api', |
| prebuild_sdk_container_engine='cloud_build') |
| |
| def _run_wordcount_it(self, run_wordcount, **opts): |
| test_pipeline = TestPipeline(is_integration_test=True) |
| extra_opts = {} |
| |
| # Set extra options to the pipeline for test purpose |
| test_output = '/'.join([ |
| test_pipeline.get_option('output'), |
| str(int(time.time() * 1000)), |
| 'results' |
| ]) |
| extra_opts['output'] = test_output |
| |
| test_input = test_pipeline.get_option('input') |
| if test_input: |
| extra_opts['input'] = test_input |
| |
| arg_sleep_secs = test_pipeline.get_option('sleep_secs') |
| sleep_secs = int(arg_sleep_secs) if arg_sleep_secs is not None else None |
| expect_checksum = ( |
| test_pipeline.get_option('expect_checksum') or self.DEFAULT_CHECKSUM) |
| pipeline_verifiers = [ |
| PipelineStateMatcher(), |
| FileChecksumMatcher( |
| test_output + '*-of-*', expect_checksum, sleep_secs) |
| ] |
| extra_opts['on_success_matcher'] = all_of(*pipeline_verifiers) |
| extra_opts.update(opts) |
| |
| # Register clean up before pipeline execution |
| self.addCleanup(delete_files, [test_output + '*']) |
| |
| publish_to_bq = bool( |
| test_pipeline.get_option('publish_to_big_query') or False) |
| |
| # Start measure time for performance test |
| start_time = time.time() |
| |
| # Get pipeline options from command argument: --test-pipeline-options, |
| # and start pipeline job by calling pipeline main function. |
| run_wordcount( |
| test_pipeline.get_full_options_as_args(**extra_opts), |
| save_main_session=False, |
| ) |
| |
| end_time = time.time() |
| run_time = end_time - start_time |
| |
| if publish_to_bq: |
| self._publish_metrics(test_pipeline, run_time) |
| |
| def _publish_metrics(self, pipeline, metric_value): |
| influx_options = InfluxDBMetricsPublisherOptions( |
| pipeline.get_option('influx_measurement'), |
| pipeline.get_option('influx_db_name'), |
| pipeline.get_option('influx_hostname'), |
| os.getenv('INFLUXDB_USER'), |
| os.getenv('INFLUXDB_USER_PASSWORD'), |
| ) |
| metric_reader = MetricsReader( |
| project_name=pipeline.get_option('project'), |
| bq_table=pipeline.get_option('metrics_table'), |
| bq_dataset=pipeline.get_option('metrics_dataset'), |
| publish_to_bq=True, |
| influxdb_options=influx_options, |
| ) |
| |
| metric_reader.publish_values([( |
| 'runtime', |
| metric_value, |
| )]) |
| |
| |
| if __name__ == '__main__': |
| logging.getLogger().setLevel(logging.DEBUG) |
| unittest.main() |