spark-shell intends to set MASTER automatically if we do not provide the option when we start the shell , but there's a problem. 
The condition is "if [[ "x" != "x$SPARK_MASTER_IP" && "y" != "y$SPARK_MASTER_PORT" ]];" we sure will set SPARK_MASTER_IP explicitly, the SPARK_MASTER_PORT option, however, we probably do not set just using spark default port 7077. So if we do not set SPARK_MASTER_PORT, the condition will never be true. We should just use default port if users do not set port explicitly I think.

remove "-XX:+UseCompressedStrings" option from tuning guide since jdk7 no longer supports this.

Rename VertexID -> VertexId in GraphX

Fixed the flaky tests by making SparkConf not serializable

SparkConf was being serialized with CoGroupedRDD and Aggregator, which somehow caused OptionalJavaException while being deserialized as part of a ShuffleMapTask. SparkConf should not even be serializable (according to conversation with Matei). This change fixes that.

@mateiz @pwendell

Fixed SVDPlusPlusSuite in Maven build.

This should go into 0.9.0 also.

Changed SparkConf to not be serializable. And also fixed unit-test log paths in log4j.properties of external modules.

Additional edits for clarity in the graphx programming guide.

Added an overview of the Graph and GraphOps functions and fixed numerous typos.

Describe caching and uncaching in GraphX programming guide

Don't clone records for text files

Add GraphX dependency to examples/pom.xml

Deprecate rather than remove old combineValuesByKey function

API doc update & make Broadcast public

In #413 Broadcast was mistakenly made private[spark]. I changed it to public again. Also exposing id in public given the R frontend requires that.

Copied some of the documentation from the programming guide to API Doc for Broadcast and Accumulator.

This should be cherry picked into branch-0.9 as well for 0.9.0 release.

Maintain Serializable API compatibility by reverting back to java.io.Serializable for Broadcast and Accumulator.

Note that previously Broadcast class was accidentally marked as private[spark]. It needs to be public
for broadcast variables to work. Also exposing the broadcast varaible id.

Improving the graphx-programming-guide

This PR will track a few minor improvements to the content and formatting of the graphx-programming-guide.

Add missing header files

Removed unnecessary DStream operations and updated docs

Removed StreamingContext.registerInputStream and registerOutputStream - they were useless. InputDStream has been made to register itself, and just registering a DStream as output stream cause RDD objects to be created but the RDDs will not be computed at all.. Also made DStream.register() private[streaming] for the same reasons.

Updated docs, specially added package documentation for streaming package.

Also, changed NetworkWordCount's input storage level to use MEMORY_ONLY, replication on the local machine causes warning messages (as replication fails) which is scary for a new user trying out his/her first example.

Conflicts:
	streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala

Enable compression by default for spills

Removed StreamingContext.registerInputStream and registerOutputStream - they were useless as InputDStream has been made to register itself. Also made DStream.register() private[streaming] - not useful to expose the confusing function. Updated a lot of documentation.

Add Naive Bayes to Python MLlib, and some API fixes

- Added a Python wrapper for Naive Bayes
- Updated the Scala Naive Bayes to match the style of our other
  algorithms better and in particular make it easier to call from Java
  (added builder pattern, removed default value in train method)
- Updated Python MLlib functions to not require a SparkContext; we can
  get that from the RDD the user gives
- Added a toString method in LabeledPoint
- Made the Python MLlib tests run as part of run-tests as well (before
  they could only be run individually through each file)