[jira] [Created] (SPARK-22285) Change implementation of ApproxCountDistinctForIntervals to TypedImperativeAggregate

["Zhenhua Wang (JIRA)" <ji...@apache.org>]

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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