[jira] [Updated] (SPARK-19255) SQL Listener is causing out of memory, in case of data size is in petabytes.

["Ashok Kumar (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-19255?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Ashok Kumar updated SPARK-19255:
--------------------------------
    Summary: SQL Listener is causing out of memory, in case of  data size is in petabytes.  (was: SQL Listener is causing out of memory, in case of large no of shuffle partition)

> SQL Listener is causing out of memory, in case of  data size is in petabytes.
> -----------------------------------------------------------------------------
>
>                 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
>         Attachments: spark_sqllistener_oom.png
>
>
> 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



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org