SPARK-1119 and other build improvements

1. Makes assembly and examples jar naming consistent in maven/sbt.
2. Updates make-distribution.sh to use Maven and fixes some bugs.
3. Updates the create-release script to call make-distribution script.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #502 from pwendell/make-distribution and squashes the following commits:

1a97f0d [Patrick Wendell] SPARK-1119 and other build improvements
SPARK-1583: Fix a bug that using java.util.HashMap by mistake

JIRA: https://issues.apache.org/jira/browse/SPARK-1583

Does anyone know why using `java.util.HashMap` rather than `mutable.HashMap`? Some methods of `java.util.HashMap` are not generics and compiler can not help us find similar problems.

Author: zsxwing <zsxwing@gmail.com>

Closes #500 from zsxwing/SPARK-1583 and squashes the following commits:

7bfd74d [zsxwing] SPARK-1583: Fix a bug that using java.util.HashMap by mistake
SPARK-1572 Don't kill Executor if PythonRDD fails while computing parent

Previously, the behavior was that if the parent RDD threw any exception other than IOException or FileNotFoundException (which is quite possible for Hadoop input sources), the entire Executor would crash, because the default thread a uncaught exception handler calls System.exit().

This patch avoids two related issues:

  1. Always catch exceptions in this reader thread.
  2. Don't mask readerException when Python throws an EOFError
     after worker.shutdownOutput() is called.

Author: Aaron Davidson <aaron@databricks.com>

Closes #486 from aarondav/pyspark and squashes the following commits:

fbb11e9 [Aaron Davidson] Make sure FileNotFoundExceptions are handled same as before
b9acb3e [Aaron Davidson] SPARK-1572 Don't kill Executor if PythonRDD fails while computing parent
Honor default fs name when initializing event logger.

This is related to SPARK-1459 / PR #375. Without this fix,
FileLogger.createLogDir() may try to create the log dir on
HDFS, while createWriter() will try to open the log file on
the local file system, leading to interesting errors and
confusion.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #450 from vanzin/event-file-2 and squashes the following commits:

592cdb3 [Marcelo Vanzin] Honor default fs name when initializing event logger.
SPARK-1582 Invoke Thread.interrupt() when cancelling jobs

Sometimes executor threads are blocked waiting for IO or monitors, and the current implementation of job cancellation may never recover these threads. By simply invoking Thread.interrupt() during cancellation, we can often safely unblock the threads and use them for subsequent work.

Note that this feature must remain optional for now because of a bug in HDFS where Thread.interrupt() may cause nodes to be marked as permanently dead (as the InterruptedException is reinterpreted as an IOException during communication with some node).

Author: Aaron Davidson <aaron@databricks.com>

Closes #498 from aarondav/cancel and squashes the following commits:

e52b829 [Aaron Davidson] Don't use job.properties when null
82f78bb [Aaron Davidson] Update DAGSchedulerSuite
b67f472 [Aaron Davidson] Add comment on why interruptOnCancel is in setJobGroup
4cb9fd6 [Aaron Davidson] SPARK-1582 Invoke Thread.interrupt() when cancelling jobs
[SPARK-1540] Add an optional Ordering parameter to PairRDDFunctions.

In https://issues.apache.org/jira/browse/SPARK-1540 we'd like to look at Spark's API to see if we can take advantage of Comparable keys in more places, which will make external spilling more efficient. This PR is a first step towards that that shows how to pass an Ordering when available and still continue functioning otherwise. It does this using a new implicit parameter with a default value of null.

The API is currently only in Scala -- in Java we'd have to add new versions of mapToPair and such that take a Comparator, or a new method to add a "type hint" to an RDD. We can address those later though.

Unfortunately requiring all keys to be Comparable would not work without requiring RDDs in general to contain only Comparable types. The reason is that methods such as distinct() and intersection() do a shuffle, but should be usable on RDDs of any type. So ordering will have to remain an optimization for the types that can be ordered. I think this isn't a horrible outcome though because one of the nice things about Spark's API is that it works on objects of *any* type, without requiring you to specify a schema or implement Writable or stuff like that.

Author: Matei Zaharia <matei@databricks.com>

This patch had conflicts when merged, resolved by
Committer: Reynold Xin <rxin@apache.org>

Closes #487 from mateiz/ordered-keys and squashes the following commits:

bd565f6 [Matei Zaharia] Pass an Ordering to only one version of groupBy because the Scala language spec doesn't allow having an optional parameter on all of them (this was only compiling in Scala 2.10 due to a bug).
4629965 [Matei Zaharia] Add tests for other versions of groupBy
3beae85 [Matei Zaharia] Added a test for implicit orderings
80b7a3b [Matei Zaharia] Add an optional Ordering parameter to PairRDDFunctions.
[Hot Fix #469] Fix flaky test in SparkListenerSuite

The two modified tests may fail if the race condition does not bid in our favor...

Author: Andrew Or <andrewor14@gmail.com>

Closes #516 from andrewor14/stage-info-test-fix and squashes the following commits:

b4b6100 [Andrew Or] Add/replace missing waitUntilEmpty() calls to listener bus
Update Java api for setJobGroup with interruptOnCancel

Also adds a unit test.

Author: Aaron Davidson <aaron@databricks.com>

Closes #522 from aarondav/cancel2 and squashes the following commits:

565c253 [Aaron Davidson] Update Java api for setJobGroup with interruptOnCancel
65b33d8 [Aaron Davidson] Add unit test for Thread interruption on cancellation
Mark all fields of EdgePartition, Graph, and GraphOps transient

These classes are only serializable to work around closure capture, so their fields should all be marked `@transient` to avoid wasteful serialization.

This PR supersedes apache/spark#519 and fixes the same bug.

Author: Ankur Dave <ankurdave@gmail.com>

Closes #520 from ankurdave/graphx-transient and squashes the following commits:

6431760 [Ankur Dave] Mark all fields of EdgePartition, Graph, and GraphOps `@transient`
SPARK-1589: Fix the incorrect compare

JIRA: https://issues.apache.org/jira/browse/SPARK-1589

Author: zsxwing <zsxwing@gmail.com>

Closes #508 from zsxwing/SPARK-1589 and squashes the following commits:

570c67a [zsxwing] SPARK-1589: Fix the incorrect compare
[Fix #79] Replace Breakable For Loops By While Loops

Author: Sandeep <sandeep@techaddict.me>

Closes #503 from techaddict/fix-79 and squashes the following commits:

e3f6746 [Sandeep] Style changes
07a4f6b [Sandeep] for loop to While loop
0a6d8e9 [Sandeep] Breakable for loop to While loop
SPARK-1587 Fix thread leak

mvn test fails (intermittently) due to thread leak - since scalatest runs all tests in same vm.

Author: Mridul Muralidharan <mridulm80@apache.org>

Closes #504 from mridulm/resource_leak_fixes and squashes the following commits:

a5d10d0 [Mridul Muralidharan] Prevent thread leaks while running tests : cleanup all threads when SparkContext.stop is invoked. Causes tests to fail
7b5e19c [Mridul Muralidharan] Prevent NPE while running tests
SPARK-1601 & SPARK-1602: two bug fixes related to cancellation

This should go into 1.0 since it would return wrong data when the bug happens (which is pretty likely if cancellation is used). Test case attached.

1. Do not put partially executed partitions into cache (in task killing).

2. Iterator returned by CacheManager#getOrCompute was not an InterruptibleIterator, and was thus leading to uninterruptible jobs.

Thanks @aarondav and @ahirreddy for reporting and helping debug.

Author: Reynold Xin <rxin@apache.org>

Closes #521 from rxin/kill and squashes the following commits:

401033f [Reynold Xin] Merge branch 'master' of https://git-wip-us.apache.org/repos/asf/spark into kill
7a7bdd2 [Reynold Xin] Add a new line in the end of JobCancellationSuite.scala.
35cd9f7 [Reynold Xin] Fixed a bug that partially executed partitions can be put into cache (in task killing).