Various enhancements to the programming guide and HTML/CSS

1 files changed, 4 insertions, 4 deletions

diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 3c0e54671b..7cd46da940 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -3,16 +3,16 @@ layout: global
 title: Launching Spark on YARN
 ---
 
-Spark allows you to launch jobs on an existing [YARN](http://hadoop.apache.org/common/docs/r0.23.1/hadoop-yarn/hadoop-yarn-site/YARN.html) cluster. 
+Spark allows you to launch jobs on an existing [YARN](http://hadoop.apache.org/docs/r2.0.1-alpha/hadoop-yarn/hadoop-yarn-site/YARN.html) cluster. 
 
-## Preparations
+# Preparations
 
 - In order to distribute Spark within the cluster it must be packaged into a single JAR file. This can be done by running `sbt/sbt assembly`
 - Your application code must be packaged into a separate jar file.
 
 If you want to test out the YARN deployment mode, you can use the current spark examples. A `spark-examples_2.9.1-0.6.0-SNAPSHOT.jar` file can be generated by running `sbt/sbt package`.
 
-## Launching Spark on YARN
+# Launching Spark on YARN
 
 The command to launch the YARN Client is as follows:
 
@@ -36,7 +36,7 @@ For example:
 
 The above starts a YARN Client programs which periodically polls the Application Master for status updates and displays them in the console. The client will exit once your application has finished running.
 
-## Important Notes
+# Important Notes
 
 - When your application instantiates a Spark context it must use a special "standalone" master url. This starts the scheduler without forcing it to connect to a cluster. A good way to handle this is to pass "standalone" as an argument to your program, as shown in the example above.
 - YARN does not support requesting container resources based on the number of cores. Thus the numbers of cores given via command line arguments cannot be guaranteed.