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https://issues.apache.org/jira/browse/SPARK-59901?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Peter Toth updated SPARK-59901:
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Fix Version/s: 4.2.2
> Storage-partitioned join fails with INTERNAL_ERROR when a one-side shuffle's
> join key references two columns
> ------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-59901
> URL: https://issues.apache.org/jira/browse/SPARK-59901
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 4.2.0, 4.1.3, 4.0.4
> Reporter: Peter Toth
> Assignee: Peter Toth
> Priority: Major
> Fix For: 4.3.0, 4.4.0, 4.2.2
>
>
> With {{spark.sql.sources.v2.bucketing.shuffle.enabled}} on, this fails at
> planning with an {{INTERNAL_ERROR}} from the {{assert(refs.size == 1)}} in
> {{KeyedShuffleSpec.keyPositions}}. {{b4(id)}} is partitioned by {{bucket(4,
> id)}}, and {{pbc(b, c)}} and {{qxy(x, y)}} are not partitioned:
> {code:sql}
> SELECT * FROM b4
> JOIN pbc p ON b4.id = p.b + p.c
> JOIN qxy q ON p.b = q.x AND p.c = q.y
> {code}
> The first join shuffles {{pbc}} onto {{bucket(4, b + c)}}, which
> {{KeyedShuffleSpec.createPartitioning}} builds from its join key. The second
> join builds a shuffle spec for that layout, and {{keyPositions}} asserts that
> each partition expression has exactly one reference. A bucketed third table
> fails the same way.
> Found while reviewing SPARK-59887. It fails on master and with SPARK-59887
> alike.
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