Update README.

README.md

-# Spark
-
-Lightning-Fast Cluster Computing - <http://www.spark-project.org/>
-
-
-## Online Documentation
-
-You can find the latest Spark documentation, including a programming
-guide, on the project webpage at <http://spark-project.org/documentation.html>.
-This README file only contains basic setup instructions.
-
-
-## Building
-
-Spark requires Scala 2.9.2 (Scala 2.10 is not yet supported). The project is
-built using Simple Build Tool (SBT), which is packaged with it. To build
-Spark and its example programs, run:
-
-    sbt/sbt package
-
-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..
-
-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:
-
-    ./run spark.examples.SparkLR local[2]
-
-will run the Logistic Regression example locally on 2 CPUs.
-
-Each of the example programs prints usage help if no params are given.
-
-All of the Spark samples take a `<host>` 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.
-
-
-## A Note About Hadoop Versions
-
-Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported
-storage systems. Because the HDFS API has changed in different versions of
-Hadoop, you must build Spark against the same version that your cluster runs.
-You can change the version by setting the `HADOOP_VERSION` variable at the top
-of `project/SparkBuild.scala`, then rebuilding Spark.
-
-
-## Configuration
-
-Please refer to the "Configuration" guide in the online documentation for a
-full overview on how to configure Spark. At the minimum, you will need to
-create a `conf/spark-env.sh` script (copy `conf/spark-env.sh.template`) and
-set the following two variables:
-
-- `SCALA_HOME`: Location where Scala is installed.
-
-- `MESOS_NATIVE_LIBRARY`: Your Mesos library (only needed if you want to run
-  on Mesos). For example, this might be `/usr/local/lib/libmesos.so` on Linux.
-
-
-## Contributing to Spark
-
-Contributions via GitHub pull requests are gladly accepted from their original
-author. Along with any pull requests, please state that the contribution is
-your original work and that you license the work to the project under the
-project's open source license. Whether or not you state this explicitly, by
-submitting any copyrighted material via pull request, email, or other means
-you agree to license the material under the project's open source license and
-warrant that you have the legal authority to do so.
+This is a preview of GraphX that we are actively working....