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https://issues.apache.org/jira/browse/SPARK-33303?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Peter Toth updated SPARK-33303:
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Description:
We run into an issue where a customer created a column with an expensive
PythonUDF call and build a very complex logic on the the top of that column as
new derived columns. Due to `CollapseProject` and `ExtractPythonUDFs` rules the
UDF is called ~1000 times for each row which degraded the performance of the
query significantly.
The `ExtractPythonUDFs` rule could deduplicate deterministic UDFs so as to
avoid performance degradation.
was:
We run into an issue where a customer created a column with an expensive UDF
call and build a very complex logic on the the top of that column as new
derived columns. Due to `CollapseProject` and `ExtractPythonUDFs` rules the UDF
is called ~1000 times for each row which degraded the performance of the query
significantly.
The `ExtractPythonUDFs` rule could deduplicate deterministic UDFs so as to
avoid performance degradation.
> Deduplicate deterministic PythonUDF calls
> -----------------------------------------
>
> Key: SPARK-33303
> URL: https://issues.apache.org/jira/browse/SPARK-33303
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Peter Toth
> Assignee: Apache Spark
> Priority: Major
>
> We run into an issue where a customer created a column with an expensive
> PythonUDF call and build a very complex logic on the the top of that column
> as new derived columns. Due to `CollapseProject` and `ExtractPythonUDFs`
> rules the UDF is called ~1000 times for each row which degraded the
> performance of the query significantly.
> The `ExtractPythonUDFs` rule could deduplicate deterministic UDFs so as to
> avoid performance degradation.
>
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