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Hyukjin Kwon commented on SPARK-25599: -------------------------------------- Are you proposong UDAF for Python side? Then it might be a duplicate of SPARK-10915 > Stateful aggregation in PySpark > ------------------------------- > > Key: SPARK-25599 > URL: https://issues.apache.org/jira/browse/SPARK-25599 > Project: Spark > Issue Type: New Feature > Components: PySpark > Affects Versions: 2.3.0 > Reporter: Vincent Grosbois > Priority: Minor > > Hi! > > From PySpark, I am trying to define a custom aggregator *that is accumulating > state*. Is it possible in Spark 2.3 ? > AFAIK, it is now possible to define a custom UDAF in PySpark since Spark 2.3 > (cf [How to define and use a User-Defined Aggregate Function in Spark > SQL?|https://stackoverflow.com/questions/32100973/how-to-define-and-use-a-user-defined-aggregate-function-in-spark-sql]), > by calling {{pandas_udf}} with the {{PandasUDFType.GROUPED_AGG}} keyword. > However given that it is just taking a function as a parameter I don't think > it is possible to carry state around during the aggregation with this > function. > From Scala, I see it is possible to have stateful aggregation by either > extending {{UserDefinedAggregateFunction}} or > {{org.apache.spark.sql.expressions.Aggregator}} , but is there a similar > thing I can do on python-side only? > If no, is this planned in a future release? > thanks! -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org