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author | Bryan Cutler <cutlerb@gmail.com> | 2017-01-31 15:42:36 -0800 |
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committer | Holden Karau <holden@us.ibm.com> | 2017-01-31 15:42:36 -0800 |
commit | 57d70d26c88819360cdc806e7124aa2cc1b9e4c5 (patch) | |
tree | 989a46211f9f6e7069dd77a41bf3f805716f863d /external/docker/README.md | |
parent | ce112cec4f9bff222aa256893f94c316662a2a7e (diff) | |
download | spark-57d70d26c88819360cdc806e7124aa2cc1b9e4c5.tar.gz spark-57d70d26c88819360cdc806e7124aa2cc1b9e4c5.tar.bz2 spark-57d70d26c88819360cdc806e7124aa2cc1b9e4c5.zip |
[SPARK-17161][PYSPARK][ML] Add PySpark-ML JavaWrapper convenience function to create Py4J JavaArrays
## What changes were proposed in this pull request?
Adding convenience function to Python `JavaWrapper` so that it is easy to create a Py4J JavaArray that is compatible with current class constructors that have a Scala `Array` as input so that it is not necessary to have a Java/Python friendly constructor. The function takes a Java class as input that is used by Py4J to create the Java array of the given class. As an example, `OneVsRest` has been updated to use this and the alternate constructor is removed.
## How was this patch tested?
Added unit tests for the new convenience function and updated `OneVsRest` doctests which use this to persist the model.
Author: Bryan Cutler <cutlerb@gmail.com>
Closes #14725 from BryanCutler/pyspark-new_java_array-CountVectorizer-SPARK-17161.
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