[jira] [Commented] (SPARK-24796) Support GROUPED_AGG_PANDAS_UDF in Pivot

["Xiao Li (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-24796?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16542338#comment-16542338 ] 

Xiao Li commented on SPARK-24796:
---------------------------------

cc [~icexelloss] [~bryanc] [~hyukjin.kwon]

> Support GROUPED_AGG_PANDAS_UDF in Pivot
> ---------------------------------------
>
>                 Key: SPARK-24796
>                 URL: https://issues.apache.org/jira/browse/SPARK-24796
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark, SQL
>    Affects Versions: 2.4.0
>            Reporter: Xiao Li
>            Priority: Major
>
> Currently, Grouped AGG PandasUDF is not supported in Pivot. It is nice to support it. 
> {code}
> # create input dataframe
> from pyspark.sql import Row
> data = [
>   Row(id=123, total=200.0, qty=3, name='item1'),
>   Row(id=124, total=1500.0, qty=1, name='item2'),
>   Row(id=125, total=203.5, qty=2, name='item3'),
>   Row(id=126, total=200.0, qty=500, name='item1'),
> ]
> df = spark.createDataFrame(data)
> from pyspark.sql.functions import pandas_udf, PandasUDFType
> @pandas_udf('double', PandasUDFType.GROUPED_AGG)
> def pandas_avg(v):
>    return v.mean()
> from pyspark.sql.functions import col, sum
>   
> applied_df = df.groupby('id').pivot('name').agg(pandas_avg('total').alias('mean'))
> applied_df.show()
> {code}



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