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From "Reynold Xin (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-12957) Derive and propagate data constrains in logical plan
Date Wed, 26 Jul 2017 16:06:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-12957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Reynold Xin resolved SPARK-12957.
---------------------------------
       Resolution: Fixed
    Fix Version/s: 2.0.0

> 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
>             Fix For: 2.0.0
>
>         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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