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From "Joseph K. Bradley (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-19348) pyspark.ml.Pipeline gets corrupted under multi threaded use
Date Sat, 04 Mar 2017 00:45:46 GMT

     [ https://issues.apache.org/jira/browse/SPARK-19348?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Joseph K. Bradley updated SPARK-19348:
--------------------------------------
    Fix Version/s: 2.2.0

> 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: 2.2.0
>
>         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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