- Don't include trailing $'s in class names of Scala objects
- Report errors using logError instead of printStackTrace

Changed printlns to log statements and fixed a bug in run that was causing it to fail on a Mesos cluster

HTTP server instead of a shared (NFS) file system.

Added fork()/join() operations for SparkContext, as well as corresponding changes to MesosScheduler to support multiple ParallelOperations.

- Added SampledRDD, SplitRDD and CartesianRDD
- Made Split a class rather than a type parameter
- Added numCores() to Scheduler to help set default level of parallelism

MesosScheduler.scala: formatted the slaveOffer() output to include the serialized task size
RDD.scala: added support for aggregating RDDs on a per-split basis
(aggregateSplit()) as well as for sampling without replacement (sample())

as Python on GitHub :|.

all results when :silent is enabled, so that it is easier to work with
large arrays in Spark. (The string version of an array of numbers might
not fit in memory even though the array itself does.)

Fixed a bug where we would incorrectly decide we've finished a parallel operation if Mesos tells us a task is finished twice

that unit tests can run successfully.

in general through a conf/spark-env.sh script.

Conflicts:
	src/scala/spark/HdfsFile.scala
	src/scala/spark/NexusScheduler.scala
	src/test/spark/repl/ReplSuite.scala

This also means that parallel arrays now get all the functionality files
used to have (filter, map, reduce, cache, etc).