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https://issues.apache.org/jira/browse/SPARK-12957?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15864796#comment-15864796
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Nick Dimiduk commented on SPARK-12957:
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I'm trying to understand the current state of SPARK-13219/SPARK-12532, which it
seems are deferring to this issue. I see all subtasks here have been fixedFor
in 2.0; is there further work to be done on this ticket? How does the sum of
this work relate back to the predicate pushdown join optimization described in
SPARK-13219. Basically, I'm trying to determine if I get this very useful
enhancement by upgrading to 2.x. 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.
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