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From "Santiago M. Mola (JIRA)" <>
Subject [jira] [Commented] (SPARK-12449) Pushing down arbitrary logical plans to data sources
Date Wed, 23 Dec 2015 19:15:46 GMT


Santiago M. Mola commented on SPARK-12449:

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:
>             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 []
> I will add a design document explaining details. 

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