[ https://issues.apache.org/jira/browse/SPARK-18804?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gopal Nagar reopened SPARK-18804: --------------------------------- Apologies for marking this JIRA as bug. This may not be a bug in Spark. But i wanted to get some input on How to make effective join ? Bcoz in my case, job fails despite having enough resources. > Join doesn't work in Spark on Bigger tables > ------------------------------------------- > > Key: SPARK-18804 > URL: https://issues.apache.org/jira/browse/SPARK-18804 > Project: Spark > Issue Type: Question > Components: Input/Output > Affects Versions: 1.6.1 > Reporter: Gopal Nagar > > Hi All, > Spark1.6.1 has been installed on a AWS EMR 3 node cluster which has 32 GB RAM > and 80 GB storage each node. I am trying to join two tables (1.2 GB & 900 MB > ) have rows 4607818 & 14273378 respectively. It's running in client mode on > Yarn cluster manager. > If i put the limit as 100 in select query it works fine. But if i try to join > on entire data set, Query runs for 3-4 hours and finally gets terminated. I > can see always 18 GB free on each nodes. > I have tried increasing no of executers/cores/partitions. But still doesn't > work. This has been tried in PySpark and submitted using Spark Submit command > but doesn't run. Please advise. > Join Query > -------------- > select * FROM table1 as t1 join table2 as t2 on t1.col = t2.col limit 100; -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org