[SQL] SPARK-1372 Support for caching and uncaching tables in a SQLContext.

This doesn't yet support different databases in Hive (though you can probably workaround this by calling `USE <dbname>`).  However, given the time constraints for 1.0 I think its probably worth including this now and extending the functionality in the next release.

Author: Michael Armbrust <michael@databricks.com>

Closes #282 from marmbrus/cacheTables and squashes the following commits:

83785db [Michael Armbrust] Support for caching and uncaching tables in a SQLContext.
[SPARK-1342] Scala 2.10.4

Just a Scala version increment

Author: Mark Hamstra <markhamstra@gmail.com>

Closes #259 from markhamstra/scala-2.10.4 and squashes the following commits:

fbec547 [Mark Hamstra] [SPARK-1342] Bumped Scala version to 2.10.4
[Spark-1134] only call ipython if no arguments are given; remove IPYTHONOPTS from call

see comments on Pull Request https://github.com/apache/spark/pull/38
(i couldn't figure out how to modify an existing pull request, so I'm hoping I can withdraw that one and replace it with this one.)

Author: Diana Carroll <dcarroll@cloudera.com>

Closes #227 from dianacarroll/spark-1134 and squashes the following commits:

ffe47f2 [Diana Carroll] [spark-1134] remove ipythonopts from ipython command
b673bf7 [Diana Carroll] Merge branch 'master' of github.com:apache/spark
0309cf9 [Diana Carroll] SPARK-1134 bug with ipython prevents non-interactive use with spark; only call ipython if no command line arguments were supplied
Revert "[Spark-1134] only call ipython if no arguments are given; remove IPYTHONOPTS from call"

This reverts commit afb5ea62786e3ca055e247176def3e7ecf0d2c9d.
MLI-1 Decision Trees

Joint work with @hirakendu, @etrain, @atalwalkar and @harsha2010.

Key features:
+ Supports binary classification and regression
+ Supports gini, entropy and variance for information gain calculation
+ Supports both continuous and categorical features

The algorithm has gone through several development iterations over the last few months leading to a highly optimized implementation. Optimizations include:

1. Level-wise training to reduce passes over the entire dataset.
2. Bin-wise split calculation to reduce computation overhead.
3. Aggregation over partitions before combining to reduce communication overhead.

Author: Manish Amde <manish9ue@gmail.com>
Author: manishamde <manish9ue@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes #79 from manishamde/tree and squashes the following commits:

1e8c704 [Manish Amde] remove numBins field in the Strategy class
7d54b4f [manishamde] Merge pull request #4 from mengxr/dtree
f536ae9 [Xiangrui Meng] another pass on code style
e1dd86f [Manish Amde] implementing code style suggestions
62dc723 [Manish Amde] updating javadoc and converting helper methods to package private to allow unit testing
201702f [Manish Amde] making some more methods private
f963ef5 [Manish Amde] making methods private
c487e6a [manishamde] Merge pull request #1 from mengxr/dtree
24500c5 [Xiangrui Meng] minor style updates
4576b64 [Manish Amde] documentation and for to while loop conversion
ff363a7 [Manish Amde] binary search for bins and while loop for categorical feature bins
632818f [Manish Amde] removing threshold for classification predict method
2116360 [Manish Amde] removing dummy bin calculation for categorical variables
6068356 [Manish Amde] ensuring num bins is always greater than max number of categories
62c2562 [Manish Amde] fixing comment indentation
ad1fc21 [Manish Amde] incorporated mengxr's code style suggestions
d1ef4f6 [Manish Amde] more documentation
794ff4d [Manish Amde] minor improvements to docs and style
eb8fcbe [Manish Amde] minor code style updates
cd2c2b4 [Manish Amde] fixing code style based on feedback
63e786b [Manish Amde] added multiple train methods for java compatability
d3023b3 [Manish Amde] adding more docs for nested methods
84f85d6 [Manish Amde] code documentation
9372779 [Manish Amde] code style: max line lenght <= 100
dd0c0d7 [Manish Amde] minor: some docs
0dd7659 [manishamde] basic doc
5841c28 [Manish Amde] unit tests for categorical features
f067d68 [Manish Amde] minor cleanup
c0e522b [Manish Amde] updated predict and split threshold logic
b09dc98 [Manish Amde] minor refactoring
6b7de78 [Manish Amde] minor refactoring and tests
d504eb1 [Manish Amde] more tests for categorical features
dbb7ac1 [Manish Amde] categorical feature support
6df35b9 [Manish Amde] regression predict logic
53108ed [Manish Amde] fixing index for highest bin
e23c2e5 [Manish Amde] added regression support
c8f6d60 [Manish Amde] adding enum for feature type
b0e3e76 [Manish Amde] adding enum for feature type
154aa77 [Manish Amde] enums for configurations
733d6dd [Manish Amde] fixed tests
02c595c [Manish Amde] added command line parsing
98ec8d5 [Manish Amde] tree building and prediction logic
b0eb866 [Manish Amde] added logic to handle leaf nodes
80e8c66 [Manish Amde] working version of multi-level split calculation
4798aae [Manish Amde] added gain stats class
dad0afc [Manish Amde] decison stump functionality working
03f534c [Manish Amde] some more tests
0012a77 [Manish Amde] basic stump working
8bca1e2 [Manish Amde] additional code for creating intermediate RDD
92cedce [Manish Amde] basic building blocks for intermediate RDD calculation. untested.
cd53eae [Manish Amde] skeletal framework