Github user yinxusen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11108#discussion_r55267567
--- Diff: docs/mllib-statistics.md ---
@@ -612,17 +327,17 @@ distribution `N(0, 1)`, and then map it to `N(1, 4)`.
Refer to the [`RandomRDDs` Python
docs](api/python/pyspark.mllib.html#pyspark.mllib.random.RandomRDDs) for more
details on the API.
-{% highlight python %}
-from pyspark.mllib.random import RandomRDDs
-
-sc = ... # SparkContext
-
-# Generate a random double RDD that contains 1 million i.i.d. values drawn
from the
-# standard normal distribution `N(0, 1)`, evenly distributed in 10
partitions.
-u = RandomRDDs.normalRDD(sc, 1000000L, 10)
-# Apply a transform to get a random double RDD following `N(1, 4)`.
-v = u.map(lambda x: 1.0 + 2.0 * x)
-{% endhighlight %}
+-{% highlight python %}
--- End diff --
ditto
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
