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Yan commented on SPARK-12449: ----------------------------- Conceivably, if only logical plan is used, the Spark SQL execution would probably redo the already-pushed-down partial op, which would amount to a no-op. It might work but just not be super efficient. > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org