[jira] [Resolved] (SPARK-25601) Register Grouped aggregate UDF Vectorized UDFs for SQL Statement

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-25601?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-25601.
----------------------------------
       Resolution: Fixed
         Assignee: Hyukjin Kwon
    Fix Version/s: 3.0.0
                   2.4.0

Fixed in https://github.com/apache/spark/pull/22620

> Register Grouped aggregate UDF Vectorized UDFs for SQL Statement
> ----------------------------------------------------------------
>
>                 Key: SPARK-25601
>                 URL: https://issues.apache.org/jira/browse/SPARK-25601
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark, SQL
>    Affects Versions: 2.4.0
>            Reporter: Hyukjin Kwon
>            Assignee: Hyukjin Kwon
>            Priority: Major
>             Fix For: 2.4.0, 3.0.0
>
>
> Capable of registering grouped aggregate UDsF and then use it in SQL statement.
> For example,
> {code}
> from pyspark.sql.functions import pandas_udf, PandasUDFType
> @pandas_udf("integer", PandasUDFType.GROUPED_AGG)  # doctest: +SKIP
> def sum_udf(v):
>     return v.sum()
> spark.udf.register("sum_udf", sum_udf)  # doctest: +SKIP
> q = "SELECT sum_udf(v1) FROM VALUES (3, 0), (2, 0), (1, 1) tbl(v1, v2) GROUP BY v2"
> spark.sql(q).show()
> +-----------+
> |sum_udf(v1)|
> +-----------+
> |          1|
> |          5|
> +-----------+
> {code}



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