diff --git a/docs/java-programming-guide.md b/docs/java-programming-guide.md
index 2411e078494f5363c0fce2de28bcc452982ae86d..4a36934553bf2f078f12f87efdfadb1839a07b1d 100644
--- a/docs/java-programming-guide.md
+++ b/docs/java-programming-guide.md
@@ -33,7 +33,7 @@ There are a few key differences between the Java and Scala APIs:
 * RDD methods like `collect()` and `countByKey()` return Java collections types,
   such as `java.util.List` and `java.util.Map`.
 * Key-value pairs, which are simply written as `(key, value)` in Scala, are represented
-  by the `scala.Tuple2` class, and need to be created using `new Tuple2<K, V>(key, value)`
+  by the `scala.Tuple2` class, and need to be created using `new Tuple2<K, V>(key, value)`.
 
 ## RDD Classes
 
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 081b67ae1ea5d00fbae172744217debba51e7268..501b19b79e45f7ee9c4dd28fec1f422b4f17af7e 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -18,7 +18,7 @@ separate branch of Spark, called `yarn`, which you can do as follows:
 - 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`.
+If you want to test out the YARN deployment mode, you can use the current Spark examples. A `spark-examples_2.9.2-0.6.0-SNAPSHOT.jar` file can be generated by running `sbt/sbt package`.
 
 # Launching Spark on YARN
 
@@ -35,7 +35,7 @@ The command to launch the YARN Client is as follows:
 For example:
 
     SPARK_JAR=./core/target/spark-core-assembly-0.6.0-SNAPSHOT.jar ./run spark.deploy.yarn.Client \
-      --jar examples/target/scala-2.9.1/spark-examples_2.9.1-0.6.0-SNAPSHOT.jar \
+      --jar examples/target/scala-2.9.2/spark-examples_2.9.2-0.6.0-SNAPSHOT.jar \
       --class spark.examples.SparkPi \
       --args standalone \
       --num-workers 3 \