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Kyle Weaver commented on BEAM-7219: ----------------------------------- For the test_metrics failure, I found that metrics are being passed to Python. The test breaks because no metrics match the filter [1], because the step names are transformed somehow such that the filter logic is too strict to recognize [2]: Spark Runner: MetricKey(step=ref_AppliedPTransform_count1_17, metric=MetricName(namespace=ns, name=counter), labels={}): 2 MetricKey(step=ref_AppliedPTransform_count2_18, metric=MetricName(namespace=ns, name=counter), labels={}): 4 ... Fn API Runner: MetricKey(step=count1, metric=MetricName(namespace=ns, name=counter), labels={}): 2, MetricKey(step=count2, metric=MetricName(namespace=ns, name=counter), labels={}): 4 Also, note that Flink has its own, completely different implementation of test_metrics [3]. [1] https://github.com/apache/beam/blob/2ef7b9db8af015dcba544b93df00a4e54cd8caf2/sdks/python/apache_beam/runners/portability/fn_api_runner/fn_runner_test.py#L744 [2] https://github.com/apache/beam/blob/2ef7b9db8af015dcba544b93df00a4e54cd8caf2/sdks/python/apache_beam/metrics/metric.py#L151-L155 [3] https://github.com/apache/beam/blob/2ef7b9db8af015dcba544b93df00a4e54cd8caf2/sdks/python/apache_beam/runners/portability/flink_runner_test.py#L251 > Spark portable runner: support Spark metrics > -------------------------------------------- > > Key: BEAM-7219 > URL: https://issues.apache.org/jira/browse/BEAM-7219 > Project: Beam > Issue Type: New Feature > Components: runner-spark > Reporter: Kyle Weaver > Assignee: Kyle Weaver > Priority: Major > Labels: portability-spark > > The Spark portable runner already updates and collects metrics from the SDK > harness, but it needs to send the collected metrics on to Spark itself, > similar to FlinkMetricContainer > ([https://github.com/apache/beam/blob/5c31efbae5fa40c024a47a44af3e6bc8a079cc2a/runners/flink/src/main/java/org/apache/beam/runners/flink/metrics/FlinkMetricContainer.java]). -- This message was sent by Atlassian Jira (v8.3.4#803005)