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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2018/02/21 22:10:00 UTC
[jira] [Comment Edited] (SPARK-15526) Shade JPMML
[ https://issues.apache.org/jira/browse/SPARK-15526?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16372091#comment-16372091 ]
Joseph K. Bradley edited comment on SPARK-15526 at 2/21/18 10:09 PM:
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[~srowen] I just found that PMML is now listed as a dependency in a lot (all?) of the Spark modules: catalyst, mllib-local, etc. I haven't yet tested to see if these 2 PRs caused that change, but it seems likely.
Update: Maybe I built it incorrectly...I don't see this issue in the artifacts from RC4.
was (Author: josephkb):
[~srowen] I just found that PMML is now listed as a dependency in a lot (all?) of the Spark modules: catalyst, mllib-local, etc. I haven't yet tested to see if these 2 PRs caused that change, but it seems likely.
> 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
> Assignee: Sean Owen
> Priority: Minor
> Fix For: 2.3.0
>
> 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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