Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8227#discussion_r37255077
--- Diff: docs/mllib-clustering.md ---
@@ -564,6 +564,35 @@ public class JavaLDAExample {
{% endhighlight %}
</div>
+<div data-lang="python" markdown="1">
+{% highlight python %}
+from pyspark.mllib.clustering import LDA
+from pyspark.mllib.clustering import LDAModel
+from pyspark.mllib.linalg import Vectors
+
+# Load and parse the data
+data = sc.textFile("data/mllib/sample_lda_data.txt")
+parsedData = data.map(lambda line: Vectors.dense([float(x) for x in
line.strip().split(' ')]))
+# Index documents with unique IDs
+corpus = parsedData.zipWithIndex().map(lambda x: [x[1], x[0]]).cache()
+
+# Cluster the documents into three topics using LDA
+ldaModel = LDA.train(corpus, k=3)
+
+# Output topics. Each is a distribution over words (matching word count
vectors)
+print("Learned topics (as distributions over vocab of " +
str(ldaModel.vocabSize()) + " words):")
+topics = ldaModel.topicsMatrix()
+for topic in range(3):
+ print("Topic " + str(topic) + ":")
--- End diff --
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