[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.

1 files changed, 29 insertions, 0 deletions

diff --git a/python/pyspark/ml/wrapper.py b/python/pyspark/ml/wrapper.py
index 13b75e9919..80a0b31cd8 100644
--- a/python/pyspark/ml/wrapper.py
+++ b/python/pyspark/ml/wrapper.py
@@ -16,6 +16,9 @@
 #
 
 from abc import ABCMeta, abstractmethod
+import sys
+if sys.version >= '3':
+    xrange = range
 
 from pyspark import SparkContext
 from pyspark.sql import DataFrame
@@ -59,6 +62,32 @@ class JavaWrapper(object):
         java_args = [_py2java(sc, arg) for arg in args]
         return java_obj(*java_args)
 
+    @staticmethod
+    def _new_java_array(pylist, java_class):
+        """
+        Create a Java array of given java_class type. Useful for
+        calling a method with a Scala Array from Python with Py4J.
+
+        :param pylist:
+          Python list to convert to a Java Array.
+        :param java_class:
+          Java class to specify the type of Array. Should be in the
+          form of sc._gateway.jvm.* (sc is a valid Spark Context).
+        :return:
+          Java Array of converted pylist.
+
+        Example primitive Java classes:
+          - basestring -> sc._gateway.jvm.java.lang.String
+          - int -> sc._gateway.jvm.java.lang.Integer
+          - float -> sc._gateway.jvm.java.lang.Double
+          - bool -> sc._gateway.jvm.java.lang.Boolean
+        """
+        sc = SparkContext._active_spark_context
+        java_array = sc._gateway.new_array(java_class, len(pylist))
+        for i in xrange(len(pylist)):
+            java_array[i] = pylist[i]
+        return java_array
+
 
 @inherit_doc
 class JavaParams(JavaWrapper, Params):