[ https://issues.apache.org/jira/browse/SPARK-22285?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Wenchen Fan reassigned SPARK-22285: ----------------------------------- Assignee: Zhenhua Wang > 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 > Assignee: Zhenhua Wang > Fix For: 2.3.0 > > > 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 generated methods also result in performance regression. -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org