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From "Sameer Agarwal (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-12957) Derive and propagate data constrains in logical plan
Date Thu, 10 Mar 2016 07:45:41 GMT

    [ https://issues.apache.org/jira/browse/SPARK-12957?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15188856#comment-15188856
] 

Sameer Agarwal commented on SPARK-12957:
----------------------------------------

[~ksunitha] I've attached a copy of the design document to the JIRA: https://issues.apache.org/jira/secure/attachment/12792466/ConstraintPropagationinSparkSQL.pdf.
Thanks!

> 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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