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https://issues.apache.org/jira/browse/SPARK-19255?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15825552#comment-15825552
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Takeshi Yamamuro commented on SPARK-19255:
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You mean not `_stageIdToStageMetrics ` but `taskIdToMetricUpdates` inside?
https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/ui/SQLListener.scala#L469
This is because IIUC `_stageIdToStageMetrics ` does not grow as #partitions
increases.
> SQL Listener is causing out of memory, in case of large no of shuffle
> partition
> -------------------------------------------------------------------------------
>
> Key: SPARK-19255
> URL: https://issues.apache.org/jira/browse/SPARK-19255
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Environment: Linux
> Reporter: Ashok Kumar
> Priority: Minor
>
> Test steps.
> 1.CREATE TABLE sample(imei string,age int,task bigint,num double,level
> decimal(10,3),productdate timestamp,name string,point int)USING
> com.databricks.spark.csv OPTIONS (path "data.csv", header "false",
> inferSchema "false");
> 2. set spark.sql.shuffle.partitions=100000;
> 3. select count(*) from (select task,sum(age) from sample group by task) t;
> After running above query, number of objects in map variable
> _stageIdToStageMetrics has increase to very high number , this increment is
> proportional to number of shuffle partition.
> Please have a look at attached screenshot
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