[jira] [Updated] (BEAM-112) Using non-IntervalWindows seems to fail

["Amit Sela (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-112?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Amit Sela updated BEAM-112:
---------------------------
    Attachment: test_stocks.csv

example input file

> Using non-IntervalWindows seems to fail
> ---------------------------------------
>
>                 Key: BEAM-112
>                 URL: https://issues.apache.org/jira/browse/BEAM-112
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Ben Chambers
>            Assignee: Amit Sela
>            Priority: Minor
>         Attachments: test_stocks.csv
>
>
> See here for more details: http://stackoverflow.com/questions/35993777/globalwindow-cannot-be-cast-to-intervalwindow
> The linked stack trace indicates this is using the Spark Runner:
> {noformat:title=Exception}
> java.lang.ClassCastException: com.google.cloud.dataflow.sdk.transforms.windowing.GlobalWindow cannot be cast to com.google.cloud.dataflow.sdk.transforms.windowing.IntervalWindow
>     at com.google.cloud.dataflow.sdk.transforms.windowing.IntervalWindow$IntervalWindowCoder.encode(IntervalWindow.java:171)
>     at com.google.cloud.dataflow.sdk.coders.IterableLikeCoder.encode(IterableLikeCoder.java:113)
>     at com.google.cloud.dataflow.sdk.coders.IterableLikeCoder.encode(IterableLikeCoder.java:59)
>     at com.google.cloud.dataflow.sdk.util.WindowedValue$FullWindowedValueCoder.encode(WindowedValue.java:599)
>     at com.google.cloud.dataflow.sdk.util.WindowedValue$FullWindowedValueCoder.encode(WindowedValue.java:540)
>     at com.cloudera.dataflow.spark.CoderHelpers.toByteArray(CoderHelpers.java:48)
>     at com.cloudera.dataflow.spark.CoderHelpers$3.call(CoderHelpers.java:134)
>     at com.cloudera.dataflow.spark.CoderHelpers$3.call(CoderHelpers.java:131)
>     at org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:1018)
>     at org.apache.spark.api.java.JavaPairRDD$$anonfun$pairFunToScalaFun$1.apply(JavaPairRDD.scala:1018)
>     at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>     at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
>     at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
>     at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>     at org.apache.spark.scheduler.Task.run(Task.scala:89)
>     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>     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)
> {noformat}
> It seems likely that at some point the Spark runner is assuming that all windows are IntervalWindows, which may not be true. Specifically the GlobalWindow+Triggers is valid, as is any custom implementation of BoundedWindow.



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