[SPARK-3838][examples][mllib][python] Word2Vec example in python

docs/mllib-feature-extraction.md

@@ -162,6 +162,23 @@ for((synonym, cosineSimilarity) <- synonyms) {
 }
 {% endhighlight %}
 </div>
+<div data-lang="python">
+{% highlight python %}
+from pyspark import SparkContext
+from pyspark.mllib.feature import Word2Vec
+
+sc = SparkContext(appName='Word2Vec')
+inp = sc.textFile("text8_lines").map(lambda row: row.split(" "))
+
+word2vec = Word2Vec()
+model = word2vec.fit(inp)
+
+synonyms = model.findSynonyms('china', 40)
+
+for word, cosine_distance in synonyms:
+    print "{}: {}".format(word, cosine_distance)
+{% endhighlight %}
+</div>
 </div>
 
 ## StandardScaler

examples/src/main/python/mllib/word2vec.py

@@ -0,0 +1,50 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# This example uses text8 file from http://mattmahoney.net/dc/text8.zip
+# The file was downloadded, unziped and split into multiple lines using
+#
+# wget http://mattmahoney.net/dc/text8.zip
+# unzip text8.zip
+# grep -o -E '\w+(\W+\w+){0,15}' text8 > text8_lines
+# This was done so that the example can be run in local mode
+
+
+import sys
+
+from pyspark import SparkContext
+from pyspark.mllib.feature import Word2Vec
+
+USAGE = ("bin/spark-submit --driver-memory 4g "
+         "examples/src/main/python/mllib/word2vec.py text8_lines")
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print USAGE
+        sys.exit("Argument for file not provided")
+    file_path = sys.argv[1]
+    sc = SparkContext(appName='Word2Vec')
+    inp = sc.textFile(file_path).map(lambda row: row.split(" "))
+
+    word2vec = Word2Vec()
+    model = word2vec.fit(inp)
+
+    synonyms = model.findSynonyms('china', 40)
+
+    for word, cosine_distance in synonyms:
+        print "{}: {}".format(word, cosine_distance)
+    sc.stop()