[jira] [Commented] (SPARK-12957) Derive and propagate data constrains in logical plan

["Sunitha Kambhampati (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-12957?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15183831#comment-15183831 ] 

Sunitha Kambhampati commented on SPARK-12957:
---------------------------------------------

Hi Sameer, Michael, 

Can you share this design doc if possible. I was not able to access from this location. 
https://docs.google.com/a/databricks.com/document/d/1WQRgDurUBV9Y6CWOBS75PQIqJwT-6WftVa18xzm7nCo/edit?usp=sharing

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
>
> 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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