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Posted to issues@spark.apache.org by "Villu Ruusmann (JIRA)" <ji...@apache.org> on 2017/07/01 20:37:02 UTC

[jira] [Commented] (SPARK-15526) Shade JPMML

    [ https://issues.apache.org/jira/browse/SPARK-15526?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16071392#comment-16071392 ] 

Villu Ruusmann commented on SPARK-15526:
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This issue is responsible for >95% of support requests around my JPMML-SparkML and JPMML-SparkML-Package projects.

I've given up teaching people how to use Apache Maven Shade plugin to work around it. For Apache Spark 2.0 and 2.1 users the "official fix" is to delete the two offending JAR files `$SPARK_HOME/jars/pmml-model-1.2.15.jar` and `$SPARK_HOME/jars/pmml-schema-1.2.15.jar`. Sure, it will break built-in MLlib PMML export functionality, but anyone who is interested in using their JPMML-SparkML replacements, shouldn't mind it.

> Shade JPMML
> -----------
>
>                 Key: SPARK-15526
>                 URL: https://issues.apache.org/jira/browse/SPARK-15526
>             Project: Spark
>          Issue Type: Dependency upgrade
>          Components: ML, MLlib
>    Affects Versions: 2.0.0
>            Reporter: Villu Ruusmann
>            Priority: Minor
>   Original Estimate: 2h
>  Remaining Estimate: 2h
>
> The Spark-MLlib module depends on the JPMML-Model library (org.jpmml:pmml-model:1.2.7) for its PMML export capabilities. The JPMML-Model library is included in the Apache Spark assembly, which makes it very difficult to build and deploy competing PMML exporters that may wish to depend on different versions (typically much newer) of the same library.
> JPMML-Model library classes are not part of Apache Spark public APIs, so it shouldn't be a problem if they are relocated by prepending a prefix "org.spark_project" to their package names using Maven Shade Plugin. The requested treatment is identical to how Google Guava and Jetty dependencies are shaded in the final assembly.
> This issue is raised in relation to the JPMML-SparkML project (https://github.com/jpmml/jpmml-sparkml), which provides PMML export capabilities for Spark ML Pipelines. Currently, application developers who wish to use it must tweak their application classpath, which assumes familiarity with build internals.



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