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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2021/10/27 01:03:00 UTC
[jira] [Assigned] (SPARK-37124) Support Writable
ArrowColumnarVector
[ https://issues.apache.org/jira/browse/SPARK-37124?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-37124:
------------------------------------
Assignee: (was: Apache Spark)
> Support Writable ArrowColumnarVector
> ------------------------------------
>
> Key: SPARK-37124
> URL: https://issues.apache.org/jira/browse/SPARK-37124
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 3.2.0
> Reporter: Chendi.Xue
> Priority: Major
>
> This Jira is aim to add Arrow format as an alternative for ColumnVector solution.
> Current ArrowColumnVector is not fully equivalent to OnHeap/OffHeapColumnVector in spark, and since Arrow API is now being more stable, and using pandas udf will perform much better than python udf.
> I am proposing to fully support arrow format as an alternative to ColumnVector just like the other two.
> What I did in this PR is to create a new class in the same package with OnHeap/OffHeapColumnVector and extend from WritableColumnVector to support all put APIs.
> UTs are covering all Data Format with testing on writing to columnVector and reading from columnVector. I also added 3 UTs for testing on loading from ArrowRecordBatch and allocateColumns .
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