Removed XYZFunctions and added XYZUtils as a common Scala and Java interface for creating XYZ streams.

Conflicts:
	examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java
	streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
	streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
	streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
	streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
	streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala

Changed JavaStreamingContextWith*** to ***Function in streaming.api.java.*** package. Also fixed packages of Flume and MQTT tests.

Quiet ERROR-level Akka Logs

This fixes an issue I've seen where akka logs a bunch of things at ERROR level when connecting to a standalone cluster, even in the normal case. I noticed that even when lifecycle logging was disabled, the netty code inside of akka still logged away via akka's EndpointWriter class. There are also some other log streams that I think are new in akka 2.2.1 that I've disabled.

Finally, I added some better logging to the standalone client. This makes it more clear when a connection failure occurs what is going on. Previously it never explicitly said if a connection attempt had failed.

The commit messages here have some more detail.

Removing SPARK_EXAMPLES_JAR in the code

This re-writes all of the examples to use the `SparkContext.jarOfClass` mechanism for loading the examples jar. This necessary for environments like YARN and the Standalone mode where example programs will be submit from inside the cluster rather than at the client using `./spark-example`.

This still leaves SPARK_EXAMPLES_JAR in place in the shell scripts for setting up the classpath if `./spark-example` is run.

Fall back to zero-arg constructor for Serializer initialization if there is no constructor that accepts SparkConf.

This maintains backward compatibility with older serializers implemented by users.

Fall back to zero-arg constructor for Serializer initialization if there is no constructor that accepts SparkConf.
This maintains backward compatibility with older serializers implemented by users.

Without these it's a bit less clear what's going on for the user.

One thing I realize when doing this is that akka itself actually retries
the initial association. So the retry we currently have is redundant with
akka's.

I noticed when connecting to a standalone cluster Spark gives a bunch
of Akka ERROR logs that make it seem like something is failing.

This patch does two things:

1. Akka dead letter logging is turned on/off according to the existing
   lifecycle spark property.
2. We explicitly silence akka's EndpointWriter log in log4j. This is necessary
   because for some reason that log doesn't pick up on the lifecycle
   logging settings. After a few hours of debugging this was the only solution
   I found that worked.

standard Naive Bayes classifier

Has implemented the standard Naive Bayes classifier. This is an updated version of #288, which is closed because of misoperations.

SPARK-1002: Remove Binaries from Spark Source

This adds a few changes on top of the work by @scrapcodes.

Conflicts:
	core/src/test/scala/org/apache/spark/DriverSuite.scala
	docs/python-programming-guide.md

Closes #316

Modify spark on yarn to create SparkConf process

Spark-915 segregate scripts

Yarn refactor