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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/05/05 09:56:00 UTC
[jira] [Assigned] (SPARK-27635) Prevent from splitting too many
partitions smaller than row group size in Parquet file format
[ https://issues.apache.org/jira/browse/SPARK-27635?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-27635:
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Assignee: (was: Apache Spark)
> Prevent from splitting too many partitions smaller than row group size in Parquet file format
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-27635
> URL: https://issues.apache.org/jira/browse/SPARK-27635
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.2, 3.0.0
> Reporter: Lantao Jin
> Priority: Major
> Attachments: Screen Shot 2019-05-05 at 5.45.15 PM.png
>
>
> The scenario is submitting multiple jobs concurrently with spark dynamic allocation enabled. The issue happens in determining RDD partition numbers. When there are more available CPU cores, spark will try to split RDD to more pieces. But since the file is stored as parquet format, parquet's row group is actually the basic unit block to read data. Splitting RDD to too many small pieces doesn't make sense.
> Jobs will launch too many partitions and never complete.
> !Screen Shot 2019-05-05 at 5.45.15 PM.png!
> Set the default parallelism to a fixed number (for example 200) could workaround.
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