Added filter functionality to reduceByKeyAndWindow with inverse. Consolidated reduceByKeyAndWindow's many functions into smaller number of functions with optional parameters.

Changed scheduler and file input stream to fix bugs in the driver fault tolerance. Added MasterFailureTest to rigorously test master fault tolerance with file input stream.

Fixed bugs in FileInputDStream and Scheduler that occasionally failed to reprocess old files after recovering from master failure. Completely modified spark.streaming.FailureTest to test multiple master failures using file input stream.

Removing offset management code that is non-existent in kafka 0.7.0+

StateDStream changes to give updateStateByKey consistent behavior

Inline mergePair to look more like the narrow dep branch.

Handle Terminated to avoid endless DeathPactExceptions.

Conflicts:
	core/src/main/scala/spark/deploy/worker/Worker.scala

Increase DriverSuite timeout.

Credit to Roland Kuhn, Akka's tech lead, for pointing out this
various obvious fix, but StandaloneExecutorBackend.preStart's
catch block would never (ever) get hit, because all of the
operation's in preStart are async.

So, the System.exit in the catch block was skipped, and instead
Akka was sending Terminated messages which, since we didn't
handle, it turned into DeathPactException, which started
a postRestart/preStart infinite loop.

No functionality changes, I think this is just more consistent
given mergePair isn't called multiple times/recursive.

Also added a comment to explain the usual case of having two parent RDDs.

Streaming constructor which takes JavaSparkContext

It's sometimes helpful to directly pass a JavaSparkContext,
and take advantage of the various constructors available for that.

Fix exit status in PySpark unit tests; fix/optimize PySpark's RDD.take()

Add spark.executor.memory to differentiate executor memory from spark-shell

RDDInfo available from SparkContext

Once we find a split with no block, we don't have to look for more.

Fix createActorSystem not actually using the systemName parameter.

Tests for DAGScheduler

Conflicts:
	core/src/main/scala/spark/scheduler/DAGScheduler.scala

This meant all system names were "spark", which worked, but didn't
lead to the most intuitive log output.

This fixes createActorSystem to use the passed system name, and
refactors Master/Worker to encapsulate their system/actor names
instead of having the clients guess at them.

Note that the driver system name, "spark", is left as is, and is
still repeated a few times, but that seems like a separate issue.