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https://issues.apache.org/jira/browse/SPARK-12449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15070062#comment-15070062
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Santiago M. Mola commented on SPARK-12449:
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The physical plan would not be consumed by data sources, only the logical plan. 

An alternative approach would be to use a different representation to pass the 
logical plan to the data source. If the relational algebra from Apache Calcite 
is stable enough, it could be used as the logical plan representation for this 
interface. 

> Pushing down arbitrary logical plans to data sources
> ----------------------------------------------------
>
>                 Key: SPARK-12449
>                 URL: https://issues.apache.org/jira/browse/SPARK-12449
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>            Reporter: Stephan Kessler
>         Attachments: pushingDownLogicalPlans.pdf
>
>
> With the help of the DataSource API we can pull data from external sources 
> for processing. Implementing interfaces such as {{PrunedFilteredScan}} allows 
> to push down filters and projects pruning unnecessary fields and rows 
> directly in the data source.
> However, data sources such as SQL Engines are capable of doing even more 
> preprocessing, e.g., evaluating aggregates. This is beneficial because it 
> would reduce the amount of data transferred from the source to Spark. The 
> existing interfaces do not allow such kind of processing in the source.
> We would propose to add a new interface {{CatalystSource}} that allows to 
> defer the processing of arbitrary logical plans to the data source. We have 
> already shown the details at the Spark Summit 2015 Europe 
> [https://spark-summit.org/eu-2015/events/the-pushdown-of-everything/]
> I will add a design document explaining details. 



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