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Posted to issues@spark.apache.org by "Oscar Delicaat (Jira)" <ji...@apache.org> on 2022/10/06 13:38:00 UTC
[jira] [Commented] (SPARK-39763) Executor memory footprint substantially increases while reading zstd compressed parquet files
[ https://issues.apache.org/jira/browse/SPARK-39763?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17613536#comment-17613536 ]
Oscar Delicaat commented on SPARK-39763:
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Thanks for the work [~camper42]! This seems to have solved the issue for us.
> Executor memory footprint substantially increases while reading zstd compressed parquet files
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-39763
> URL: https://issues.apache.org/jira/browse/SPARK-39763
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.2.0
> Reporter: Yeachan Park
> Priority: Minor
>
> Hi all,
>
> While transitioning from the default snappy compression to zstd, we noticed a substantial increase in executor memory whilst *reading* and applying transformations on *zstd* compressed parquet files.
> Memory footprint increased increased 3 fold in some cases, compared to reading and applying the same transformations on a parquet file compressed with snappy.
> This behaviour only occurs when reading zstd compressed parquet files. Writing a zstd parquet file does not result in this behaviour.
> To reproduce:
> # Set "spark.sql.parquet.compression.codec" to zstd
> # Write some parquet files, the compression will default to zstd after setting the option above
> # Read the compressed zstd file and run some transformations. Compare the memory usage of the executor vs running the same transformation on a parquet file with snappy compression.
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