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.