[SPARK-6615][MLLIB] Python API for Word2Vec

This is the sub-task of SPARK-6254.
Wrap missing method for `Word2Vec` and `Word2VecModel`.

Author: lewuathe <lewuathe@me.com>

Closes #5296 from Lewuathe/SPARK-6615 and squashes the following commits:

f14c304 [lewuathe] Reorder tests
1d326b9 [lewuathe] Merge master
e2bedfb [lewuathe] Modify test cases
afb866d [lewuathe] [SPARK-6615] Python API for Word2Vec

1 files changed, 40 insertions, 5 deletions

diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 6e9c68ec8a..dd3b66ce67 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -42,6 +42,7 @@ from pyspark.mllib.linalg import Vector, SparseVector, DenseVector, VectorUDT, _
 from pyspark.mllib.regression import LabeledPoint
 from pyspark.mllib.random import RandomRDDs
 from pyspark.mllib.stat import Statistics
+from pyspark.mllib.feature import Word2Vec
 from pyspark.mllib.feature import IDF
 from pyspark.serializers import PickleSerializer
 from pyspark.sql import SQLContext
@@ -630,6 +631,12 @@ class ChiSqTestTests(PySparkTestCase):
         self.assertIsNotNone(chi[1000])
 
 
+class SerDeTest(PySparkTestCase):
+    def test_to_java_object_rdd(self):  # SPARK-6660
+        data = RandomRDDs.uniformRDD(self.sc, 10, 5, seed=0L)
+        self.assertEqual(_to_java_object_rdd(data).count(), 10)
+
+
 class FeatureTest(PySparkTestCase):
     def test_idf_model(self):
         data = [
@@ -643,11 +650,39 @@ class FeatureTest(PySparkTestCase):
         self.assertEqual(len(idf), 11)
 
 
-class SerDeTest(PySparkTestCase):
-    def test_to_java_object_rdd(self):  # SPARK-6660
-        data = RandomRDDs.uniformRDD(self.sc, 10, 5, seed=0L)
-        self.assertEqual(_to_java_object_rdd(data).count(), 10)
-
+class Word2VecTests(PySparkTestCase):
+    def test_word2vec_setters(self):
+        data = [
+            ["I", "have", "a", "pen"],
+            ["I", "like", "soccer", "very", "much"],
+            ["I", "live", "in", "Tokyo"]
+        ]
+        model = Word2Vec() \
+            .setVectorSize(2) \
+            .setLearningRate(0.01) \
+            .setNumPartitions(2) \
+            .setNumIterations(10) \
+            .setSeed(1024) \
+            .setMinCount(3)
+        self.assertEquals(model.vectorSize, 2)
+        self.assertTrue(model.learningRate < 0.02)
+        self.assertEquals(model.numPartitions, 2)
+        self.assertEquals(model.numIterations, 10)
+        self.assertEquals(model.seed, 1024)
+        self.assertEquals(model.minCount, 3)
+
+    def test_word2vec_get_vectors(self):
+        data = [
+            ["a", "b", "c", "d", "e", "f", "g"],
+            ["a", "b", "c", "d", "e", "f"],
+            ["a", "b", "c", "d", "e"],
+            ["a", "b", "c", "d"],
+            ["a", "b", "c"],
+            ["a", "b"],
+            ["a"]
+        ]
+        model = Word2Vec().fit(self.sc.parallelize(data))
+        self.assertEquals(len(model.getVectors()), 3)
 
 if __name__ == "__main__":
     if not _have_scipy: