Change defaultPartitioner to use upstream split size.

Previously it used the SparkContext.defaultParallelism, which occassionally
ended up being a very bad guess. Looking at upstream RDDs seems to make
better use of the context.

Also sorted the upstream RDDs by partition size first, as if we have
a hugely-partitioned RDD and tiny-partitioned RDD, it is unlikely
we want the resulting RDD to be tiny-partitioned.
Update default.parallelism docs, have StandaloneSchedulerBackend use it.

Only brand new RDDs (e.g. parallelize and makeRDD) now use default
parallelism, everything else uses their largest parent's partitioner
or partition size.
Remove fileServerSuite.txt.
Tweak test names.
Update more javadocs.
Merge branch 'master' into bettersplits

Conflicts:
	core/src/main/scala/spark/RDD.scala
	core/src/main/scala/spark/scheduler/cluster/StandaloneSchedulerBackend.scala
	core/src/test/scala/spark/ShuffleSuite.scala
Use default parallelism if its set.
Merge pull request #459 from stephenh/bettersplits

Change defaultPartitioner to use upstream split size.
Get spark.default.paralellism on each call to defaultPartitioner,
instead of only once, in case the user changes it across Spark uses
Change tabs to spaces
Disable remote lifecycle logging from Akka.

This changes the default setting to `off` for remote lifecycle events. When this is on, it is very chatty at the INFO level. It also prints out several ERROR messages sometimes when sc.stop() is called.
Merge pull request #498 from pwendell/shutup-akka

Disable remote lifecycle logging from Akka.
Merge branch 'master' of github.com:mesos/spark
Use a single setting for disabling API doc build
Change doc color scheme slightly for Spark 0.7 (to differ from 0.6)
Use public method sparkContext instead of protected sc in streaming examples
Fix compile error
Add a config property for Akka lifecycle event logging
Some tweaks to docs
Set spark.deploy.spreadOut to true by default in 0.7 (improves locality)