From 22732e1eca730929345e440ba831386ee7446b74 Mon Sep 17 00:00:00 2001
From: MechCoder <manojkumarsivaraj334@gmail.com>
Date: Wed, 17 Jun 2015 22:08:38 -0700
Subject: [SPARK-7605] [MLLIB] [PYSPARK] Python API for ElementwiseProduct

Python API for org.apache.spark.mllib.feature.ElementwiseProduct

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #6346 from MechCoder/spark-7605 and squashes the following commits:

79d1ef5 [MechCoder] Consistent and support list / array types
5f81d81 [MechCoder] [SPARK-7605] [MLlib] Python API for ElementwiseProduct
---
 docs/mllib-feature-extraction.md | 22 ++++++++++++++++++++++
 1 file changed, 22 insertions(+)

(limited to 'docs/mllib-feature-extraction.md')

diff --git a/docs/mllib-feature-extraction.md b/docs/mllib-feature-extraction.md
index 4fe470a8de..1197dbbb8d 100644
--- a/docs/mllib-feature-extraction.md
+++ b/docs/mllib-feature-extraction.md
@@ -558,6 +558,28 @@ JavaRDD<Vector> transformedData2 = data.map(
   }
 );
 
+{% endhighlight %}
+</div>
+
+<div data-lang="python">
+{% highlight python %}
+from pyspark import SparkContext
+from pyspark.mllib.linalg import Vectors
+from pyspark.mllib.feature import ElementwiseProduct
+
+# Load and parse the data
+sc = SparkContext()
+data = sc.textFile("data/mllib/kmeans_data.txt")
+parsedData = data.map(lambda x: [float(t) for t in x.split(" ")])
+
+# Create weight vector.
+transformingVector = Vectors.dense([0.0, 1.0, 2.0])
+transformer = ElementwiseProduct(transformingVector)
+
+# Batch transform.
+transformedData = transformer.transform(parsedData)
+transformedData2 = transformer.transform(parsedData.first())
+
 {% endhighlight %}
 </div>
 </div>
-- 
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