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Ryan Blue commented on SPARK-17995: ----------------------------------- [~cloud_fan] and [~yhuai], I'd like to help fix this, but I'm not sure the best way. I started to write an analyzer rule that uses transformUp on the initial logical plan, before unresovled aliases are resolved. That rule would find outer joins and generate a map of attributes to replace to the new attribute above the join, with the schema updated to be nullable and with a new exprId. The attributes to replace come from the output of the outer join. Where I ran into trouble was in replacing the attributes in the logical plan above the a join. I don't think it is a good idea to have cases in the rule for every possible plan, so I think we need a method to substitute attributes that is implemented by nodes in the plan. That sounds like a larger patch than I originally thought, so I wanted to make sure I'm going down the right path before I put up a PR for it. What do you think? > Use new attributes for columns from outer joins > ----------------------------------------------- > > Key: SPARK-17995 > URL: https://issues.apache.org/jira/browse/SPARK-17995 > Project: Spark > Issue Type: Improvement > Components: SQL > Affects Versions: 1.6.2, 2.0.0, 2.1.0 > Reporter: Ryan Blue > > Plans involving outer joins use the same attribute reference (by exprId) to > reference columns above the join and below the join. This is a false > equivalence that leads to bugs like SPARK-16181, in which an attributes were > incorrectly replaced by the optimizer. The column has a different schema > above the outer join because its values may be null. The fix for that issue, > [PR #13884](https://github.com/apache/spark/pull/13884) has a TODO comment > from [~cloud_fan] to fix this by using different attributes instead of > needing to special-case outer joins in rules and this issue is to track that > improvement. -- 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