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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2015/01/16 09:43:34 UTC
[jira] [Commented] (SPARK-4867) UDF clean up
[ https://issues.apache.org/jira/browse/SPARK-4867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14279983#comment-14279983 ]
Reynold Xin commented on SPARK-4867:
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BTW if we plan to implement most SQL functions using this new UDF interface, than we should consider making mutable primitive types a first class citizen. Otherwise we will incur a huge performance hit when any functions on primitives are invoked.
> UDF clean up
> ------------
>
> Key: SPARK-4867
> URL: https://issues.apache.org/jira/browse/SPARK-4867
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Reporter: Michael Armbrust
> Priority: Blocker
>
> Right now our support and internal implementation of many functions has a few issues. Specifically:
> - UDFS don't know their input types and thus don't do type coercion.
> - We hard code a bunch of built in functions into the parser. This is bad because in SQL it creates new reserved words for things that aren't actually keywords. Also it means that for each function we need to add support to both SQLContext and HiveContext separately.
> For this JIRA I propose we do the following:
> - Change the interfaces for registerFunction and ScalaUdf to include types for the input arguments as well as the output type.
> - Add a rule to analysis that does type coercion for UDFs.
> - Add a parse rule for functions to SQLParser.
> - Rewrite all the UDFs that are currently hacked into the various parsers using this new functionality.
> Depending on how big this refactoring becomes we could split parts 1&2 from part 3 above.
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