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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/02/02 23:27:51 UTC
[jira] [Assigned] (SPARK-19348) pyspark.ml.Pipeline gets corrupted
under multi threaded use
[ https://issues.apache.org/jira/browse/SPARK-19348?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-19348:
------------------------------------
Assignee: (was: Apache Spark)
> 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
> Reporter: Vinayak Joshi
> 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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