Change build and run instructions to use assemblies

This commit makes Spark invocation saner by using an assembly JAR to
find all of Spark's dependencies instead of adding all the JARs in
lib_managed. It also packages the examples into an assembly and uses
that as SPARK_EXAMPLES_JAR. Finally, it replaces the old "run" script
with two better-named scripts: "run-examples" for examples, and
"spark-class" for Spark internal classes (e.g. REPL, master, etc). This
is also designed to minimize the confusion people have in trying to use
"run" to run their own classes; it's not meant to do that, but now at
least if they look at it, they can modify run-examples to do a decent
job for them.

As part of this, Bagel's examples are also now properly moved to the
examples package instead of bagel.

1 files changed, 3 insertions, 3 deletions

diff --git a/README.md b/README.md
index e5f527b84a..e7af34f513 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.