[jira] [Updated] (SPARK-44718) High On-heap memory usage is detected while doing parquet-file reading with Off-Heap memory mode enabled on spark

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-44718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

ASF GitHub Bot updated SPARK-44718:
-----------------------------------
    Labels: pull-request-available  (was: )

> High On-heap memory usage is detected while doing parquet-file reading with Off-Heap memory mode enabled on spark
> -----------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-44718
>                 URL: https://issues.apache.org/jira/browse/SPARK-44718
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core, SQL
>    Affects Versions: 3.4.1
>            Reporter: Zamil Majdy
>            Assignee: Zamil Majdy
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.0.0
>
>
> I see the high use of on-heap memory usage while doing the parquet file reading when the off-heap memory mode is enabled. This is caused by the memory-mode for the column vector for the vectorized reader is configured by different flag, and the default value is always set to On-Heap.
> Conf to reproduce the issue:
> {{spark.memory.offHeap.size 1000000}}
> {{spark.memory.offHeap.enabled true}}
> Enabling these configurations only will not change the memory mode used for parquet-reading by the vectorized reader to Off-Heap.
>  
> Proposed PR: https://github.com/apache/spark/pull/42394



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