def test_bigquery_tornadoes_it(self): test_pipeline = TestPipeline(is_integration_test=True) # Set extra options to the pipeline for test purpose project = test_pipeline.get_option('project') dataset = 'BigQueryTornadoesIT' table = 'monthly_tornadoes_%s' % int(round(time.time() * 1000)) output_table = '.'.join([dataset, table]) query = 'SELECT month, tornado_count FROM [%s]' % output_table pipeline_verifiers = [PipelineStateMatcher(), BigqueryMatcher( project=project, query=query, checksum=self.DEFAULT_CHECKSUM)] extra_opts = {'output': output_table, 'on_success_matcher': all_of(*pipeline_verifiers)} # Register cleanup before pipeline execution. self.addCleanup(utils.delete_bq_table, project, dataset, table) # Get pipeline options from command argument: --test-pipeline-options, # and start pipeline job by calling pipeline main function. bigquery_tornadoes.run( test_pipeline.get_full_options_as_args(**extra_opts))
def test_bigquery_tornadoes_it(self): test_pipeline = TestPipeline(is_integration_test=True) # Set extra options to the pipeline for test purpose output_table = ('BigQueryTornadoesIT' '.monthly_tornadoes_%s' % int(round(time.time() * 1000))) query = 'SELECT month, tornado_count FROM [%s]' % output_table pipeline_verifiers = [PipelineStateMatcher(), BigqueryMatcher( project=test_pipeline.get_option('project'), query=query, checksum=self.DEFAULT_CHECKSUM)] extra_opts = {'output': output_table, 'on_success_matcher': all_of(*pipeline_verifiers)} # Get pipeline options from command argument: --test-pipeline-options, # and start pipeline job by calling pipeline main function. bigquery_tornadoes.run( test_pipeline.get_full_options_as_args(**extra_opts))
def test_bigquery_tornadoes_it(self): test_pipeline = TestPipeline(is_integration_test=True) # Set extra options to the pipeline for test purpose project = test_pipeline.get_option('project') dataset = 'BigQueryTornadoesIT' table = 'monthly_tornadoes_%s' % int(round(time.time() * 1000)) output_table = '.'.join([dataset, table]) query = 'SELECT month, tornado_count FROM `%s`' % output_table pipeline_verifiers = [PipelineStateMatcher(), BigqueryMatcher( project=project, query=query, checksum=self.DEFAULT_CHECKSUM)] extra_opts = {'output': output_table, 'on_success_matcher': all_of(*pipeline_verifiers)} # Register cleanup before pipeline execution. # Note that actual execution happens in reverse order. self.addCleanup(utils.delete_bq_table, project, dataset, table) # Get pipeline options from command argument: --test-pipeline-options, # and start pipeline job by calling pipeline main function. bigquery_tornadoes.run( test_pipeline.get_full_options_as_args(**extra_opts))