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https://issues.apache.org/jira/browse/SPARK-4867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14252846#comment-14252846
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Michael Armbrust commented on SPARK-4867:
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One slightly hacky option that still keeps simplicity is to allow users to
register multiple functions with the same name but different input types. The
resolver can pick the closest function and only coerce when a matching function
is not available.
> UDF clean up
> ------------
>
> Key: SPARK-4867
> URL: https://issues.apache.org/jira/browse/SPARK-4867
> Project: Spark
> Issue Type: Bug
> 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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