[SPARK-16348][ML][MLLIB][PYTHON] Use full classpaths for pyspark ML JVM calls

## What changes were proposed in this pull request?

Issue: Omitting the full classpath can cause problems when calling JVM methods or classes from pyspark.

This PR: Changed all uses of jvm.X in pyspark.ml and pyspark.mllib to use full classpath for X

## How was this patch tested?

Existing unit tests.  Manual testing in an environment where this was an issue.

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #14023 from jkbradley/SPARK-16348.

2 files changed, 9 insertions, 9 deletions

diff --git a/python/pyspark/ml/common.py b/python/pyspark/ml/common.py
index 256e91e141..7d449aaccb 100644
--- a/python/pyspark/ml/common.py
+++ b/python/pyspark/ml/common.py
@@ -63,7 +63,7 @@ def _to_java_object_rdd(rdd):
     RDD is serialized in batch or not.
     """
     rdd = rdd._reserialize(AutoBatchedSerializer(PickleSerializer()))
-    return rdd.ctx._jvm.MLSerDe.pythonToJava(rdd._jrdd, True)
+    return rdd.ctx._jvm.org.apache.spark.ml.python.MLSerDe.pythonToJava(rdd._jrdd, True)
 
 
 def _py2java(sc, obj):
@@ -82,7 +82,7 @@ def _py2java(sc, obj):
         pass
     else:
         data = bytearray(PickleSerializer().dumps(obj))
-        obj = sc._jvm.MLSerDe.loads(data)
+        obj = sc._jvm.org.apache.spark.ml.python.MLSerDe.loads(data)
     return obj
 
 
@@ -95,17 +95,17 @@ def _java2py(sc, r, encoding="bytes"):
             clsName = 'JavaRDD'
 
         if clsName == 'JavaRDD':
-            jrdd = sc._jvm.MLSerDe.javaToPython(r)
+            jrdd = sc._jvm.org.apache.spark.ml.python.MLSerDe.javaToPython(r)
             return RDD(jrdd, sc)
 
         if clsName == 'Dataset':
             return DataFrame(r, SQLContext.getOrCreate(sc))
 
         if clsName in _picklable_classes:
-            r = sc._jvm.MLSerDe.dumps(r)
+            r = sc._jvm.org.apache.spark.ml.python.MLSerDe.dumps(r)
         elif isinstance(r, (JavaArray, JavaList)):
             try:
-                r = sc._jvm.MLSerDe.dumps(r)
+                r = sc._jvm.org.apache.spark.ml.python.MLSerDe.dumps(r)
             except Py4JJavaError:
                 pass  # not pickable
 
diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index 981ed9dda0..24efce812b 100755
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -1195,12 +1195,12 @@ class VectorTests(MLlibTestCase):
 
     def _test_serialize(self, v):
         self.assertEqual(v, ser.loads(ser.dumps(v)))
-        jvec = self.sc._jvm.MLSerDe.loads(bytearray(ser.dumps(v)))
-        nv = ser.loads(bytes(self.sc._jvm.MLSerDe.dumps(jvec)))
+        jvec = self.sc._jvm.org.apache.spark.ml.python.MLSerDe.loads(bytearray(ser.dumps(v)))
+        nv = ser.loads(bytes(self.sc._jvm.org.apache.spark.ml.python.MLSerDe.dumps(jvec)))
         self.assertEqual(v, nv)
         vs = [v] * 100
-        jvecs = self.sc._jvm.MLSerDe.loads(bytearray(ser.dumps(vs)))
-        nvs = ser.loads(bytes(self.sc._jvm.MLSerDe.dumps(jvecs)))
+        jvecs = self.sc._jvm.org.apache.spark.ml.python.MLSerDe.loads(bytearray(ser.dumps(vs)))
+        nvs = ser.loads(bytes(self.sc._jvm.org.apache.spark.ml.python.MLSerDe.dumps(jvecs)))
         self.assertEqual(vs, nvs)
 
     def test_serialize(self):