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https://issues.apache.org/jira/browse/SPARK-24632?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-24632:
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Description:
This is a follow-up for [SPARK-17025], which allowed users to implement Python
PipelineStages in 3rd-party libraries, include them in Pipelines, and use
Pipeline persistence. This task is to make it easier for 3rd-party libraries
to have PipelineStages written in Java and then to use pyspark.ml abstractions
to create wrappers around those Java classes. This is currently possible,
except that users hit bugs around persistence.
Some fixes we'll need include:
* an overridable method for converting between Python and Java classpaths. See
https://github.com/apache/spark/blob/b56e9c613fb345472da3db1a567ee129621f6bf3/python/pyspark/ml/util.py#L284
*
https://github.com/apache/spark/blob/4e7d8678a3d9b12797d07f5497e0ed9e471428dd/python/pyspark/ml/pipeline.py#L378
One unusual thing for this task will be to write unit tests which test a custom
PipelineStage written outside of the pyspark package.
was:
This is a follow-up for [SPARK-17025], which allowed users to implement Python
PipelineStages in 3rd-party libraries, include them in Pipelines, and use
Pipeline persistence. This task is to make it easier for 3rd-party libraries
to have PipelineStages written in Java and then to use pyspark.ml abstractions
to create wrappers around those Java classes. This is currently possible,
except that users hit bugs around persistence.
One fix we'll need is an overridable method for converting between Python and
Java classpaths. See
https://github.com/apache/spark/blob/b56e9c613fb345472da3db1a567ee129621f6bf3/python/pyspark/ml/util.py#L284
One unusual thing for this task will be to write unit tests which test a custom
PipelineStage written outside of the pyspark package.
> Allow 3rd-party libraries to use pyspark.ml abstractions for Java wrappers
> for persistence
> ------------------------------------------------------------------------------------------
>
> Key: SPARK-24632
> URL: https://issues.apache.org/jira/browse/SPARK-24632
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 2.4.0
> Reporter: Joseph K. Bradley
> Priority: Major
>
> This is a follow-up for [SPARK-17025], which allowed users to implement
> Python PipelineStages in 3rd-party libraries, include them in Pipelines, and
> use Pipeline persistence. This task is to make it easier for 3rd-party
> libraries to have PipelineStages written in Java and then to use pyspark.ml
> abstractions to create wrappers around those Java classes. This is currently
> possible, except that users hit bugs around persistence.
> Some fixes we'll need include:
> * an overridable method for converting between Python and Java classpaths.
> See
> https://github.com/apache/spark/blob/b56e9c613fb345472da3db1a567ee129621f6bf3/python/pyspark/ml/util.py#L284
> *
> https://github.com/apache/spark/blob/4e7d8678a3d9b12797d07f5497e0ed9e471428dd/python/pyspark/ml/pipeline.py#L378
> One unusual thing for this task will be to write unit tests which test a
> custom PipelineStage written outside of the pyspark package.
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