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https://issues.apache.org/jira/browse/SPARK-12449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15080867#comment-15080867
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Stephan Kessler commented on SPARK-12449:
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Hi Yan,
this is only true for the {{DataSourceStrategy}} built in Spark currently
(there are some changes for 1.6 dealing with this issue, [SPARK-10978]). For
the proposed CatalystSourceStrategy this is not the case. We would just return
the RDD {{logicalPlanToRDD}} and no additional duplicated operations.
Best,
Stephan
> 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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