SPARK-1104: kill Process in workerThread of ExecutorRunner

As reported in https://spark-project.atlassian.net/browse/SPARK-1104

By @pwendell: "Sometimes due to large shuffles executors will take a long time shutting down. In particular this can happen if large numbers of shuffle files are around (this will be alleviated by SPARK-1103, but nonetheless...).

The symptom is you have DEAD workers sitting around in the UI and the existing workers keep trying to re-register but can't because they've been assumed dead."

In this patch, I add lines in the handler of InterruptedException in workerThread of executorRunner, so that the process.destroy() and process.waitFor() can only block the workerThread instead of blocking the worker Actor...

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analysis: process.destroy() is a blocking method, i.e. it only returns when all shutdownHook threads return...so calling it in Worker thread will make Worker block for a long while....

about what will happen on the shutdown hooks when the JVM process is killed: http://www.tutorialspoint.com/java/lang/runtime_addshutdownhook.htm

Author: CodingCat <zhunansjtu@gmail.com>

Closes #35 from CodingCat/SPARK-1104 and squashes the following commits:

85767da [CodingCat] add null checking and remove unnecessary killProce
3107aeb [CodingCat] address Aaron's comments
eb615ba [CodingCat] kill the process when the error happens
0accf2f [CodingCat] set process to null after killed it
1d511c8 [CodingCat] kill Process in workerThread
SPARK-1438 RDD.sample() make seed param optional

copying form previous pull request https://github.com/apache/spark/pull/462

Its probably better to let the underlying language implementation take care of the default . This was easier to do with python as the default value for seed in random and numpy random is None.

In Scala/Java side it might mean propagating an Option or null(oh no!) down the chain until where the Random is constructed. But, looks like the convention in some other methods was to use System.nanoTime. So, followed that convention.

Conflict with overloaded method in sql.SchemaRDD.sample which also defines default params.
sample(fraction, withReplacement=false, seed=math.random)
Scala does not allow more than one overloaded to have default params. I believe the author intended to override the RDD.sample method and not overload it. So, changed it.

If backward compatible is important, 3 new method can be introduced (without default params) like this
sample(fraction)
sample(fraction, withReplacement)
sample(fraction, withReplacement, seed)

Added some tests for the scala RDD takeSample method.

Author: Arun Ramakrishnan <smartnut007@gmail.com>

This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>

Closes #477 from smartnut007/master and squashes the following commits:

07bb06e [Arun Ramakrishnan] SPARK-1438 fixing more space formatting issues
b9ebfe2 [Arun Ramakrishnan] SPARK-1438 removing redundant import of random in python rddsampler
8d05b1a [Arun Ramakrishnan] SPARK-1438 RDD . Replace System.nanoTime with a Random generated number. python: use a separate instance of Random instead of seeding language api global Random instance.
69619c6 [Arun Ramakrishnan] SPARK-1438 fix spacing issue
0c247db [Arun Ramakrishnan] SPARK-1438 RDD language apis to support optional seed in RDD methods sample/takeSample
[SPARK-1592][streaming] Automatically remove streaming input blocks

The raw input data is stored as blocks in BlockManagers. Earlier they were cleared by cleaner ttl. Now since streaming does not require cleaner TTL to be set, the block would not get cleared. This increases up the Spark's memory usage, which is not even accounted and shown in the Spark storage UI. It may cause the data blocks to spill over to disk, which eventually slows down the receiving of data (persisting to memory become bottlenecked by writing to disk).

The solution in this PR is to automatically remove those blocks. The mechanism to keep track of which BlockRDDs (which has presents the raw data blocks as a RDD) can be safely cleared already exists. Just use it to explicitly remove blocks from BlockRDDs.

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #512 from tdas/block-rdd-unpersist and squashes the following commits:

d25e610 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
5f46d69 [Tathagata Das] Merge remote-tracking branch 'apache/master' into block-rdd-unpersist
2c320cd [Tathagata Das] Updated configuration with spark.streaming.unpersist setting.
2d4b2fd [Tathagata Das] Automatically removed input blocks
[SQL] Add support for parsing indexing into arrays in SQL.

Author: Michael Armbrust <michael@databricks.com>

Closes #518 from marmbrus/parseArrayIndex and squashes the following commits:

afd2d6b [Michael Armbrust] 100 chars
c3d6026 [Michael Armbrust] Add support for parsing indexing into arrays in SQL.
Spark 1489 Fix the HistoryServer view acls

This allows the view acls set by the user to be enforced by the history server.  It also fixes filters being applied properly.

Author: Thomas Graves <tgraves@apache.org>

Closes #509 from tgravescs/SPARK-1489 and squashes the following commits:

869c186 [Thomas Graves] change to either acls enabled or disabled
0d8333c [Thomas Graves] Add history ui policy to allow acls to either use application set, history server force acls on, or off
65148b5 [Thomas Graves] SPARK-1489 Fix the HistoryServer view acls
[SPARK-1510] Spark Streaming metrics source for metrics system

This pulls in changes made by @jerryshao in https://github.com/apache/spark/pull/424 and merges with the master.

Author: jerryshao <saisai.shao@intel.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #545 from tdas/streaming-metrics and squashes the following commits:

034b443 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into streaming-metrics
fb3b0a5 [jerryshao] Modify according master update
21939f5 [jerryshao] Style changes according to style check error
976116b [jerryshao] Add StreamSource in StreamingContext for better monitoring through metrics system
[SPARK-1615] Synchronize accesses to the LiveListenerBus' event queue

Original poster is @zsxwing, who reported this bug in #516.

Much of SparkListenerSuite relies on LiveListenerBus's `waitUntilEmpty()` method. As the name suggests, this waits until the event queue is empty. However, the following race condition could happen:

(1) We dequeue an event
(2) The queue is empty, we return true (even though the event has not been processed)
(3) The test asserts something assuming that all listeners have finished executing (and fails)
(4) The listeners receive and process the event

This PR makes (1) and (4) atomic by synchronizing around it. To do that, however, we must avoid using `eventQueue.take`, which is blocking and will cause a deadlock if we synchronize around it. As a workaround, we use the non-blocking `eventQueue.poll` + a semaphore to provide the same semantics.

This has been a possible race condition for a long time, but for some reason we've never run into it.

Author: Andrew Or <andrewor14@gmail.com>

Closes #544 from andrewor14/stage-info-test-fix and squashes the following commits:

3cbe40c [Andrew Or] Merge github.com:apache/spark into stage-info-test-fix
56dbbcb [Andrew Or] Check if event is actually added before releasing semaphore
eb486ae [Andrew Or] Synchronize accesses to the LiveListenerBus' event queue
[SPARK-986]: Job cancelation for PySpark

* Additions to the PySpark API to cancel jobs
* Monitor Thread in PythonRDD to kill Python workers if a task is interrupted

Author: Ahir Reddy <ahirreddy@gmail.com>

Closes #541 from ahirreddy/python-cancel and squashes the following commits:

dfdf447 [Ahir Reddy] Changed success -> completed and made logging message clearer
6c860ab [Ahir Reddy] PR Comments
4b4100a [Ahir Reddy] Success flag
adba6ed [Ahir Reddy] Destroy python workers
27a2f8f [Ahir Reddy] Start the writer thread...
d422f7b [Ahir Reddy] Remove unnecesssary vals
adda337 [Ahir Reddy] Busy wait on the ocntext.interrupted flag, and then kill the python worker
d9e472f [Ahir Reddy] Revert "removed unnecessary vals"
5b9cae5 [Ahir Reddy] removed unnecessary vals
07b54d9 [Ahir Reddy] Fix canceling unit test
8ae9681 [Ahir Reddy] Don't interrupt worker
7722342 [Ahir Reddy] Monitor Thread for python workers
db04e16 [Ahir Reddy] Added canceling api to PySpark
SPARK-1584: Upgrade Flume dependency to 1.4.0

Updated the Flume dependency in the maven pom file and the scala build file.

Author: tmalaska <ted.malaska@cloudera.com>

Closes #507 from tmalaska/master and squashes the following commits:

79492c8 [tmalaska] excluded all thrift
159c3f1 [tmalaska] fixed the flume pom file issues
5bf56a7 [tmalaska] Upgrade flume version
SPARK-1586 Windows build fixes

Unfortunately, this is not exhaustive - particularly hive tests still fail due to path issues.

Author: Mridul Muralidharan <mridulm80@apache.org>

This patch had conflicts when merged, resolved by
Committer: Matei Zaharia <matei@databricks.com>

Closes #505 from mridulm/windows_fixes and squashes the following commits:

ef12283 [Mridul Muralidharan] Move to org.apache.commons.lang3 for StringEscapeUtils. Earlier version was buggy appparently
cdae406 [Mridul Muralidharan] Remove leaked changes from > 2G fix branch
3267f4b [Mridul Muralidharan] Fix build failures
35b277a [Mridul Muralidharan] Fix Scalastyle failures
bc69d14 [Mridul Muralidharan] Change from hardcoded path separator
10c4d78 [Mridul Muralidharan] Use explicit encoding while using getBytes
1337abd [Mridul Muralidharan] fix classpath while running in windows