[ https://issues.apache.org/jira/browse/SPARK-4019?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Patrick Wendell resolved SPARK-4019. ------------------------------------ Resolution: Fixed Fix Version/s: 1.2.0 Fixed by Josh's patch: https://github.com/apache/spark/pull/2866 > Shuffling with more than 2000 reducers may drop all data when partitons are > mostly empty or cause deserialization errors if at least one partition is > empty > ----------------------------------------------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-4019 > URL: https://issues.apache.org/jira/browse/SPARK-4019 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 1.2.0 > Reporter: Xiangrui Meng > Assignee: Josh Rosen > Priority: Blocker > Fix For: 1.2.0 > > > {code} > sc.makeRDD(0 until 10, 1000).repartition(2001).collect() > {code} > returns `Array()`. > 1.1.0 doesn't have this issue. Tried both HASH and SORT manager. > This problem can also manifest itself as Snappy deserialization errors if the > average map output status size is non-zero but there is at least one empty > partition, e.g. > sc.makeRDD(0 until 100000, 1000).repartition(2001).collect() -- 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