Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2041#discussion_r16443539
--- Diff: docs/mllib-stats.md ---
@@ -25,7 +25,79 @@ displayTitle: <a href="mllib-guide.html">MLlib</a> -
Statistics Functionality
\newcommand{\zero}{\mathbf{0}}
\]`
-## Data Generators
+## Random data generation
+
+Random data generation is useful for randomized algorithms, prototyping,
and performance testing.
+MLlib supports generating random RDDs with i.i.d. values drawn from a
given distribution:
+uniform, standard normal, or Poisson.
+
+<div class="codetabs">
+<div data-lang="scala" markdown="1">
+[`RandomRDDs`](api/scala/index.html#org.apache.spark.mllib.random.RandomRDDs)
provides factory
+methods to generate random double RDDs or vector RDDs.
--- End diff --
I marked `RandomDataGenerator` as a developer API and didn't mention it in
the guide.
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