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https://issues.apache.org/jira/browse/SPARK-32494?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-32494:
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Assignee: Apache Spark
> Null Aware Anti Join Optimize Support Multi-Column
> --------------------------------------------------
>
> Key: SPARK-32494
> URL: https://issues.apache.org/jira/browse/SPARK-32494
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Leanken.Lin
> Assignee: Apache Spark
> Priority: Major
>
> In Issue SPARK-32290, we managed to optimize BroadcastNestedLoopJoin into
> BroadcastHashJoin within the Single-Column NAAJ scenario, by using hash
> lookup instead of loop join.
> It's simple to just fulfill a "NOT IN" logical when it's a single key, but
> multi-column not in is much more complicated with all these null aware
> comparison.
> FYI, code logical for single and multi column is defined at
> ~/sql/core/src/test/resources/sql-tests/inputs/subquery/in-subquery/not-in-unit-tests-single-column.sql
> ~/sql/core/src/test/resources/sql-tests/inputs/subquery/in-subquery/not-in-unit-tests-multi-column.sql
>
> Hence, proposed with a New type HashedRelation, NullAwareHashedRelation.
> For NullAwareHashedRelation
> # it will not skip anyNullColumn key like LongHashedRelation and
> UnsafeHashedRelation do.
> # while building NullAwareHashedRelation, will put extra keys into the
> relation, just to make null aware columns comparison in hash lookup style.
> the duplication would be 2^numKeys - 1 times, for example, if we are to
> support NAAJ with 3 column join key, the buildSide would be expanded into
> (2^3 - 1) times, 7X.
> For example, if there is a UnsafeRow key (1,2,3)
> In NullAware Mode, it should be expanded into 7 keys with extra C(3,1),
> C(3,2) combinations, within the combinations, we duplicated these record with
> null padding as following.
> Original record
> (1,2,3)
> Extra record to be appended into NullAwareHashedRelation
> (null, 2, 3) (1, null, 3) (1, 2, null)
> (null, null, 3) (null, 2, null) (1, null, null))
> with the expanded data we can extract a common pattern for both single and
> multi column. allNull refer to a unsafeRow which has all null columns.
> * buildSide is empty input => return all rows
> * allNullColumnKey Exists In buildSide input => reject all rows
> * if streamedSideRow.allNull is true => drop the row
> * if streamedSideRow.allNull is false & findMatch in NullAwareHashedRelation
> => drop the row
> * if streamedSideRow.allNull is false & notFindMatch in
> NullAwareHashedRelation => return the row
>
>
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