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https://issues.apache.org/jira/browse/SPARK-19842?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16397809#comment-16397809
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Wenchen Fan commented on SPARK-19842:
-------------------------------------

can we put the design doc to google doc so that other people can comment and 
discuss?

> Informational Referential Integrity Constraints Support in Spark
> ----------------------------------------------------------------
>
>                 Key: SPARK-19842
>                 URL: https://issues.apache.org/jira/browse/SPARK-19842
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.2.0
>            Reporter: Ioana Delaney
>            Priority: Major
>         Attachments: InformationalRIConstraints.doc
>
>
> *Informational Referential Integrity Constraints Support in Spark*
> This work proposes support for _informational primary key_ and _foreign key 
> (referential integrity) constraints_ in Spark. The main purpose is to open up 
> an area of query optimization techniques that rely on referential integrity 
> constraints semantics. 
> An _informational_ or _statistical constraint_ is a constraint such as a 
> _unique_, _primary key_, _foreign key_, or _check constraint_, that can be 
> used by Spark to improve query performance. Informational constraints are not 
> enforced by the Spark SQL engine; rather, they are used by Catalyst to 
> optimize the query processing. They provide semantics information that allows 
> Catalyst to rewrite queries to eliminate joins, push down aggregates, remove 
> unnecessary Distinct operations, and perform a number of other optimizations. 
> Informational constraints are primarily targeted to applications that load 
> and analyze data that originated from a data warehouse. For such 
> applications, the conditions for a given constraint are known to be true, so 
> the constraint does not need to be enforced during data load operations. 
> The attached document covers constraint definition, metastore storage, 
> constraint validation, and maintenance. The document shows many examples of 
> query performance improvements that utilize referential integrity constraints 
> and can be implemented in Spark.
> Link to the google doc: 
> [InformationalRIConstraints|https://docs.google.com/document/d/17r-cOqbKF7Px0xb9L7krKg2-RQB_gD2pxOmklm-ehsw/edit]



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