[ https://issues.apache.org/jira/browse/SPARK-12336?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Davies Liu resolved SPARK-12336. -------------------------------- Resolution: Fixed Fix Version/s: 2.0.0 https://github.com/apache/spark/pull/10333 > Outer join using multiple columns results in wrong nullability > -------------------------------------------------------------- > > Key: SPARK-12336 > URL: https://issues.apache.org/jira/browse/SPARK-12336 > Project: Spark > Issue Type: Sub-task > Components: SQL > Affects Versions: 1.4.1, 1.5.2, 1.6.0, 2.0.0 > Reporter: Cheng Lian > Assignee: Davies Liu > Fix For: 2.0.0 > > > When joining two DataFrames using multiple columns, a temporary inner join is > used to compute join output. Then a real join operator is created and > projected. However, the final projection list is based on the inner join > rather than real join operator. When the real join operator is an outer join, > nullability of the final projection can be wrong, since outer join may alter > nullability of its child plan(s). -- 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