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Posted to issues@spark.apache.org by "Cody Koeninger (JIRA)" <ji...@apache.org> on 2018/03/16 17:34:00 UTC
[jira] [Resolved] (SPARK-18371) Spark Streaming backpressure bug -
generates a batch with large number of records
[ https://issues.apache.org/jira/browse/SPARK-18371?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Cody Koeninger resolved SPARK-18371.
------------------------------------
Resolution: Fixed
Fix Version/s: 2.4.0
> Spark Streaming backpressure bug - generates a batch with large number of records
> ---------------------------------------------------------------------------------
>
> Key: SPARK-18371
> URL: https://issues.apache.org/jira/browse/SPARK-18371
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 2.0.0
> Reporter: mapreduced
> Assignee: Sebastian Arzt
> Priority: Major
> Fix For: 2.4.0
>
> Attachments: 01.png, 02.png, GiantBatch2.png, GiantBatch3.png, Giant_batch_at_23_00.png, Look_at_batch_at_22_14.png
>
>
> When the streaming job is configured with backpressureEnabled=true, it generates a GIANT batch of records if the processing time + scheduled delay is (much) larger than batchDuration. This creates a backlog of records like no other and results in batches queueing for hours until it chews through this giant batch.
> Expectation is that it should reduce the number of records per batch in some time to whatever it can really process.
> Attaching some screen shots where it seems that this issue is quite easily reproducible.
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