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https://issues.apache.org/jira/browse/SPARK-19348?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley resolved SPARK-19348.
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Resolution: Fixed
Fix Version/s: 2.0.3
2.1.1
Issue resolved by pull request 17195
[https://github.com/apache/spark/pull/17195]
> pyspark.ml.Pipeline gets corrupted under multi threaded use
> -----------------------------------------------------------
>
> Key: SPARK-19348
> URL: https://issues.apache.org/jira/browse/SPARK-19348
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark
> Affects Versions: 1.6.0, 2.0.0, 2.1.0, 2.2.0
> Reporter: Vinayak Joshi
> Assignee: Bryan Cutler
> Fix For: 2.1.1, 2.0.3, 2.2.0
>
> Attachments: pyspark_pipeline_threads.py
>
>
> When pyspark.ml.Pipeline objects are constructed concurrently in separate
> python threads, it is observed that the stages used to construct a pipeline
> object get corrupted i.e the stages supplied to a Pipeline object in one
> thread appear inside a different Pipeline object constructed in a different
> thread.
> Things work fine if construction of pyspark.ml.Pipeline objects is
> serialized, so this looks like a thread safety problem with
> pyspark.ml.Pipeline object construction.
> Confirmed that the problem exists with Spark 1.6.x as well as 2.x.
> While the corruption of the Pipeline stages is easily caught, we need to know
> if performing other pipeline operations, such as pyspark.ml.pipeline.fit( )
> are also affected by the underlying cause of this problem. That is, whether
> other pipeline operations like pyspark.ml.pipeline.fit( ) may be performed
> in separate threads (on distinct pipeline objects) concurrently without any
> cross contamination between them.
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