Enrico Minack created SPARK-40601:
-------------------------------------
Summary: Improve error when cogrouping groups with mismatching key
sizes
Key: SPARK-40601
URL: https://issues.apache.org/jira/browse/SPARK-40601
Project: Spark
Issue Type: Improvement
Components: PySpark, SQL
Affects Versions: 3.4.0
Reporter: Enrico Minack
Cogrouping two grouped DataFrames in PySpark that have different group key
cardinalities raises an error that is not very descriptive:
{code:python}
left.groupby("id", "k")
.cogroup(right.groupby("id"))
{code}
{code:java}
Traceback (most recent call last):
py4j.protocol.Py4JJavaError: An error occurred while calling
o726.collectToPython.
: java.lang.IndexOutOfBoundsException: 1
at
scala.collection.mutable.ResizableArray.apply(ResizableArray.scala:46)
at
scala.collection.mutable.ResizableArray.apply$(ResizableArray.scala:45)
at scala.collection.mutable.ArrayBuffer.apply(ArrayBuffer.scala:49)
at
org.apache.spark.sql.catalyst.plans.physical.HashShuffleSpec.$anonfun$createPartitioning$5(partitioning.scala:650)
{code}
*Note:* This is Python-specific as cogrouping with differing group key sizes is
not possible in Scala. The respective Scala API is fully typed on the key.
The problem is that {{EnsureRequirements.ensureDistributionAndOrdering}} calls
into {{HashShuffleSpec.createPartitioning(clustering)}} where length of
{{clustering}} is smaller than largest bits ({{{}v.head{}}}) in
{{{}hashKeyPositions{}}} (EnsureRequirements.scala:159):
{code:java}
hashKeyPositions.map(v => clustering(v.head))
{code}
Possible fixes:
# Assert identical size for group keys, and provide meaningful
cogroup-specific error message.
# {{EnsureRequirements}} identifies this situation and provide a meaningful
distribution-requirements-specific error message.
# Ideally both.
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