Refactored streaming project to separate out the twitter functionality.
Refactored kafka, flume, zeromq, mqtt as separate external projects, with their own self-contained scala API, java API, scala unit tests and java unit tests. Updated examples to use the external projects.
Added pom.xml for external projects and removed unnecessary dependencies and repositoris from other poms and sbt.
Removed unnecessary comments.
Removed extra empty lines.
Merge branch 'apache-master' into project-refactor
Suggested small changes to Java code for slightly more standard style, encapsulation and in some cases performance
Added Scala and Python examples for mllib
Commented the last part of collaborative filtering examples that lead to errors
Merge pull request #1 from apache/master

Merge latest Spark changes
Added ‘-i’ command line option to spark REPL.
We had to create a new implementation of both scala.tools.nsc.CompilerCommand and scala.tools.nsc.Settings, because using scala.tools.nsc.GenericRunnerSettings would bring in other options (-howtorun, -save and -execute) which don’t make sense in Spark.
Any new Spark specific command line option could now be added to org.apache.spark.repl.SparkRunnerSettings class.

Since the behavior of loading a script from the command line should be the same as loading it using the “:load” command inside the shell, the script should be loaded when the SparkContext is available, that’s why we had to move the call to ‘loadfiles(settings)’ _after_ the call to postInitialization(). This still doesn’t work if ‘isAsync = true’.
Added a method to enable bulk prediction
Added unit tests for bulk prediction in MatrixFactorizationModel
Removed unnecessary blank line
Added table of contents and minor fixes
Added python binding for bulk recommendation
Add a script to download sbt if not present on the system
Pass commands down to system sbt as well
Switch from sbt to ./sbt in the README file
Spelling