[SPARK-4498][core] Don't transition ExecutorInfo to RUNNING until Driver adds Executor

The ExecutorInfo only reaches the RUNNING state if the Driver is alive to send the ExecutorStateChanged message to master.  Else, appInfo.resetRetryCount() is never called and failing Executors will eventually exceed ApplicationState.MAX_NUM_RETRY, resulting in the application being removed from the master's accounting.

Author: Mark Hamstra <markhamstra@gmail.com>

Closes #3550 from markhamstra/SPARK-4498 and squashes the following commits:

8f543b1 [Mark Hamstra] Don't transition ExecutorInfo to RUNNING until Executor is added by Driver
[SPARK-4085] Propagate FetchFailedException when Spark fails to read local shuffle file.

cc aarondav kayousterhout pwendell

This should go into 1.2?

Author: Reynold Xin <rxin@databricks.com>

Closes #3579 from rxin/SPARK-4085 and squashes the following commits:

255b4fd [Reynold Xin] Updated test.
f9814d9 [Reynold Xin] Code review feedback.
2afaf35 [Reynold Xin] [SPARK-4085] Propagate FetchFailedException when Spark fails to read local shuffle file.

(cherry picked from commit 1826372d0a1bc80db9015106dd5d2d155ada33f5)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
[SPARK-4711] [mllib] [docs] Programming guide advice on choosing optimizer

I have heard requests for the docs to include advice about choosing an optimization method. The programming guide could include a brief statement about this (so the user does not have to read the whole optimization section).

CC: mengxr

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #3569 from jkbradley/lr-doc and squashes the following commits:

654aeb5 [Joseph K. Bradley] updated section header for mllib-optimization
5035ad0 [Joseph K. Bradley] updated based on review
94f6dec [Joseph K. Bradley] Updated linear methods and optimization docs with quick advice on choosing an optimization method

(cherry picked from commit 27ab0b8a03b711e8d86b6167df833f012205ccc7)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
[SPARK-4580] [SPARK-4610] [mllib] [docs] Documentation for tree ensembles + DecisionTree API fix

Major changes:
* Added programming guide sections for tree ensembles
* Added examples for tree ensembles
* Updated DecisionTree programming guide with more info on parameters
* **API change**: Standardized the tree parameter for the number of classes (for classification)

Minor changes:
* Updated decision tree documentation
* Updated existing tree and tree ensemble examples
 * Use train/test split, and compute test error instead of training error.
 * Fixed decision_tree_runner.py to actually use the number of classes it computes from data. (small bug fix)

Note: I know this is a lot of lines, but most is covered by:
* Programming guide sections for gradient boosting and random forests.  (The changes are probably best viewed by generating the docs locally.)
* New examples (which were copied from the programming guide)
* The "numClasses" renaming

I have run all examples and relevant unit tests.

CC: mengxr manishamde codedeft

Author: Joseph K. Bradley <joseph@databricks.com>
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>

Closes #3461 from jkbradley/ensemble-docs and squashes the following commits:

70a75f3 [Joseph K. Bradley] updated forest vs boosting comparison
d1de753 [Joseph K. Bradley] Added note about toString and toDebugString for DecisionTree to migration guide
8e87f8f [Joseph K. Bradley] Combined GBT and RandomForest guides into one ensembles guide
6fab846 [Joseph K. Bradley] small fixes based on review
b9f8576 [Joseph K. Bradley] updated decision tree doc
375204c [Joseph K. Bradley] fixed python style
2b60b6e [Joseph K. Bradley] merged Java RandomForest examples into 1 file.  added header.  Fixed small bug in same example in the programming guide.
706d332 [Joseph K. Bradley] updated python DT runner to print full model if it is small
c76c823 [Joseph K. Bradley] added migration guide for mllib
abe5ed7 [Joseph K. Bradley] added examples for random forest in Java and Python to examples folder
07fc11d [Joseph K. Bradley] Renamed numClassesForClassification to numClasses everywhere in trees and ensembles. This is a breaking API change, but it was necessary to correct an API inconsistency in Spark 1.1 (where Python DecisionTree used numClasses but Scala used numClassesForClassification).
cdfdfbc [Joseph K. Bradley] added examples for GBT
6372a2b [Joseph K. Bradley] updated decision tree examples to use random split.  tested all of them.
ad3e695 [Joseph K. Bradley] added gbt and random forest to programming guide.  still need to update their examples

(cherry picked from commit 657a88835d8bf22488b53d50f75281d7dc32442e)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
[Release] Correctly translate contributors name in release notes

This commit involves three main changes:

(1) It separates the translation of contributor names from the
generation of the contributors list. This is largely motivated
by the Github API limit; even if we exceed this limit, we should
at least be able to proceed manually as before. This is why the
translation logic is abstracted into its own script
translate-contributors.py.

(2) When we look for candidate replacements for invalid author
names, we should look for the assignees of the associated JIRAs
too. As a result, the intermediate file must keep track of these.

(3) This provides an interactive mode with which the user can
sit at the terminal and manually pick the candidate replacement
that he/she thinks makes the most sense. As before, there is a
non-interactive mode that picks the first candidate that the
script considers "valid."

TODO: We should have a known_contributors file that stores
known mappings so we don't have to go through all of this
translation every time. This is also valuable because some
contributors simply cannot be automatically translated.

Conflicts:
	.gitignore