Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18584
@vanzin I took this example:
https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/mllib/PMMLModelExportExample.scala
which should exercise this code most directly, broke it out into a project and
compiled it vs Spark 2.1.1.
I then build Spark from this PR's branch, and ran the example locally with
`spark-submit`. It worked, but only if I set `SPARK_PREPEND_CLASSES=1`. Am I
right that this is to be expected, or the fact that it failed without this is a
problem? the failure otherwise was:
```
Exception in thread "main" java.lang.NoClassDefFoundError:
org/spark_project/dmg/pmml/Measure
at
org.apache.spark.mllib.pmml.export.PMMLModelExportFactory$.createPMMLModelExport(PMMLModelExportFactory.scala:38)
at
org.apache.spark.mllib.pmml.PMMLExportable$class.toPMML(PMMLExportable.scala:43)
at
org.apache.spark.mllib.pmml.PMMLExportable$class.toPMML(PMMLExportable.scala:78)
at
org.apache.spark.mllib.clustering.KMeansModel.toPMML(KMeansModel.scala:39)
at com.cloudera.datascience.jpmml.Test$.main(Test.scala:31)
...
```
That's not an error between the app and Spark API but saying that the Spark
code isn't finding the shaded JPMML that it is expecting to link against.
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