instead of only once, in case the user changes it across Spark uses

Change defaultPartitioner to use upstream split size.

Moving akka dependency resolver to shared.

Conflicts:
	core/src/main/scala/spark/RDD.scala
	core/src/main/scala/spark/scheduler/cluster/StandaloneSchedulerBackend.scala
	core/src/test/scala/spark/ShuffleSuite.scala

Final set of Spark Streaming changes

Changed class paths and dependencies based on Matei's comments

Streaming bug fixes

Change numSplits to numPartitions in PySpark

support customized java options for Master, Worker, Executor, and Repl

Add RDD.subtract.

Fixed differences in APIs of StreamingContext and JavaStreamingContext. Change rawNetworkStream to rawSocketStream, and added twitter, actor, zeroMQ streams to JavaStreamingContext. Also added them to JavaAPISuite.

Adding Java-accessible methods to Vector.scala

This is needed for the Strata machine learning tutorial (and
also is generally helpful).

Donahue)

Detect when SendingConnections disconnect even if we aren't sending to them

Comment fix

Fixed some of the messages as well as code style.

Also fixed a bug where master was offering executors on dead workers

Conflicts:
	core/src/main/scala/spark/deploy/master/Master.scala

Remove hack workaround for SPARK-668

SPARK-702: Replace Function --> JFunction in JavaAPI Suite.

In a few places the Scala (rather than Java) function class is used.