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Nick Dimiduk commented on SPARK-12957: -------------------------------------- [~sameerag] thanks for the comment. From a naive scan of the tickets, I believe I am seeing the benefits of SPARK-13871 in that a {{IsNotNull}} constraint is applied from the names of the join columns. However, I don't see the boon of SPARK-13789, specifically the {{a = 5, a = b}} mentioned in the description. My query is a join between a very small relation (100's of rows) and a very large one (10's of billions). I've hinted the planner to broadcast the smaller table, which it honors. After SPARK-13789, I expected to see the join column values pushed down as well. This is not the case. Any tips on debugging this further? I've set breakpoints in the {{RelationProvider}} implementation and see that it's only receiving the {{IsNotNull}} filters, nothing further from the planner. Thanks a lot! > Derive and propagate data constrains in logical plan > ----------------------------------------------------- > > Key: SPARK-12957 > URL: https://issues.apache.org/jira/browse/SPARK-12957 > Project: Spark > Issue Type: New Feature > Components: SQL > Reporter: Yin Huai > Assignee: Sameer Agarwal > Attachments: ConstraintPropagationinSparkSQL.pdf > > > Based on the semantic of a query plan, we can derive data constrains (e.g. if > a filter defines {{a > 10}}, we know that the output data of this filter > satisfy the constrain of {{a > 10}} and {{a is not null}}). We should build a > framework to derive and propagate constrains in the logical plan, which can > help us to build more advanced optimizations. -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org