[jira] [Commented] (SPARK-39962) Global aggregation against pandas aggregate UDF does not take the column order into account

["Apache Spark (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-39962?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17574481#comment-17574481 ] 

Apache Spark commented on SPARK-39962:
--------------------------------------

User 'HyukjinKwon' has created a pull request for this issue:
https://github.com/apache/spark/pull/37390

> Global aggregation against pandas aggregate UDF does not take the column order into account
> -------------------------------------------------------------------------------------------
>
>                 Key: SPARK-39962
>                 URL: https://issues.apache.org/jira/browse/SPARK-39962
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 3.1.3, 3.3.0, 3.2.2, 3.4.0
>            Reporter: Hyukjin Kwon
>            Priority: Major
>
> {code}
> import pandas as pd 
> from pyspark.sql import functions as f 
> @f.pandas_udf("double") 
> def AVG(x: pd.Series) -> float: 
>     return x.mean() 
> abc = spark.createDataFrame([(1.0, 5.0, 17.0)], schema=["a", "b", "c"]) 
> abc.agg(AVG("a"), AVG("c")).show()
> abc.select("c", "a").agg(AVG("a"), AVG("c")).show()
> {code}
> {code}
> +------+------+
> |AVG(a)|AVG(c)|
> +------+------+
> |   1.0|  17.0|
> +------+------+
> +------+------+
> |AVG(a)|AVG(c)|
> +------+------+
> |  17.0|   1.0|
> +------+------+
> {code}
> Both have to be the same.



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