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https://issues.apache.org/jira/browse/IMPALA-9271?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tim Armstrong updated IMPALA-9271:
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Component/s: Frontend
Backend
> Provide UDF framework corresponding to Hive's GenericUDF
> --------------------------------------------------------
>
> Key: IMPALA-9271
> URL: https://issues.apache.org/jira/browse/IMPALA-9271
> Project: IMPALA
> Issue Type: New Feature
> Components: Backend, Frontend
> Reporter: Quanlong Huang
> Priority: Major
>
> Hive GenericUDF are superior to normal UDFs in the following ways:
> # It can accept arguments of complex types, and return complex types.
> # It can accept variable length of arguments.
> # It can accept an infinite number of function signature - for example, it's
> easy to write a GenericUDF that accepts array<int>, array<array<int>> and so
> on (arbitrary levels of nesting).
> # It can do short-circuit evaluations using DeferedObject. Arguments can in
> any types and it's allowed to do lazy-evaluation for them.
> The masking functions added for Ranger column masking are some important
> examples of GenericUDF. For instance, there're hundreds of ways to use
> {{mask_show_first_n}}:
> {code:java}
> mask_show_first_n(val)
> mask_show_first_n(val, 8)
> mask_show_first_n(val, 8, 'X', 'x', 'n')
> mask_show_first_n(val, 8, 'x', 'x', 'x', 'x', -1)
> mask_show_first_n(val, 8, 'x', -1, 'x', 'x', '9')
> ...{code}
> We have to implement hundreds of overloads for all possible combinations.
> Currently we don't support complex types in UDF arguments or return type, so
> we should at least provide a framework to support UDFs that:
> # It can accept variable length of arguments.
> # Arguments can in any types. Their actual values are extracted in the UDF
> (lazy-evaluation).
> For 2, maybe just adding a field in {{impala_udf::AnyVal}} reflecting the
> actual types is enough.
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