[SPARK-3469] Make sure all TaskCompletionListener are called even with failures

This is necessary because we rely on this callback interface to clean resources up. The old behavior would lead to resource leaks.

Note that this also changes the fault semantics of TaskCompletionListener. Previously failures in TaskCompletionListeners would result in the task being reported immediately. With this change, we report the exception at the end, and the reported exception is a TaskCompletionListenerException that contains all the exception messages.

Author: Reynold Xin <rxin@apache.org>

Closes #2343 from rxin/taskcontext-callback and squashes the following commits:

a3845b2 [Reynold Xin] Mark TaskCompletionListenerException as private[spark].
ac5baea [Reynold Xin] Removed obsolete comment.
aa68ea4 [Reynold Xin] Throw an exception if task completion callback fails.
29b6162 [Reynold Xin] oops compilation failed.
1cb444d [Reynold Xin] [SPARK-3469] Call all TaskCompletionListeners even if some fail.
[SQL][Docs] Update SQL programming guide to show the correct default value of containsNull in an ArrayType

After #1889, the default value of `containsNull` in an `ArrayType` is `true`.

Author: Yin Huai <huai@cse.ohio-state.edu>

Closes #2374 from yhuai/containsNull and squashes the following commits:

dc609a3 [Yin Huai] Update the SQL programming guide to show the correct default value of containsNull in an ArrayType (the default value is true instead of false).
SPARK-3470 [CORE] [STREAMING] Add Closeable / close() to Java context objects

...  that expose a stop() lifecycle method. This doesn't add `AutoCloseable`, which is Java 7+ only. But it should be possible to use try-with-resources on a `Closeable` in Java 7, as long as the `close()` does not throw a checked exception, and these don't. Q.E.D.

Author: Sean Owen <sowen@cloudera.com>

Closes #2346 from srowen/SPARK-3470 and squashes the following commits:

612c21d [Sean Owen] Add Closeable / close() to Java context objects that expose a stop() lifecycle method
Proper indent for the previous commit.
[SQL] [Docs] typo fixes

* Fixed random typo
* Added in missing description for DecimalType

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #2367 from nchammas/patch-1 and squashes the following commits:

aa528be [Nicholas Chammas] doc fix for SQL DecimalType
3247ac1 [Nicholas Chammas] [SQL] [Docs] typo fixes
[SPARK-3481][SQL] Removes the evil MINOR HACK

This is a follow up of #2352. Now we can finally remove the evil "MINOR HACK", which covered up the eldest bug in the history of Spark SQL (see details [here](https://github.com/apache/spark/pull/2352#issuecomment-55440621)).

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

Closes #2377 from liancheng/remove-evil-minor-hack and squashes the following commits:

0869c78 [Cheng Lian] Removes the evil MINOR HACK
[SPARK-3294][SQL] Eliminates boxing costs from in-memory columnar storage

This is a major refactoring of the in-memory columnar storage implementation, aims to eliminate boxing costs from critical paths (building/accessing column buffers) as much as possible. The basic idea is to refactor all major interfaces into a row-based form and use them together with `SpecificMutableRow`. The difficult part is how to adapt all compression schemes, esp. `RunLengthEncoding` and `DictionaryEncoding`, to this design. Since in-memory compression is disabled by default for now, and this PR should be strictly better than before no matter in-memory compression is enabled or not, maybe I'll finish that part in another PR.

**UPDATE** This PR also took the chance to optimize `HiveTableScan` by

1. leveraging `SpecificMutableRow` to avoid boxing cost, and
1. building specific `Writable` unwrapper functions a head of time to avoid per row pattern matching and branching costs.

TODO

- [x] Benchmark
- [ ] ~~Eliminate boxing costs in `RunLengthEncoding`~~ (left to future PRs)
- [ ] ~~Eliminate boxing costs in `DictionaryEncoding` (seems not easy to do without specializing `DictionaryEncoding` for every supported column type)~~  (left to future PRs)

## Micro benchmark

The benchmark uses a 10 million line CSV table consists of bytes, shorts, integers, longs, floats and doubles, measures the time to build the in-memory version of this table, and the time to scan the whole in-memory table.

Benchmark code can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-hivetablescanbenchmark-scala). Script used to generate the input table can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-tablegen-scala).

Speedup:

- Hive table scanning + column buffer building: **18.74%**

  The original benchmark uses 1K as in-memory batch size, when increased to 10K, it can be 28.32% faster.

- In-memory table scanning: **7.95%**

Before:

        | Building | Scanning
------- | -------- | --------
1       | 16472    | 525
2       | 16168    | 530
3       | 16386    | 529
4       | 16184    | 538
5       | 16209    | 521
Average | 16283.8  | 528.6

After:

        | Building | Scanning
------- | -------- | --------
1       | 13124    | 458
2       | 13260    | 529
3       | 12981    | 463
4       | 13214    | 483
5       | 13583    | 500
Average | 13232.4  | 486.6

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

Closes #2327 from liancheng/prevent-boxing/unboxing and squashes the following commits:

4419fe4 [Cheng Lian] Addressing comments
e5d2cf2 [Cheng Lian] Bug fix: should call setNullAt when field value is null to avoid NPE
8b8552b [Cheng Lian] Only checks for partition batch pruning flag once
489f97b [Cheng Lian] Bug fix: TableReader.fillObject uses wrong ordinals
97bbc4e [Cheng Lian] Optimizes hive.TableReader by by providing specific Writable unwrappers a head of time
3dc1f94 [Cheng Lian] Minor changes to eliminate row object creation
5b39cb9 [Cheng Lian] Lowers log level of compression scheme details
f2a7890 [Cheng Lian] Use SpecificMutableRow in InMemoryColumnarTableScan to avoid boxing
9cf30b0 [Cheng Lian] Added row based ColumnType.append/extract
456c366 [Cheng Lian] Made compression decoder row based
edac3cd [Cheng Lian] Makes ColumnAccessor.extractSingle row based
8216936 [Cheng Lian] Removes boxing cost in IntDelta and LongDelta by providing specialized implementations
b70d519 [Cheng Lian] Made some in-memory columnar storage interfaces row-based
[SQL] Decrease partitions when testing

Author: Michael Armbrust <michael@databricks.com>

Closes #2164 from marmbrus/shufflePartitions and squashes the following commits:

0da1e8c [Michael Armbrust] test hax
ef2d985 [Michael Armbrust] more test hacks.
2dabae3 [Michael Armbrust] more test fixes
0bdbf21 [Michael Armbrust] Make parquet tests less order dependent
b42eeab [Michael Armbrust] increase test parallelism
80453d5 [Michael Armbrust] Decrease partitions when testing
[SPARK-3030] [PySpark] Reuse Python worker

Reuse Python worker to avoid the overhead of fork() Python process for each tasks. It also tracks the broadcasts for each worker, avoid sending repeated broadcasts.

This can reduce the time for dummy task from 22ms to 13ms (-40%). It can help to reduce the latency for Spark Streaming.

For a job with broadcast (43M after compress):
```
    b = sc.broadcast(set(range(30000000)))
    print sc.parallelize(range(24000), 100).filter(lambda x: x in b.value).count()
```
It will finish in 281s without reused worker, and it will finish in 65s with reused worker(4 CPUs). After reusing the worker, it can save about 9 seconds for transfer and deserialize the broadcast for each tasks.

It's enabled by default, could be disabled by `spark.python.worker.reuse = false`.

Author: Davies Liu <davies.liu@gmail.com>

Closes #2259 from davies/reuse-worker and squashes the following commits:

f11f617 [Davies Liu] Merge branch 'master' into reuse-worker
3939f20 [Davies Liu] fix bug in serializer in mllib
cf1c55e [Davies Liu] address comments
3133a60 [Davies Liu] fix accumulator with reused worker
760ab1f [Davies Liu] do not reuse worker if there are any exceptions
7abb224 [Davies Liu] refactor: sychronized with itself
ac3206e [Davies Liu] renaming
8911f44 [Davies Liu] synchronized getWorkerBroadcasts()
6325fc1 [Davies Liu] bugfix: bid >= 0
e0131a2 [Davies Liu] fix name of config
583716e [Davies Liu] only reuse completed and not interrupted worker
ace2917 [Davies Liu] kill python worker after timeout
6123d0f [Davies Liu] track broadcasts for each worker
8d2f08c [Davies Liu] reuse python worker
[SPARK-3463] [PySpark] aggregate and show spilled bytes in Python

Aggregate the number of bytes spilled into disks during aggregation or sorting, show them in Web UI.

![spilled](https://cloud.githubusercontent.com/assets/40902/4209758/4b995562-386d-11e4-97c1-8e838ee1d4e3.png)

This patch is blocked by SPARK-3465. (It includes a fix for that).

Author: Davies Liu <davies.liu@gmail.com>

Closes #2336 from davies/metrics and squashes the following commits:

e37df38 [Davies Liu] remove outdated comments
1245eb7 [Davies Liu] remove the temporary fix
ebd2f43 [Davies Liu] Merge branch 'master' into metrics
7e4ad04 [Davies Liu] Merge branch 'master' into metrics
fbe9029 [Davies Liu] show spilled bytes in Python in web ui
SPARK-3039: Allow spark to be built using avro-mapred for hadoop2

SPARK-3039: Adds the maven property "avro.mapred.classifier" to build spark-assembly with avro-mapred with support for the new Hadoop API. Sets this property to hadoop2 for Hadoop 2 profiles.

I am not very familiar with maven, nor do I know whether this potentially breaks something in the hive part of spark. There might be a more elegant way of doing this.

Author: Bertrand Bossy <bertrandbossy@gmail.com>

Closes #1945 from bbossy/SPARK-3039 and squashes the following commits:

c32ce59 [Bertrand Bossy] SPARK-3039: Allow spark to be built using avro-mapred for hadoop2
[SPARK-3452] Maven build should skip publishing artifacts people shouldn...

...'t depend on

Publish local in maven term is `install`

and publish otherwise is `deploy`

So disabled both for following projects.

Author: Prashant Sharma <prashant.s@imaginea.com>

Closes #2329 from ScrapCodes/SPARK-3452/maven-skip-install and squashes the following commits:

257b79a [Prashant Sharma] [SPARK-3452] Maven build should skip publishing artifacts people shouldn't depend on
[SPARK-3410] The priority of shutdownhook for ApplicationMaster should not be integer literal

I think, it need to keep the priority of shutdown hook for ApplicationMaster than the priority of shutdown hook for o.a.h.FileSystem depending on changing the priority for FileSystem.

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2283 from sarutak/SPARK-3410 and squashes the following commits:

1d44fef [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3410
bd6cc53 [Kousuke Saruta] Modified style
ee6f1aa [Kousuke Saruta] Added constant "SHUTDOWN_HOOK_PRIORITY" to ApplicationMaster
54eb68f [Kousuke Saruta] Changed Shutdown hook priority to 20
2f0aee3 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3410
4c5cb93 [Kousuke Saruta] Modified the priority for AM's shutdown hook
217d1a4 [Kousuke Saruta] Removed unused import statements
717aba2 [Kousuke Saruta] Modified ApplicationMaster to make to keep the priority of shutdown hook for ApplicationMaster higher than the priority of shutdown hook for HDFS
[SPARK-3425] do not set MaxPermSize for OpenJDK 1.8

Closes #2387

Author: Matthew Farrellee <matt@redhat.com>

Closes #2301 from mattf/SPARK-3425 and squashes the following commits:

20f3c09 [Matthew Farrellee] [SPARK-3425] do not set MaxPermSize for OpenJDK 1.8
[SPARK-3518] Remove wasted statement in JsonProtocol

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2380 from sarutak/SPARK-3518 and squashes the following commits:

8a1464e [Kousuke Saruta] Replaced a variable with simple field reference
c660fbc [Kousuke Saruta] Removed useless statement in JsonProtocol.scala
[SPARK-2714] DAGScheduler logs jobid when runJob finishes

DAGScheduler logs jobid when runJob finishes

Author: yantangzhai <tyz0303@163.com>

Closes #1617 from YanTangZhai/SPARK-2714 and squashes the following commits:

0a0243f [yantangzhai] [SPARK-2714] DAGScheduler logs jobid when runJob finishes
fbb1150 [yantangzhai] [SPARK-2714] DAGScheduler logs jobid when runJob finishes
7aec2a9 [yantangzhai] [SPARK-2714] DAGScheduler logs jobid when runJob finishes
fb42f0f [yantangzhai] [SPARK-2714] DAGScheduler logs jobid when runJob finishes
090d908 [yantangzhai] [SPARK-2714] DAGScheduler logs jobid when runJob finishes
[SPARK-3396][MLLIB] Use SquaredL2Updater in LogisticRegressionWithSGD

SimpleUpdater ignores the regularizer, which leads to an unregularized
LogReg. To enable the common L2 regularizer (and the corresponding
regularization parameter) for logistic regression the SquaredL2Updater
has to be used in SGD (see, e.g., [SVMWithSGD])

Author: Christoph Sawade <christoph@sawade.me>

Closes #2398 from BigCrunsh/fix-regparam-logreg and squashes the following commits:

0820c04 [Christoph Sawade] Use SquaredL2Updater in LogisticRegressionWithSGD
[MLlib] Update SVD documentation in IndexedRowMatrix

Updating this to reflect the newest SVD via ARPACK

Author: Reza Zadeh <rizlar@gmail.com>

Closes #2389 from rezazadeh/irmdocs and squashes the following commits:

7fa1313 [Reza Zadeh] Update svd docs
715da25 [Reza Zadeh] Updated computeSVD documentation IndexedRowMatrix
[SPARK-3516] [mllib] DecisionTree: Add minInstancesPerNode, minInfoGain params to example and Python API

Added minInstancesPerNode, minInfoGain params to:
* DecisionTreeRunner.scala example
* Python API (tree.py)

Also:
* Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements"
* small style fixes

CC: mengxr

Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Author: chouqin <liqiping1991@gmail.com>

Closes #2349 from jkbradley/chouqin-dt-preprune and squashes the following commits:

61b2e72 [Joseph K. Bradley] Added max of 10GB for maxMemoryInMB in Strategy.
a95e7c8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
95c479d [Joseph K. Bradley] * Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements" * small style fixes
e2628b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
19b01af [Joseph K. Bradley] Merge remote-tracking branch 'chouqin/dt-preprune' into chouqin-dt-preprune
f1d11d1 [chouqin] fix typo
c7ebaf1 [chouqin] fix typo
39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test
c6e2dfc [Joseph K. Bradley] Added minInstancesPerNode and minInfoGain parameters to DecisionTreeRunner.scala and to Python API in tree.py
0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree
d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1
efcc736 [qiping.lqp] fix bug
10b8012 [qiping.lqp] fix style
6728fad [qiping.lqp] minor fix: remove empty lines
bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune
cadd569 [qiping.lqp] add api docs
46b891f [qiping.lqp] fix bug
e72c7e4 [qiping.lqp] add comments
845c6fa [qiping.lqp] fix style
f195e83 [qiping.lqp] fix style
987cbf4 [qiping.lqp] fix bug
ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain
ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree
[SPARK-2951] [PySpark] support unpickle array.array for Python 2.6

Pyrolite can not unpickle array.array which pickled by Python 2.6, this patch fix it by extend Pyrolite.

There is a bug in Pyrolite when unpickle array of float/double, this patch workaround it by reverse the endianness for float/double. This workaround should be removed after Pyrolite have a new release to fix this issue.

I had send an PR to Pyrolite to fix it:  https://github.com/irmen/Pyrolite/pull/11

Author: Davies Liu <davies.liu@gmail.com>

Closes #2365 from davies/pickle and squashes the following commits:

f44f771 [Davies Liu] enable tests about array
3908f5c [Davies Liu] Merge branch 'master' into pickle
c77c87b [Davies Liu] cleanup debugging code
60e4e2f [Davies Liu] support unpickle array.array for Python 2.6