diff --git a/README.md b/README.md
index e5f527b84a941795dc0b2819faa34bc5c63f2d7e..e7af34f51319737493d876893a8e34b2f9bdc012 100644
--- a/README.md
+++ b/README.md
@@ -20,16 +20,16 @@ Spark and its example programs, run:
 
 Spark also supports building using Maven. If you would like to build using Maven,
 see the [instructions for building Spark with Maven](http://spark-project.org/docs/latest/building-with-maven.html)
-in the spark documentation..
+in the Spark documentation..
 
 To run Spark, you will need to have Scala's bin directory in your `PATH`, or
 you will need to set the `SCALA_HOME` environment variable to point to where
 you've installed Scala. Scala must be accessible through one of these
 methods on your cluster's worker nodes as well as its master.
 
-To run one of the examples, use `./run <class> <params>`. For example:
+To run one of the examples, use `./run-example <class> <params>`. For example:
 
-    ./run spark.examples.SparkLR local[2]
+    ./run-example spark.examples.SparkLR local[2]
 
 will run the Logistic Regression example locally on 2 CPUs.
 
diff --git a/bin/compute-classpath.sh b/bin/compute-classpath.sh
index 7a21b3c4a140e4f7f006cba08097523be4923e57..5dc86c51a4a2c8caed6772adedf5c5cc2541e1f4 100755
--- a/bin/compute-classpath.sh
+++ b/bin/compute-classpath.sh
@@ -30,79 +30,25 @@ if [ -e $FWDIR/conf/spark-env.sh ] ; then
   . $FWDIR/conf/spark-env.sh
 fi
 
-CORE_DIR="$FWDIR/core"
-REPL_DIR="$FWDIR/repl"
-REPL_BIN_DIR="$FWDIR/repl-bin"
-EXAMPLES_DIR="$FWDIR/examples"
-BAGEL_DIR="$FWDIR/bagel"
-MLLIB_DIR="$FWDIR/mllib"
-TOOLS_DIR="$FWDIR/tools"
-YARN_DIR="$FWDIR/yarn"
-STREAMING_DIR="$FWDIR/streaming"
-PYSPARK_DIR="$FWDIR/python"
-
 # Build up classpath
-CLASSPATH="$SPARK_CLASSPATH"
-
-function dev_classpath {
-  CLASSPATH="$CLASSPATH:$FWDIR/conf"
-  CLASSPATH="$CLASSPATH:$CORE_DIR/target/scala-$SCALA_VERSION/classes"
-  if [ -n "$SPARK_TESTING" ] ; then
-    CLASSPATH="$CLASSPATH:$CORE_DIR/target/scala-$SCALA_VERSION/test-classes"
-    CLASSPATH="$CLASSPATH:$STREAMING_DIR/target/scala-$SCALA_VERSION/test-classes"
-  fi
-  CLASSPATH="$CLASSPATH:$CORE_DIR/src/main/resources"
-  CLASSPATH="$CLASSPATH:$REPL_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$EXAMPLES_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$STREAMING_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$STREAMING_DIR/lib/org/apache/kafka/kafka/0.7.2-spark/*" # <-- our in-project Kafka Jar
-  if [ -e "$FWDIR/lib_managed" ]; then
-    CLASSPATH="$CLASSPATH:$FWDIR/lib_managed/jars/*"
-    CLASSPATH="$CLASSPATH:$FWDIR/lib_managed/bundles/*"
-  fi
-  CLASSPATH="$CLASSPATH:$REPL_DIR/lib/*"
-  # Add the shaded JAR for Maven builds
-  if [ -e $REPL_BIN_DIR/target ]; then
-    for jar in `find "$REPL_BIN_DIR/target" -name 'spark-repl-*-shaded.jar'`; do
-      CLASSPATH="$CLASSPATH:$jar"
-    done
-    # The shaded JAR doesn't contain examples, so include those separately
-    for jar in `find "$EXAMPLES_DIR/target" -name 'spark-examples*[0-9T].jar'`; do
-      CLASSPATH="$CLASSPATH:$jar"
-    done
-  fi
-  CLASSPATH="$CLASSPATH:$BAGEL_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$MLLIB_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$TOOLS_DIR/target/scala-$SCALA_VERSION/classes"
-  CLASSPATH="$CLASSPATH:$YARN_DIR/target/scala-$SCALA_VERSION/classes"
-  for jar in `find $PYSPARK_DIR/lib -name '*jar'`; do
-    CLASSPATH="$CLASSPATH:$jar"
-  done
-
-  # Add Scala standard library
-  if [ -z "$SCALA_LIBRARY_PATH" ]; then
-    if [ -z "$SCALA_HOME" ]; then
-      echo "SCALA_HOME is not set" >&2
-      exit 1
-    fi
-    SCALA_LIBRARY_PATH="$SCALA_HOME/lib"
-  fi
-  CLASSPATH="$CLASSPATH:$SCALA_LIBRARY_PATH/scala-library.jar"
-  CLASSPATH="$CLASSPATH:$SCALA_LIBRARY_PATH/scala-compiler.jar"
-  CLASSPATH="$CLASSPATH:$SCALA_LIBRARY_PATH/jline.jar"
-}
-
-function release_classpath {
-  CLASSPATH="$CLASSPATH:$FWDIR/jars/*"
-}
-
+CLASSPATH="$SPARK_CLASSPATH:$FWDIR/conf"
 if [ -f "$FWDIR/RELEASE" ]; then
-  release_classpath
+  ASSEMBLY_JAR=`ls "$FWDIR"/jars/spark-assembly*.jar`
 else
-  dev_classpath
+  ASSEMBLY_JAR=`ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/spark-assembly*.jar`
+fi
+CLASSPATH="$CLASSPATH:$ASSEMBLY_JAR"
+
+# Add test classes if we're running from SBT or Maven with SPARK_TESTING set to 1
+if [[ $SPARK_TESTING == 1 ]]; then
+  CLASSPATH="$CLASSPATH:$FWDIR/core/target/scala-$SCALA_VERSION/test-classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/repl/target/scala-$SCALA_VERSION/test-classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/mllib/target/scala-$SCALA_VERSION/test-classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/bagel/target/scala-$SCALA_VERSION/test-classes"
+  CLASSPATH="$CLASSPATH:$FWDIR/streaming/target/scala-$SCALA_VERSION/test-classes"
 fi
 
-# Add hadoop conf dir - else FileSystem.*, etc fail !
+# Add hadoop conf dir if given -- otherwise FileSystem.*, etc fail !
 # Note, this assumes that there is either a HADOOP_CONF_DIR or YARN_CONF_DIR which hosts
 # the configurtion files.
 if [ "x" != "x$HADOOP_CONF_DIR" ]; then
diff --git a/bin/spark-daemon.sh b/bin/spark-daemon.sh
index 96c71e66caebdb7307be4eb29c36560841e99d08..eac0774669e125b1dd4fbd5c215883301aaebbb1 100755
--- a/bin/spark-daemon.sh
+++ b/bin/spark-daemon.sh
@@ -87,7 +87,7 @@ TEST_LOG_DIR=$?
 if [ "${TEST_LOG_DIR}" = "0" ]; then
   rm -f $SPARK_LOG_DIR/.spark_test
 else
-  chown $SPARK_IDENT_STRING $SPARK_LOG_DIR 
+  chown $SPARK_IDENT_STRING $SPARK_LOG_DIR
 fi
 
 if [ "$SPARK_PID_DIR" = "" ]; then
@@ -109,7 +109,7 @@ fi
 case $startStop in
 
   (start)
-    
+
     mkdir -p "$SPARK_PID_DIR"
 
     if [ -f $pid ]; then
@@ -128,11 +128,11 @@ case $startStop in
     echo starting $command, logging to $log
     echo "Spark Daemon: $command" > $log
     cd "$SPARK_PREFIX"
-    nohup nice -n $SPARK_NICENESS "$SPARK_PREFIX"/run $command "$@" >> "$log" 2>&1 < /dev/null &
+    nohup nice -n $SPARK_NICENESS "$SPARK_PREFIX"/spark-class $command "$@" >> "$log" 2>&1 < /dev/null &
     echo $! > $pid
     sleep 1; head "$log"
     ;;
-          
+
   (stop)
 
     if [ -f $pid ]; then
diff --git a/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala b/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala
index 6ebbb5ec9b2643964f4c338babbebee38ca08a8b..ebfc21392dd9cbbcd26149ba0c6829f705caeb4a 100644
--- a/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala
+++ b/core/src/main/scala/spark/scheduler/mesos/CoarseMesosSchedulerBackend.scala
@@ -125,7 +125,7 @@ private[spark] class CoarseMesosSchedulerBackend(
       StandaloneSchedulerBackend.ACTOR_NAME)
     val uri = System.getProperty("spark.executor.uri")
     if (uri == null) {
-      val runScript = new File(sparkHome, "run").getCanonicalPath
+      val runScript = new File(sparkHome, "spark-class").getCanonicalPath
       command.setValue("\"%s\" spark.executor.StandaloneExecutorBackend %s %s %s %d".format(
         runScript, driverUrl, offer.getSlaveId.getValue, offer.getHostname, numCores))
     } else {
diff --git a/core/src/test/scala/spark/DriverSuite.scala b/core/src/test/scala/spark/DriverSuite.scala
index ed16b9d8efd176b6887e6b5957eaf32988033d28..553c0309f66fa5d4c5ca58202e3f4723d5fdd018 100644
--- a/core/src/test/scala/spark/DriverSuite.scala
+++ b/core/src/test/scala/spark/DriverSuite.scala
@@ -34,7 +34,7 @@ class DriverSuite extends FunSuite with Timeouts {
     val masters = Table(("master"), ("local"), ("local-cluster[2,1,512]"))
     forAll(masters) { (master: String) =>
       failAfter(30 seconds) {
-        Utils.execute(Seq("./run", "spark.DriverWithoutCleanup", master),
+        Utils.execute(Seq("./spark-class", "spark.DriverWithoutCleanup", master),
           new File(System.getenv("SPARK_HOME")))
       }
     }
diff --git a/docs/bagel-programming-guide.md b/docs/bagel-programming-guide.md
index 8a0fa42d946011218d89a2f3b041e3a7f37cd29b..c526da3ca0bca75d0919f9655fb09e353073b285 100644
--- a/docs/bagel-programming-guide.md
+++ b/docs/bagel-programming-guide.md
@@ -158,4 +158,4 @@ trait Message[K] {
 
 ## Where to Go from Here
 
-Two example jobs, PageRank and shortest path, are included in `bagel/src/main/scala/spark/bagel/examples`. You can run them by passing the class name to the `run` script included in Spark -- for example, `./run spark.bagel.examples.WikipediaPageRank`. Each example program prints usage help when run without any arguments.
+Two example jobs, PageRank and shortest path, are included in `examples/src/main/scala/spark/examples/bagel`. You can run them by passing the class name to the `run-example` script included in Spark -- for example, `./run-example spark.examples.bagel.WikipediaPageRank`. Each example program prints usage help when run without any arguments.
diff --git a/docs/index.md b/docs/index.md
index 0c4add45dcd2adb6a5b4783a670afb985a6b8ce0..e51a6998f6c41b55814d4e269df8359942aa677c 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -27,9 +27,9 @@ Spark also supports building using Maven. If you would like to build using Maven
 # Testing the Build
 
 Spark comes with a number of sample programs in the `examples` directory.
-To run one of the samples, use `./run <class> <params>` in the top-level Spark directory
+To run one of the samples, use `./run-example <class> <params>` in the top-level Spark directory
 (the `run` script sets up the appropriate paths and launches that program).
-For example, `./run spark.examples.SparkPi` will run a sample program that estimates Pi. Each of the
+For example, `./run-example spark.examples.SparkPi` will run a sample program that estimates Pi. Each of the
 examples prints usage help if no params are given.
 
 Note that all of the sample programs take a `<master>` parameter specifying the cluster URL
diff --git a/docs/java-programming-guide.md b/docs/java-programming-guide.md
index ae8257b53938e0672efc1cb35d4f77893a7a1ec2..dd19a5f0c970cdd96c5d9be0acc3255f7689d933 100644
--- a/docs/java-programming-guide.md
+++ b/docs/java-programming-guide.md
@@ -190,6 +190,6 @@ We hope to generate documentation with Java-style syntax in the future.
 
 Spark includes several sample programs using the Java API in
 [`examples/src/main/java`](https://github.com/mesos/spark/tree/master/examples/src/main/java/spark/examples).  You can run them by passing the class name to the
-`run` script included in Spark -- for example, `./run
+`run-example` script included in Spark -- for example, `./run-example
 spark.examples.JavaWordCount`.  Each example program prints usage help when run
 without any arguments.
diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 1a0afd19d43597f932f4fefe2be6c7630f40aaa9..678cd57abac4c4deefef6000397316b58fe8ee4b 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -15,9 +15,9 @@ We need a consolidated spark core jar (which bundles all the required dependenci
 This can be built either through sbt or via maven.
 
 -   Building spark assembled jar via sbt.
-Enable YARN support by setting `SPARK_WITH_YARN=true` when invoking sbt:
+Enable YARN support by setting `SPARK_YARN=true` when invoking sbt:
 
-    SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_WITH_YARN=true ./sbt/sbt clean assembly
+    SPARK_HADOOP_VERSION=2.0.5-alpha SPARK_YARN=true ./sbt/sbt clean assembly
 
 The assembled jar would typically be something like :
 `./yarn/target/spark-yarn-assembly-0.8.0-SNAPSHOT.jar`
@@ -55,7 +55,7 @@ This would be used to connect to the cluster, write to the dfs and submit jobs t
 
 The command to launch the YARN Client is as follows:
 
-    SPARK_JAR=<SPARK_YARN_JAR_FILE> ./run spark.deploy.yarn.Client \
+    SPARK_JAR=<SPARK_YARN_JAR_FILE> ./spark-class spark.deploy.yarn.Client \
       --jar <YOUR_APP_JAR_FILE> \
       --class <APP_MAIN_CLASS> \
       --args <APP_MAIN_ARGUMENTS> \
@@ -67,7 +67,7 @@ The command to launch the YARN Client is as follows:
 
 For example:
 
-    SPARK_JAR=./yarn/target/spark-yarn-assembly-{{site.SPARK_VERSION}}.jar ./run spark.deploy.yarn.Client \
+    SPARK_JAR=./yarn/target/spark-yarn-assembly-{{site.SPARK_VERSION}}.jar ./spark-class spark.deploy.yarn.Client \
       --jar examples/target/scala-{{site.SCALA_VERSION}}/spark-examples_{{site.SCALA_VERSION}}-{{site.SPARK_VERSION}}.jar \
       --class spark.examples.SparkPi \
       --args yarn-standalone \
diff --git a/docs/scala-programming-guide.md b/docs/scala-programming-guide.md
index e9cf9ef36fcc4b7abb0468b81517292ae54b3ec2..db584d2096e79a111c613f4ea2ea8e2fc00f31b1 100644
--- a/docs/scala-programming-guide.md
+++ b/docs/scala-programming-guide.md
@@ -356,7 +356,7 @@ res2: Int = 10
 # Where to Go from Here
 
 You can see some [example Spark programs](http://www.spark-project.org/examples.html) on the Spark website.
-In addition, Spark includes several sample programs in `examples/src/main/scala`. Some of them have both Spark versions and local (non-parallel) versions, allowing you to see what had to be changed to make the program run on a cluster. You can run them using by passing the class name to the `run` script included in Spark -- for example, `./run spark.examples.SparkPi`. Each example program prints usage help when run without any arguments.
+In addition, Spark includes several sample programs in `examples/src/main/scala`. Some of them have both Spark versions and local (non-parallel) versions, allowing you to see what had to be changed to make the program run on a cluster. You can run them using by passing the class name to the `run-example` script included in Spark -- for example, `./run-example spark.examples.SparkPi`. Each example program prints usage help when run without any arguments.
 
 For help on optimizing your program, the [configuration](configuration.html) and
 [tuning](tuning.html) guides provide information on best practices. They are especially important for
diff --git a/docs/spark-standalone.md b/docs/spark-standalone.md
index 7463844a4e36aba77ff99f63fbdabbebe32d2df0..bb8be276c53c62ff8d798133f0e569ba541e34f8 100644
--- a/docs/spark-standalone.md
+++ b/docs/spark-standalone.md
@@ -20,7 +20,7 @@ Compile Spark with `sbt package` as described in the [Getting Started Guide](ind
 
 You can start a standalone master server by executing:
 
-    ./run spark.deploy.master.Master
+    ./spark-class spark.deploy.master.Master
 
 Once started, the master will print out a `spark://IP:PORT` URL for itself, which you can use to connect workers to it,
 or pass as the "master" argument to `SparkContext` to connect a job to the cluster. You can also find this URL on
@@ -28,7 +28,7 @@ the master's web UI, which is [http://localhost:8080](http://localhost:8080) by
 
 Similarly, you can start one or more workers and connect them to the master via:
 
-    ./run spark.deploy.worker.Worker spark://IP:PORT
+    ./spark-class spark.deploy.worker.Worker spark://IP:PORT
 
 Once you have started a worker, look at the master's web UI ([http://localhost:8080](http://localhost:8080) by default).
 You should see the new node listed there, along with its number of CPUs and memory (minus one gigabyte left for the OS).
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index a74c17bdb7a0ae20965e4d24bd2727fe6710d84a..3330e635986d805da2bcc1954943ffcb5e52ad5c 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -234,7 +234,7 @@ $ nc -lk 9999
 Then, in a different terminal, you can start NetworkWordCount by using
 
 {% highlight bash %}
-$ ./run spark.streaming.examples.NetworkWordCount local[2] localhost 9999
+$ ./run-example spark.streaming.examples.NetworkWordCount local[2] localhost 9999
 {% endhighlight %}
 
 This will make NetworkWordCount connect to the netcat server. Any lines typed in the terminal running the netcat server will be counted and printed on screen.
@@ -272,7 +272,7 @@ Time: 1357008430000 ms
 </td>
 </table>
 
-You can find more examples in `<Spark repo>/streaming/src/main/scala/spark/streaming/examples/`. They can be run in the similar manner using `./run spark.streaming.examples....` . Executing without any parameter would give the required parameter list. Further explanation to run them can be found in comments in the files.
+You can find more examples in `<Spark repo>/streaming/src/main/scala/spark/streaming/examples/`. They can be run in the similar manner using `./run-example spark.streaming.examples....` . Executing without any parameter would give the required parameter list. Further explanation to run them can be found in comments in the files.
 
 # DStream Persistence
 Similar to RDDs, DStreams also allow developers to persist the stream's data in memory. That is, using `persist()` method on a DStream would automatically persist every RDD of that DStream in memory. This is useful if the data in the DStream will be computed multiple times (e.g., multiple operations on the same data). For window-based operations like `reduceByWindow` and `reduceByKeyAndWindow` and state-based operations like `updateStateByKey`, this is implicitly true. Hence, DStreams generated by window-based operations are automatically persisted in memory, without the developer calling `persist()`.
diff --git a/examples/pom.xml b/examples/pom.xml
index 0db52b8691cbe2499b8f756529e3016abf3cd4ed..d24bd404fa2d97c5b3b9817568c391124a688718 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -47,6 +47,11 @@
       <artifactId>spark-mllib</artifactId>
       <version>${project.version}</version>
     </dependency>
+    <dependency>
+      <groupId>org.spark-project</groupId>
+      <artifactId>spark-bagel</artifactId>
+      <version>${project.version}</version>
+    </dependency>
     <dependency>
       <groupId>org.apache.hbase</groupId>
       <artifactId>hbase</artifactId>
diff --git a/bagel/src/main/scala/spark/bagel/examples/PageRankUtils.scala b/examples/src/main/scala/spark/examples/bagel/PageRankUtils.scala
similarity index 99%
rename from bagel/src/main/scala/spark/bagel/examples/PageRankUtils.scala
rename to examples/src/main/scala/spark/examples/bagel/PageRankUtils.scala
index de65e27fe0ece661bbce0376707970c8e1113dbe..c23ee9895f2b73f139a551ce542d2da1dbfafe7f 100644
--- a/bagel/src/main/scala/spark/bagel/examples/PageRankUtils.scala
+++ b/examples/src/main/scala/spark/examples/bagel/PageRankUtils.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package spark.bagel.examples
+package spark.examples.bagel
 
 import spark._
 import spark.SparkContext._
diff --git a/bagel/src/main/scala/spark/bagel/examples/WikipediaPageRank.scala b/examples/src/main/scala/spark/examples/bagel/WikipediaPageRank.scala
similarity index 99%
rename from bagel/src/main/scala/spark/bagel/examples/WikipediaPageRank.scala
rename to examples/src/main/scala/spark/examples/bagel/WikipediaPageRank.scala
index a0c5ac9c183463bb09310424afca51c125fda46d..00635a7ffa2f7471c3db86fe3d31d1aea91d9de4 100644
--- a/bagel/src/main/scala/spark/bagel/examples/WikipediaPageRank.scala
+++ b/examples/src/main/scala/spark/examples/bagel/WikipediaPageRank.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package spark.bagel.examples
+package spark.examples.bagel
 
 import spark._
 import spark.SparkContext._
diff --git a/bagel/src/main/scala/spark/bagel/examples/WikipediaPageRankStandalone.scala b/examples/src/main/scala/spark/examples/bagel/WikipediaPageRankStandalone.scala
similarity index 99%
rename from bagel/src/main/scala/spark/bagel/examples/WikipediaPageRankStandalone.scala
rename to examples/src/main/scala/spark/examples/bagel/WikipediaPageRankStandalone.scala
index 3c54a85f425dfd02626759edf1c4c333a9526f97..c416ddbc584bdb2d20b9b5b5abb55231762f325d 100644
--- a/bagel/src/main/scala/spark/bagel/examples/WikipediaPageRankStandalone.scala
+++ b/examples/src/main/scala/spark/examples/bagel/WikipediaPageRankStandalone.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package spark.bagel.examples
+package spark.examples.bagel
 
 import spark._
 import serializer.{DeserializationStream, SerializationStream, SerializerInstance}
diff --git a/make-distribution.sh b/make-distribution.sh
index 70aff418c709267cceb059a09a49a71b4ac30120..df7bbf1e748e91671e2a3700b8a6054ba78d88a1 100755
--- a/make-distribution.sh
+++ b/make-distribution.sh
@@ -47,7 +47,7 @@ VERSION=$($FWDIR/sbt/sbt "show version" | tail -1 | cut -f 2 | sed 's/^\([a-zA-Z
 
 # Initialize defaults
 SPARK_HADOOP_VERSION=1.0.4
-SPARK_WITH_YARN=false
+SPARK_YARN=false
 MAKE_TGZ=false
 
 # Parse arguments
@@ -58,7 +58,7 @@ while (( "$#" )); do
       shift
       ;;
     --with-yarn)
-      SPARK_WITH_YARN=true
+      SPARK_YARN=true
       ;;
     --tgz)
       MAKE_TGZ=true
@@ -74,7 +74,7 @@ else
 fi
 
 echo "Hadoop version set to $SPARK_HADOOP_VERSION"
-if [ "$SPARK_WITH_YARN" == "true" ]; then
+if [ "$SPARK_YARN" == "true" ]; then
   echo "YARN enabled"
 else
   echo "YARN disabled"
@@ -82,21 +82,22 @@ fi
 
 # Build fat JAR
 export SPARK_HADOOP_VERSION
-export SPARK_WITH_YARN
-"$FWDIR/sbt/sbt" "repl/assembly"
+export SPARK_YARN
+"$FWDIR/sbt/sbt" "assembly/assembly"
 
 # Make directories
 rm -rf "$DISTDIR"
 mkdir -p "$DISTDIR/jars"
-echo "$VERSION" > "$DISTDIR/RELEASE"
+echo "Spark $VERSION built for Hadoop $SPARK_HADOOP_VERSION" > "$DISTDIR/RELEASE"
 
 # Copy jars
-cp $FWDIR/repl/target/*.jar "$DISTDIR/jars/"
+cp $FWDIR/assembly/target/*/*assembly*.jar "$DISTDIR/jars/"
 
 # Copy other things
 cp -r "$FWDIR/bin" "$DISTDIR"
 cp -r "$FWDIR/conf" "$DISTDIR"
-cp "$FWDIR/run" "$FWDIR/spark-shell" "$DISTDIR"
+cp "$FWDIR/spark-class" "$DISTDIR"
+cp "$FWDIR/spark-shell" "$DISTDIR"
 cp "$FWDIR/spark-executor" "$DISTDIR"
 
 
diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala
index 5fdcf19b62401e7fb742bd545b75da0fb5c1819a..b3bf3ef89b064e9f954d2941dfa5e5006051ed4f 100644
--- a/project/SparkBuild.scala
+++ b/project/SparkBuild.scala
@@ -26,30 +26,35 @@ import AssemblyKeys._
 object SparkBuild extends Build {
   // Hadoop version to build against. For example, "1.0.4" for Apache releases, or
   // "2.0.0-mr1-cdh4.2.0" for Cloudera Hadoop. Note that these variables can be set
-  // through the environment variables SPARK_HADOOP_VERSION and SPARK_WITH_YARN.
+  // through the environment variables SPARK_HADOOP_VERSION and SPARK_YARN.
   val DEFAULT_HADOOP_VERSION = "1.0.4"
-  val DEFAULT_WITH_YARN = false
+  val DEFAULT_YARN = false
 
   // HBase version; set as appropriate.
   val HBASE_VERSION = "0.94.6"
 
-  lazy val root = Project("root", file("."), settings = rootSettings) aggregate(allProjects:_*)
+  lazy val root = Project("root", file("."), settings = rootSettings) aggregate(allProjects: _*)
 
   lazy val core = Project("core", file("core"), settings = coreSettings)
 
-  lazy val repl = Project("repl", file("repl"), settings = replSettings) dependsOn(core) dependsOn(bagel) dependsOn(mllib) dependsOn(maybeYarn:_*)
+  lazy val repl = Project("repl", file("repl"), settings = replSettings)
+    .dependsOn(core, bagel, mllib) dependsOn(maybeYarn: _*)
 
-  lazy val examples = Project("examples", file("examples"), settings = examplesSettings) dependsOn (core) dependsOn (streaming) dependsOn(mllib)
+  lazy val examples = Project("examples", file("examples"), settings = examplesSettings)
+    .dependsOn(core, mllib, bagel, streaming)
 
-  lazy val tools = Project("tools", file("tools"), settings = examplesSettings) dependsOn (core) dependsOn (streaming)
+  lazy val tools = Project("tools", file("tools"), settings = toolsSettings) dependsOn(core) dependsOn(streaming)
 
-  lazy val bagel = Project("bagel", file("bagel"), settings = bagelSettings) dependsOn (core)
+  lazy val bagel = Project("bagel", file("bagel"), settings = bagelSettings) dependsOn(core)
 
-  lazy val streaming = Project("streaming", file("streaming"), settings = streamingSettings) dependsOn (core)
+  lazy val streaming = Project("streaming", file("streaming"), settings = streamingSettings) dependsOn(core)
 
-  lazy val mllib = Project("mllib", file("mllib"), settings = mllibSettings) dependsOn (core)
+  lazy val mllib = Project("mllib", file("mllib"), settings = mllibSettings) dependsOn(core)
 
-  lazy val yarn = Project("yarn", file("yarn"), settings = yarnSettings) dependsOn (core)
+  lazy val yarn = Project("yarn", file("yarn"), settings = yarnSettings) dependsOn(core)
+
+  lazy val assemblyProj = Project("assembly", file("assembly"), settings = assemblyProjSettings)
+    .dependsOn(core, bagel, mllib, repl, streaming) dependsOn(maybeYarn: _*)
 
   // A configuration to set an alternative publishLocalConfiguration
   lazy val MavenCompile = config("m2r") extend(Compile)
@@ -57,15 +62,16 @@ object SparkBuild extends Build {
 
   // Allows build configuration to be set through environment variables
   lazy val hadoopVersion = scala.util.Properties.envOrElse("SPARK_HADOOP_VERSION", DEFAULT_HADOOP_VERSION)
-  lazy val isYarnEnabled = scala.util.Properties.envOrNone("SPARK_WITH_YARN") match {
-    case None => DEFAULT_WITH_YARN
+  lazy val isYarnEnabled = scala.util.Properties.envOrNone("SPARK_YARN") match {
+    case None => DEFAULT_YARN
     case Some(v) => v.toBoolean
   }
 
   // Conditionally include the yarn sub-project
   lazy val maybeYarn = if(isYarnEnabled) Seq[ClasspathDependency](yarn) else Seq[ClasspathDependency]()
   lazy val maybeYarnRef = if(isYarnEnabled) Seq[ProjectReference](yarn) else Seq[ProjectReference]()
-  lazy val allProjects = Seq[ProjectReference](core, repl, examples, bagel, streaming, mllib, tools) ++ maybeYarnRef
+  lazy val allProjects = Seq[ProjectReference](
+    core, repl, examples, bagel, streaming, mllib, tools, assemblyProj) ++ maybeYarnRef
 
   def sharedSettings = Defaults.defaultSettings ++ Seq(
     organization := "org.spark-project",
@@ -100,8 +106,8 @@ object SparkBuild extends Build {
       <url>http://spark-project.org/</url>
       <licenses>
         <license>
-          <name>BSD License</name>
-          <url>https://github.com/mesos/spark/blob/master/LICENSE</url>
+          <name>Apache 2.0 License</name>
+          <url>http://www.apache.org/licenses/LICENSE-2.0.html</url>
           <distribution>repo</distribution>
         </license>
       </licenses>
@@ -195,7 +201,7 @@ object SparkBuild extends Build {
       "com.twitter" % "chill_2.9.3" % "0.3.1",
       "com.twitter" % "chill-java" % "0.3.1"
     )
-  ) ++ assemblySettings ++ extraAssemblySettings
+  )
 
   def rootSettings = sharedSettings ++ Seq(
     publish := {}
@@ -204,7 +210,7 @@ object SparkBuild extends Build {
   def replSettings = sharedSettings ++ Seq(
     name := "spark-repl",
     libraryDependencies <+= scalaVersion("org.scala-lang" % "scala-compiler" % _)
-  ) ++ assemblySettings ++ extraAssemblySettings
+  )
 
   def examplesSettings = sharedSettings ++ Seq(
     name := "spark-examples",
@@ -223,7 +229,7 @@ object SparkBuild extends Build {
         exclude("org.apache.cassandra.deps", "avro")
         excludeAll(excludeSnappy)
     )
-  )
+  ) ++ assemblySettings ++ extraAssemblySettings
 
   def toolsSettings = sharedSettings ++ Seq(
     name := "spark-tools"
@@ -251,7 +257,7 @@ object SparkBuild extends Build {
       "org.twitter4j" % "twitter4j-stream" % "3.0.3" excludeAll(excludeNetty),
       "com.typesafe.akka" % "akka-zeromq" % "2.0.5" excludeAll(excludeNetty)
     )
-  ) ++ assemblySettings ++ extraAssemblySettings
+  )
 
   def yarnSettings = sharedSettings ++ Seq(
     name := "spark-yarn"
@@ -271,7 +277,13 @@ object SparkBuild extends Build {
     )
   )
 
-  def extraAssemblySettings() = Seq(test in assembly := {}) ++ Seq(
+  def assemblyProjSettings = sharedSettings ++ Seq(
+    name := "spark-assembly",
+    jarName in assembly <<= version map { v => "spark-assembly-" + v + "-hadoop" + hadoopVersion + ".jar" }
+  ) ++ assemblySettings ++ extraAssemblySettings
+
+  def extraAssemblySettings() = Seq(
+    test in assembly := {},
     mergeStrategy in assembly := {
       case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
       case m if m.toLowerCase.matches("meta-inf.*\\.sf$") => MergeStrategy.discard
diff --git a/project/build.properties b/project/build.properties
index 08e17131f64d180a386b9f77693d988ba6c5b0ca..96472771622d8e2ef4519ff645d6d195c1f9cdd6 100644
--- a/project/build.properties
+++ b/project/build.properties
@@ -15,4 +15,4 @@
 # limitations under the License.
 #
 
-sbt.version=0.12.3
+sbt.version=0.12.4
diff --git a/project/plugins.sbt b/project/plugins.sbt
index 783b40d4f5d903fa411638142f6ac1f3ffa8e8f7..cfcd85082a8cc5c60b9b850710028f154b3682e5 100644
--- a/project/plugins.sbt
+++ b/project/plugins.sbt
@@ -4,7 +4,7 @@ resolvers += "Typesafe Repository" at "http://repo.typesafe.com/typesafe/release
 
 resolvers += "Spray Repository" at "http://repo.spray.cc/"
 
-addSbtPlugin("com.eed3si9n" % "sbt-assembly" % "0.8.5")
+addSbtPlugin("com.eed3si9n" % "sbt-assembly" % "0.9.1")
 
 addSbtPlugin("com.typesafe.sbteclipse" % "sbteclipse-plugin" % "2.2.0")
 
diff --git a/python/pyspark/java_gateway.py b/python/pyspark/java_gateway.py
index e503fb7621e0dd0d9a06a9b303749e892ff470e3..18011c0dc9c83e172e65640aaa22993de93dd2f5 100644
--- a/python/pyspark/java_gateway.py
+++ b/python/pyspark/java_gateway.py
@@ -28,7 +28,7 @@ SPARK_HOME = os.environ["SPARK_HOME"]
 def launch_gateway():
     # Launch the Py4j gateway using Spark's run command so that we pick up the
     # proper classpath and SPARK_MEM settings from spark-env.sh
-    command = [os.path.join(SPARK_HOME, "run"), "py4j.GatewayServer",
+    command = [os.path.join(SPARK_HOME, "spark-class"), "py4j.GatewayServer",
                "--die-on-broken-pipe", "0"]
     proc = Popen(command, stdout=PIPE, stdin=PIPE)
     # Determine which ephemeral port the server started on:
diff --git a/run-example b/run-example
new file mode 100755
index 0000000000000000000000000000000000000000..e1b26257e14560da07b0d2c4ae6d1d5d18f4ffbe
--- /dev/null
+++ b/run-example
@@ -0,0 +1,76 @@
+#!/usr/bin/env bash
+
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+SCALA_VERSION=2.9.3
+
+# Figure out where the Scala framework is installed
+FWDIR="$(cd `dirname $0`; pwd)"
+
+# Export this as SPARK_HOME
+export SPARK_HOME="$FWDIR"
+
+# Load environment variables from conf/spark-env.sh, if it exists
+if [ -e $FWDIR/conf/spark-env.sh ] ; then
+  . $FWDIR/conf/spark-env.sh
+fi
+
+if [ -z "$1" ]; then
+  echo "Usage: run-example <example-class> [<args>]" >&2
+  exit 1
+fi
+
+# Figure out the JAR file that our examples were packaged into. This includes a bit of a hack
+# to avoid the -sources and -doc packages that are built by publish-local.
+EXAMPLES_DIR="$FWDIR"/examples
+SPARK_EXAMPLES_JAR=""
+if [ -e "$EXAMPLES_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9T].jar ]; then
+  # Use the JAR from the SBT build
+  export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR"/target/scala-$SCALA_VERSION/*assembly*[0-9T].jar`
+fi
+if [ -e "$EXAMPLES_DIR"/target/spark-examples*[0-9T].jar ]; then
+  # Use the JAR from the Maven build
+  # TODO: this also needs to become an assembly!
+  export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR"/target/spark-examples*[0-9T].jar`
+fi
+if [[ -z $SPARK_EXAMPLES_JAR ]]; then
+  echo "Failed to find Spark examples assembly in $FWDIR/examples/target" >&2
+  echo "You need to compile Spark before running this program" >&2
+  exit 1
+fi
+
+# Find java binary
+if [ -n "${JAVA_HOME}" ]; then
+  RUNNER="${JAVA_HOME}/bin/java"
+else
+  if [ `command -v java` ]; then
+    RUNNER="java"
+  else
+    echo "JAVA_HOME is not set" >&2
+    exit 1
+  fi
+fi
+
+if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then
+  echo -n "Spark Command: "
+  echo "$RUNNER" -cp "$SPARK_EXAMPLES_JAR" "$@"
+  echo "========================================"
+  echo
+fi
+
+exec "$RUNNER" -cp "$SPARK_EXAMPLES_JAR" "$@"
diff --git a/run b/spark-class
similarity index 52%
rename from run
rename to spark-class
index 715bbf93d5537b4771d5a4f802978e919bf4835e..5ef3de977371e4dd589668a700e99b9a4bd825ed 100755
--- a/run
+++ b/spark-class
@@ -66,51 +66,27 @@ case "$1" in
     ;;
 esac
 
-# Figure out whether to run our class with java or with the scala launcher.
-# In most cases, we'd prefer to execute our process with java because scala
-# creates a shell script as the parent of its Java process, which makes it
-# hard to kill the child with stuff like Process.destroy(). However, for
-# the Spark shell, the wrapper is necessary to properly reset the terminal
-# when we exit, so we allow it to set a variable to launch with scala.
-# We still fall back on java for the shell if this is a "release" created
-# from make-distribution.sh since it's possible scala is not installed
-# but we have everything we need to run the shell.
-if [[ "$SPARK_LAUNCH_WITH_SCALA" == "1" && ! -f "$FWDIR/RELEASE" ]]; then
-  if [ "$SCALA_HOME" ]; then
-    RUNNER="${SCALA_HOME}/bin/scala"
-  else
-    if [ `command -v scala` ]; then
-      RUNNER="scala"
-    else
-      echo "SCALA_HOME is not set and scala is not in PATH" >&2
-      exit 1
-    fi
-  fi
+# Find the java binary
+if [ -n "${JAVA_HOME}" ]; then
+  RUNNER="${JAVA_HOME}/bin/java"
 else
-  if [ -n "${JAVA_HOME}" ]; then
-    RUNNER="${JAVA_HOME}/bin/java"
+  if [ `command -v java` ]; then
+    RUNNER="java"
   else
-    if [ `command -v java` ]; then
-      RUNNER="java"
-    else
-      echo "JAVA_HOME is not set" >&2
-      exit 1
-    fi
+    echo "JAVA_HOME is not set" >&2
+    exit 1
   fi
-  if [[ ! -f "$FWDIR/RELEASE" && -z "$SCALA_LIBRARY_PATH" ]]; then
-    if [ -z "$SCALA_HOME" ]; then
-      echo "SCALA_HOME is not set" >&2
-      exit 1
-    fi
-    SCALA_LIBRARY_PATH="$SCALA_HOME/lib"
+fi
+if [[ ! -f "$FWDIR/RELEASE" && -z "$SCALA_LIBRARY_PATH" ]]; then
+  if [ -z "$SCALA_HOME" ]; then
+    echo "SCALA_HOME is not set" >&2
+    exit 1
   fi
+  SCALA_LIBRARY_PATH="$SCALA_HOME/lib"
 fi
 
-# Figure out how much memory to use per executor and set it as an environment
-# variable so that our process sees it and can report it to Mesos
-if [ -z "$SPARK_MEM" ] ; then
-  SPARK_MEM="512m"
-fi
+# Set SPARK_MEM if it isn't already set since we also use it for this process
+SPARK_MEM=${SPARK_MEM:-512m}
 export SPARK_MEM
 
 # Set JAVA_OPTS to be able to load native libraries and to set heap size
@@ -125,51 +101,24 @@ export JAVA_OPTS
 # Attention: when changing the way the JAVA_OPTS are assembled, the change must be reflected in ExecutorRunner.scala!
 
 if [ ! -f "$FWDIR/RELEASE" ]; then
-  CORE_DIR="$FWDIR/core"
-  EXAMPLES_DIR="$FWDIR/examples"
-  REPL_DIR="$FWDIR/repl"
-
   # Exit if the user hasn't compiled Spark
-  if [ ! -e "$CORE_DIR/target" ]; then
-    echo "Failed to find Spark classes in $CORE_DIR/target" >&2
+  ls "$FWDIR"/assembly/target/scala-$SCALA_VERSION/spark-assembly*.jar >& /dev/null
+  if [[ $? != 0 ]]; then
+    echo "Failed to find Spark assembly in $FWDIR/assembly/target" >&2
     echo "You need to compile Spark before running this program" >&2
     exit 1
   fi
-
-  if [[ "$@" = *repl* && ! -e "$REPL_DIR/target" ]]; then
-    echo "Failed to find Spark classes in $REPL_DIR/target" >&2
-    echo "You need to compile Spark repl module before running this program" >&2
-    exit 1
-  fi
-
-  # Figure out the JAR file that our examples were packaged into. This includes a bit of a hack
-  # to avoid the -sources and -doc packages that are built by publish-local.
-  if [ -e "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar ]; then
-    # Use the JAR from the SBT build
-    export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/scala-$SCALA_VERSION/spark-examples"*[0-9T].jar`
-  fi
-  if [ -e "$EXAMPLES_DIR/target/spark-examples"*[0-9T].jar ]; then
-    # Use the JAR from the Maven build
-    export SPARK_EXAMPLES_JAR=`ls "$EXAMPLES_DIR/target/spark-examples"*[0-9T].jar`
-  fi
 fi
 
 # Compute classpath using external script
 CLASSPATH=`$FWDIR/bin/compute-classpath.sh`
 export CLASSPATH
 
-if [ "$SPARK_LAUNCH_WITH_SCALA" == "1" ]; then
-  EXTRA_ARGS=""     # Java options will be passed to scala as JAVA_OPTS
-else
-  # The JVM doesn't read JAVA_OPTS by default so we need to pass it in
-  EXTRA_ARGS="$JAVA_OPTS"
-fi
-
-command="$RUNNER -cp \"$CLASSPATH\" $EXTRA_ARGS $@"
 if [ "$SPARK_PRINT_LAUNCH_COMMAND" == "1" ]; then
-  echo "Spark Command: $command"
+  echo -n "Spark Command: "
+  echo "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"
   echo "========================================"
   echo
 fi
 
-exec "$RUNNER" -cp "$CLASSPATH" $EXTRA_ARGS "$@"
+exec "$RUNNER" -cp "$CLASSPATH" $JAVA_OPTS "$@"
diff --git a/spark-executor b/spark-executor
index feccbf5cc2aaf4547ead01eae80d367856691920..63692bd46c939428ee598b43ea8a041cce808fd6 100755
--- a/spark-executor
+++ b/spark-executor
@@ -19,4 +19,4 @@
 
 FWDIR="`dirname $0`"
 echo "Running spark-executor with framework dir = $FWDIR"
-exec $FWDIR/run spark.executor.MesosExecutorBackend
+exec $FWDIR/spark-class spark.executor.MesosExecutorBackend
diff --git a/spark-shell b/spark-shell
index 62fc18550dfa5e270937d9698452d11432b9d22e..4d379c5cfb9f3adbabe28d9d0db881143d24bd0d 100755
--- a/spark-shell
+++ b/spark-shell
@@ -79,8 +79,7 @@ if [[ ! $? ]]; then
   saved_stty=""
 fi
 
-export SPARK_LAUNCH_WITH_SCALA=${SPARK_LAUNCH_WITH_SCALA:-1}
-$FWDIR/run $OPTIONS spark.repl.Main "$@"
+$FWDIR/spark-class $OPTIONS spark.repl.Main "$@"
 
 # record the exit status lest it be overwritten:
 # then reenable echo and propagate the code.