Change SVM to use {0,1} labels.
Also add a data validation check to make sure classification labels
are always 0 or 1 and add an appropriate test case.
Fix SVM model and unit test to work with {0,1}.
Also rename validateFuncs to validators.
Specify label format in LogisticRegression.
Adding Linear Regression, and refactoring Ridge Regression.
Centralizing linear data generator and mllib regression tests to use it.
Fixing typos in Java tests, and addressing alignment issues.
Center & scale variables in Ridge, Lasso.
Also add a unit test that checks if ridge regression lowers
cross-validation error.
Add an option to turn off data validation, test it.
Also moves addIntercept to have default true to make it similar
to validateData option
PySpark: implementing subtractByKey(), subtract() and keyBy()
Don't send SIGINT to Py4J gateway subprocess.

This addresses SPARK-885, a usability issue where PySpark's
Java gateway process would be killed if the user hit ctrl-c.

Note that SIGINT still won't cancel the running s

This fix is based on http://stackoverflow.com/questions/5045771
RDD sample() and takeSample() prototypes for PySpark
Fix removed block zero size log reporting
Change build and run instructions to use assemblies

This commit makes Spark invocation saner by using an assembly JAR to
find all of Spark's dependencies instead of adding all the JARs in
lib_managed. It also packages the examples into an assembly and uses
that as SPARK_EXAMPLES_JAR. Finally, it replaces the old "run" script
with two better-named scripts: "run-examples" for examples, and
"spark-class" for Spark internal classes (e.g. REPL, master, etc). This
is also designed to minimize the confusion people have in trying to use
"run" to run their own classes; it's not meant to do that, but now at
least if they look at it, they can modify run-examples to do a decent
job for them.

As part of this, Bagel's examples are also now properly moved to the
examples package instead of bagel.
Fix PySpark for assembly run and include it in dist
Provide more memory for tests
Fix finding of assembly JAR, as well as some pointers to ./run
Find assembly correctly in pyspark
Don't use SPARK_LAUNCH_WITH_SCALA in pyspark
Update Maven build to create assemblies expected by new scripts

This includes the following changes:
- The "assembly" package now builds in Maven by default, and creates an
  assembly containing both hadoop-client and Spark, unlike the old
  BigTop distribution assembly that skipped hadoop-client
- There is now a bigtop-dist package to build the old BigTop assembly
- The repl-bin package is no longer built by default since the scripts
  don't reply on it; instead it can be enabled with -Prepl-bin
- Py4J is now included in the assembly/lib folder as a local Maven repo,
  so that the Maven package can link to it
- run-example now adds the original Spark classpath as well because the
  Maven examples assembly lists spark-core and such as provided
- The various Maven projects add a spark-yarn dependency correctly
Update some build instructions because only sbt assembly and mvn package
are now needed