git commit: README update

[rx...@apache.org]

Repository: spark
Updated Branches:
  refs/heads/master 2089e0e7e -> 28238c81d


README update

Author: Reynold Xin <rx...@apache.org>

Closes #443 from rxin/readme and squashes the following commits:

16853de [Reynold Xin] Updated SBT and Scala instructions.
3ac3ceb [Reynold Xin] README update


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/28238c81
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/28238c81
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/28238c81

Branch: refs/heads/master
Commit: 28238c81d9d81dba5d880cbd7ee910ec326bdc79
Parents: 2089e0e
Author: Reynold Xin <rx...@apache.org>
Authored: Fri Apr 18 22:34:39 2014 -0700
Committer: Reynold Xin <rx...@apache.org>
Committed: Fri Apr 18 22:34:39 2014 -0700

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 README.md | 35 ++++++++++++++++++++++++-----------
 1 file changed, 24 insertions(+), 11 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/28238c81/README.md
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diff --git a/README.md b/README.md
index dc8135b..e2d1dcb 100644
--- a/README.md
+++ b/README.md
@@ -10,20 +10,33 @@ guide, on the project webpage at <http://spark.apache.org/documentation.html>.
 This README file only contains basic setup instructions.
 
 
-## Building
+## Building Spark
 
-Spark requires Scala 2.10. The project is built using Simple Build Tool (SBT),
-which can be obtained [here](http://www.scala-sbt.org). If SBT is installed we
-will use the system version of sbt otherwise we will attempt to download it
-automatically. To build Spark and its example programs, run:
+Spark is built on Scala 2.10. To build Spark and its example programs, run:
 
     ./sbt/sbt assembly
 
-Once you've built Spark, the easiest way to start using it is the shell:
+## Interactive Scala Shell
+
+The easiest way to start using Spark is through the Scala shell:
 
     ./bin/spark-shell
 
-Or, for the Python API, the Python shell (`./bin/pyspark`).
+Try the following command, which should return 1000:
+
+    scala> sc.parallelize(1 to 1000).count()
+
+## Interactive Python Shell
+
+Alternatively, if you prefer Python, you can use the Python shell:
+
+    ./bin/pyspark
+    
+And run the following command, which should also return 1000:
+
+    >>> sc.parallelize(range(1000)).count()
+
+## Example Programs
 
 Spark also comes with several sample programs in the `examples` directory.
 To run one of them, use `./bin/run-example <class> <params>`. For example:
@@ -38,13 +51,13 @@ All of the Spark samples take a `<master>` parameter that is the cluster URL
 to connect to. This can be a mesos:// or spark:// URL, or "local" to run
 locally with one thread, or "local[N]" to run locally with N threads.
 
-## Running tests
+## Running Tests
 
-Testing first requires [Building](#building) Spark. Once Spark is built, tests
+Testing first requires [building Spark](#building-spark). Once Spark is built, tests
 can be run using:
 
-`./sbt/sbt test`
- 
+    ./sbt/sbt test
+
 ## A Note About Hadoop Versions
 
 Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported