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Posted to issues@spark.apache.org by "Bram van den Akker (Jira)" <ji...@apache.org> on 2020/10/03 13:34:00 UTC
[jira] [Commented] (SPARK-33060) approxSimilarityJoin in Structured
Stream causes state to explode in size
[ https://issues.apache.org/jira/browse/SPARK-33060?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17206693#comment-17206693 ]
Bram van den Akker commented on SPARK-33060:
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!Screenshot 2020-10-01 at 16.03.26.png!
> approxSimilarityJoin in Structured Stream causes state to explode in size
> -------------------------------------------------------------------------
>
> Key: SPARK-33060
> URL: https://issues.apache.org/jira/browse/SPARK-33060
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark, Structured Streaming
> Affects Versions: 3.0.0
> Reporter: Bram van den Akker
> Priority: Major
> Attachments: Screenshot 2020-10-01 at 16.03.26.png
>
>
> I'm writing a PySpark application that joins a static and streaming dataframe together using the approxSimilarityJoin function from the ML package. Because of the high volume of data, we need to apply a watermark to make sure a minimal amount of state is preserved. However, the [approxSimilarityJoin scala code contains a `distinct` action|https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/LSH.scala#L289] right after it joins the two datasets together. This call results in a state being created to account for late arriving data.
> Watermarks created in the PySpark code are being ignored and still lead to the state accumulating in size.
> My expectation is that the watermarking is lost in between the communication from Python to Scala.
> I've created [this Stackoverflow question|https://stackoverflow.com/questions/64157104/stream-static-join-without-aggregation-still-results-in-accumulating-spark-state] earlier this week, but after more investigation this really seem like a bug rather than a user error.
>
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