[jira] [Closed] (BEAM-7599) Python SDK: IntervalWindow cannot be cast to GlobalWindow on Cloud Dataflow Runner

["John Patoch (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-7599?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

John Patoch closed BEAM-7599.
-----------------------------
    Fix Version/s: Not applicable
       Resolution: Abandoned

> Python SDK: IntervalWindow cannot be cast to GlobalWindow on Cloud Dataflow Runner
> ----------------------------------------------------------------------------------
>
>                 Key: BEAM-7599
>                 URL: https://issues.apache.org/jira/browse/BEAM-7599
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-dataflow
>    Affects Versions: 2.13.0
>            Reporter: John Patoch
>            Priority: Minor
>             Fix For: Not applicable
>
>
> Getting an error after deploying a pipeline built with the Python SDK on the Cloud Dataflow Runner.
>  
> -> The pipeline run seamlessly on the local DirectRunner.
> {code:java|title=Stackdriver Trace|borderStyle=solid}
> java.lang.ClassCastException: org.apache.beam.sdk.transforms.windowing.IntervalWindow cannot be cast to org.apache.beam.sdk.transforms.windowing.GlobalWindow at org.apache.beam.sdk.transforms.windowing.GlobalWindow$Coder.encode(GlobalWindow.java:59) at org.apache.beam.sdk.coders.Coder.encode(Coder.java:136) at org.apache.beam.sdk.util.CoderUtils.encodeToSafeStream(CoderUtils.java:82) at org.apache.beam.sdk.util.CoderUtils.encodeToByteArray(CoderUtils.java:66) at org.apache.beam.sdk.util.CoderUtils.encodeToByteArray(CoderUtils.java:51) at org.apache.beam.sdk.util.CoderUtils.encodeToBase64(CoderUtils.java:151) at org.apache.beam.runners.core.StateNamespaces$WindowNamespace.appendTo(StateNamespaces.java:117) at org.apache.beam.runners.dataflow.worker.WindmillStateInternals.encodeKey(WindmillStateInternals.java:256) at org.apache.beam.runners.dataflow.worker.WindmillStateInternals$WindmillValue.<init>(WindmillStateInternals.java:359) at org.apache.beam.runners.dataflow.worker.WindmillStateInternals$WindmillValue.<init>(WindmillStateInternals.java:337) at org.apache.beam.runners.dataflow.worker.WindmillStateInternals$CachingStateTable$1.bindValue(WindmillStateInternals.java:174) at org.apache.beam.runners.core.StateTags$2.bindValue(StateTags.java:69) at org.apache.beam.sdk.state.StateSpecs$ValueStateSpec.bind(StateSpecs.java:276) at org.apache.beam.sdk.state.StateSpecs$ValueStateSpec.bind(StateSpecs.java:266) at org.apache.beam.runners.core.StateTags$SimpleStateTag.bind(StateTags.java:296) at org.apache.beam.runners.core.StateTable.get(StateTable.java:60) at org.apache.beam.runners.dataflow.worker.WindmillStateInternals.state(WindmillStateInternals.java:334) at org.apache.beam.runners.core.ReduceFnContextFactory$StateAccessorImpl.access(ReduceFnContextFactory.java:207) at org.apache.beam.runners.core.triggers.TriggerStateMachineRunner.isClosed(TriggerStateMachineRunner.java:99) at org.apache.beam.runners.core.ReduceFnRunner.windowsThatAreOpen(ReduceFnRunner.java:275) at org.apache.beam.runners.core.ReduceFnRunner.processElements(ReduceFnRunner.java:345) at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowViaWindowSetFn.processElement(StreamingGroupAlsoByWindowViaWindowSetFn.java:94) at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowViaWindowSetFn.processElement(StreamingGroupAlsoByWindowViaWindowSetFn.java:42) at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.invokeProcessElement(GroupAlsoByWindowFnRunner.java:115) at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.processElement(GroupAlsoByWindowFnRunner.java:73) at org.apache.beam.runners.core.LateDataDroppingDoFnRunner.processElement(LateDataDroppingDoFnRunner.java:80) at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowsParDoFn.processElement(GroupAlsoByWindowsParDoFn.java:134) at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:44) at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:49) at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.runReadLoop(ReadOperation.java:201) at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.start(ReadOperation.java:159) at org.apache.beam.runners.dataflow.worker.util.common.worker.MapTaskExecutor.execute(MapTaskExecutor.java:77) at org.apache.beam.runners.dataflow.worker.fn.control.BeamFnMapTaskExecutor.execute(BeamFnMapTaskExecutor.java:125) at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.process(StreamingDataflowWorker.java:1283) at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.access$1000(StreamingDataflowWorker.java:147) at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker$6.run(StreamingDataflowWorker.java:1020) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745){code}
>  
> {{Pipeline can be found here: [https://github.com/angulartist/hashtagsbattle/blob/master/pipelines/hashtagsbattle/tpl.py]}}



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