Better explanation for how to use MIMA excludes.

This patch does a few things:
1. We have a file MimaExcludes.scala exclusively for excludes.
2. The test runner tells users about that file if a test fails.
3. I've added back the excludes used from 0.9->1.0. We should keep
   these in the project as an official audit trail of times where
   we decided to make exceptions.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #937 from pwendell/mima and squashes the following commits:

7ee0db2 [Patrick Wendell] Better explanation for how to use MIMA excludes.
Add landmark-based Shortest Path algorithm to graphx.lib

This is a modified version of apache/spark#10.

Author: Ankur Dave <ankurdave@gmail.com>
Author: Andres Perez <andres@tresata.com>

Closes #933 from ankurdave/shortestpaths and squashes the following commits:

03a103c [Ankur Dave] Style fixes
7a1ff48 [Ankur Dave] Improve ShortestPaths documentation
d75c8fc [Ankur Dave] Remove unnecessary VD type param, and pass through ED
d983fb4 [Ankur Dave] Fix style errors
60ed8e6 [Andres Perez] Add Shortest-path computations to graphx.lib with unit tests.
[SPARK-1553] Alternating nonnegative least-squares

This pull request includes a nonnegative least-squares solver (NNLS) tailored to the kinds of small-scale problems that come up when training matrix factorisation models by alternating nonnegative least-squares (ANNLS).

The method used for the NNLS subproblems is based on the classical method of projected gradients.  There is a modification where, if the set of active constraints has not changed since the last iteration, a conjugate gradient step is considered and possibly rejected in favour of the gradient; this improves convergence once the optimal face has been located.

The NNLS solver is in `org.apache.spark.mllib.optimization.NNLSbyPCG`.

Author: Tor Myklebust <tmyklebu@gmail.com>

Closes #460 from tmyklebu/annls and squashes the following commits:

79bc4b5 [Tor Myklebust] Merge branch 'master' of https://github.com/apache/spark into annls
199b0bc [Tor Myklebust] Make the ctor private again and use the builder pattern.
7fbabf1 [Tor Myklebust] Cleanup matrix math in NNLSSuite.
65ef7f2 [Tor Myklebust] Make ALS's ctor public and remove a couple of "convenience" wrappers.
2d4f3cb [Tor Myklebust] Cleanup.
0cb4481 [Tor Myklebust] Drop the iteration limit from 40k to max(400,20n).
e2a01d1 [Tor Myklebust] Create a workspace object for NNLS to cut down on memory allocations.
b285106 [Tor Myklebust] Clean up NNLS test cases.
9c820b6 [Tor Myklebust] Tweak variable names.
8a1a436 [Tor Myklebust] Describe the problem and add a reference to Polyak's paper.
5345402 [Tor Myklebust] Style fixes that got eaten.
ac673bd [Tor Myklebust] More safeguards against numerical ridiculousness.
c288b6a [Tor Myklebust] Finish moving the NNLS solver.
9a82fa6 [Tor Myklebust] Fix scalastyle moanings.
33bf4f2 [Tor Myklebust] Fix missing space.
89ea0a8 [Tor Myklebust] Hack ALSSuite to support NNLS testing.
f5dbf4d [Tor Myklebust] Teach ALS how to use the NNLS solver.
6cb563c [Tor Myklebust] Tests for the nonnegative least squares solver.
a68ac10 [Tor Myklebust] A nonnegative least-squares solver.
[SPARK-1958] Calling .collect() on a SchemaRDD should call executeCollect() on the underlying query plan.

In cases like `Limit` and `TakeOrdered`, `executeCollect()` makes optimizations that `execute().collect()` will not.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #939 from liancheng/spark-1958 and squashes the following commits:

bdc4a14 [Cheng Lian] Copy rows to present immutable data to users
8250976 [Cheng Lian] Added return type explicitly for public API
192a25c [Cheng Lian] [SPARK-1958] Calling .collect() on a SchemaRDD should call executeCollect() on the underlying query plan.
[SPARK-1995][SQL] system function upper and lower can be supported

I don't know whether it's time to implement system function about string operation in spark sql now.

Author: egraldlo <egraldlo@gmail.com>

Closes #936 from egraldlo/stringoperator and squashes the following commits:

3c6c60a [egraldlo] Add UPPER, LOWER, MAX and MIN into hive parser
ea76d0a [egraldlo] modify the formatting issues
b49f25e [egraldlo] modify the formatting issues
1f0bbb5 [egraldlo] system function upper and lower supported
13d3267 [egraldlo] system function upper and lower supported
Avoid dynamic dispatching when unwrapping Hive data.

This is a follow up of PR #758.

The `unwrapHiveData` function is now composed statically before actual rows are scanned according to the field object inspector to avoid dynamic dispatching cost.

According to the same micro benchmark used in PR #758, this simple change brings slight performance boost: 2.5% for CSV table and 1% for RCFile table.

```
Optimized version:

CSV: 6870 ms, RCFile: 5687 ms
CSV: 6832 ms, RCFile: 5800 ms
CSV: 6822 ms, RCFile: 5679 ms
CSV: 6704 ms, RCFile: 5758 ms
CSV: 6819 ms, RCFile: 5725 ms

Original version:

CSV: 7042 ms, RCFile: 5667 ms
CSV: 6883 ms, RCFile: 5703 ms
CSV: 7115 ms, RCFile: 5665 ms
CSV: 7020 ms, RCFile: 5981 ms
CSV: 6871 ms, RCFile: 5906 ms
```

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #935 from liancheng/staticUnwrapping and squashes the following commits:

c49c70c [Cheng Lian] Avoid dynamic dispatching when unwrapping Hive data.
[SPARK-1817] RDD.zip() should verify partition sizes for each partition
[SPARK-1817] Suppressing Mima warning for ZippedRDD and ZippedPartition