[ https://issues.apache.org/jira/browse/SPARK-4644?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14228279#comment-14228279 ]
Lianhui Wang commented on SPARK-4644: ------------------------------------- hi @Shixiong Zhu, with skew data, can we use broadcast join to implement it. i think performance of broadcast join is very higher. at last we can merge result of broadcast join & common join. > Implement skewed join > --------------------- > > Key: SPARK-4644 > URL: https://issues.apache.org/jira/browse/SPARK-4644 > Project: Spark > Issue Type: Improvement > Components: Spark Core > Reporter: Shixiong Zhu > Attachments: Skewed Join Design Doc.pdf > > > Skewed data is not rare. For example, a book recommendation site may have > several books which are liked by most of the users. Running ALS on such > skewed data will raise a OutOfMemory error, if some book has too many users > which cannot be fit into memory. To solve it, we propose a skewed join > implementation. -- 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