Zhenhua Wang created SPARK-22285:
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Summary: Change implementation of ApproxCountDistinctForIntervals
to TypedImperativeAggregate
Key: SPARK-22285
URL: https://issues.apache.org/jira/browse/SPARK-22285
Project: Spark
Issue Type: Sub-task
Components: SQL
Affects Versions: 2.3.0
Reporter: Zhenhua Wang
The current implementation of `ApproxCountDistinctForIntervals` is
`ImperativeAggregate`. The number of `aggBufferAttributes` is the number of
total words in the hllppHelper array. Each hllppHelper has 52 words by default
relativeSD.
Since this aggregate function is used in equi-height histogram generation, and
the number of buckets in histogram is usually hundreds, the number of
`aggBufferAttributes` can easily reach tens of thousands or even more.
This leads to a huge method in codegen and causes errors such as
`org.codehaus.janino.JaninoRuntimeException: Code of method
"apply(Lorg/apache/spark/sql/catalyst/InternalRow;)Lorg/apache/spark/sql/catalyst/expressions/UnsafeRow;"
of class
"org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection"
grows beyond 64 KB`.
Besides, huge methods also result in performance regression.
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