[SPARK-4196][SPARK-4602][Streaming] Fix serialization issue in PairDStreamFunctions.saveAsNewAPIHadoopFiles

Solves two JIRAs in one shot
- Makes the ForechDStream created by saveAsNewAPIHadoopFiles serializable for checkpoints
- Makes the default configuration object used saveAsNewAPIHadoopFiles be the Spark's hadoop configuration

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

Closes #3457 from tdas/savefiles-fix and squashes the following commits:

bb4729a [Tathagata Das] Same treatment for saveAsHadoopFiles
b382ea9 [Tathagata Das] Fix serialization issue in PairDStreamFunctions.saveAsNewAPIHadoopFiles.

(cherry picked from commit 8838ad7c135a585cde015dc38b5cb23314502dd9)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
[HOTFIX] Fixing broken build due to missing imports.
[SPARK-4592] Avoid duplicate worker registrations in standalone mode

**Summary.** On failover, the Master may receive duplicate registrations from the same worker, causing the worker to exit. This is caused by this commit https://github.com/apache/spark/commit/4afe9a4852ebeb4cc77322a14225cd3dec165f3f, which adds logic for the worker to re-register with the master in case of failures. However, the following race condition may occur:

(1) Master A fails and Worker attempts to reconnect to all masters
(2) Master B takes over and notifies Worker
(3) Worker responds by registering with Master B
(4) Meanwhile, Worker's previous reconnection attempt reaches Master B, causing the same Worker to register with Master B twice

**Fix.** Instead of attempting to register with all known masters, the worker should re-register with only the one that it has been communicating with. This is safe because the fact that a failover has occurred means the old master must have died. Then, when the worker is finally notified of a new master, it gives up on the old one in favor of the new one.

**Caveat.** Even this fix is subject to more obscure race conditions. For instance, if Master B fails and Master A recovers immediately, then Master A may still observe duplicate worker registrations. However, this and other potential race conditions summarized in [SPARK-4592](https://issues.apache.org/jira/browse/SPARK-4592), are much, much less likely than the one described above, which is deterministically reproducible.

Author: Andrew Or <andrew@databricks.com>

Closes #3447 from andrewor14/standalone-failover and squashes the following commits:

0d9716c [Andrew Or] Move re-registration logic to actor for thread-safety
79286dc [Andrew Or] Preserve old behavior for initial retries
83b321c [Andrew Or] Tweak wording
1fce6a9 [Andrew Or] Active master actor could be null in the beginning
b6f269e [Andrew Or] Avoid duplicate worker registrations

(cherry picked from commit 1b2ab1cd1b7cab9076f3c511188a610eda935701)
Signed-off-by: Andrew Or <andrew@databricks.com>
[SPARK-4546] Improve HistoryServer first time user experience

The documentation points the user to run the following
```
sbin/start-history-server.sh
```
The first thing this does is throw an exception that complains a log directory is not specified. The exception message itself does not say anything about what to set. Instead we should have a default and a landing page with a better message. The new default log directory is `file:/tmp/spark-events`.

This is what it looks like as of this PR:

![after](https://issues.apache.org/jira/secure/attachment/12682985/after.png)

Author: Andrew Or <andrew@databricks.com>

Closes #3411 from andrewor14/minor-history-improvements and squashes the following commits:

f33d6b3 [Andrew Or] Point user to set config if default log dir does not exist
fc4c17a [Andrew Or] Improve HistoryServer UX

(cherry picked from commit 9afcbe494a3535a9bf7958429b72e989972f82d9)
Signed-off-by: Andrew Or <andrew@databricks.com>
Fix SPARK-4471: blockManagerIdFromJson function throws exception while B...

Fix [SPARK-4471](https://issues.apache.org/jira/browse/SPARK-4471): blockManagerIdFromJson function throws exception while BlockManagerId be null in MetadataFetchFailedException

Author: hushan[胡珊] <hushan@xiaomi.com>

Closes #3340 from suyanNone/fix-blockmanagerId-jnothing-2 and squashes the following commits:

159f9a3 [hushan[胡珊]] Refine test code for blockmanager is null
4380d73 [hushan[胡珊]] remove useless blank line
3ccf651 [hushan[胡珊]] Fix SPARK-4471: blockManagerIdFromJson function throws exception while metadata fetch failed

(cherry picked from commit 9bdf5da59036c0b052df756fc4a28d64677072e7)
Signed-off-by: Andrew Or <andrew@databricks.com>
[Spark-4509] Revert EC2 tag-based cluster membership patch

This PR reverts changes related to tag-based cluster membership. As discussed in SPARK-3332, we didn't figure out a safe strategy to use tags to determine cluster membership, because tagging is not atomic. The following changes are reverted:

SPARK-2333: 94053a7b766788bb62e2dbbf352ccbcc75f71fc0
SPARK-3213: 7faf755ae4f0cf510048e432340260a6e609066d
SPARK-3608: 78d4220fa0bf2f9ee663e34bbf3544a5313b02f0.

I tested launch, login, and destroy. It is easy to check the diff by comparing it to Josh's patch for branch-1.1:

https://github.com/apache/spark/pull/2225/files

JoshRosen I sent the PR to master. It might be easier for us to keep master and branch-1.2 the same at this time. We can always re-apply the patch once we figure out a stable solution.

Author: Xiangrui Meng <meng@databricks.com>

Closes #3453 from mengxr/SPARK-4509 and squashes the following commits:

f0b708b [Xiangrui Meng] revert 94053a7b766788bb62e2dbbf352ccbcc75f71fc0
4298ea5 [Xiangrui Meng] revert 7faf755ae4f0cf510048e432340260a6e609066d
35963a1 [Xiangrui Meng] Revert "SPARK-3608 Break if the instance tag naming succeeds"

(cherry picked from commit 7eba0fbe456c451122d7a2353ff0beca00f15223)
Signed-off-by: Andrew Or <andrew@databricks.com>
[SPARK-4583] [mllib] LogLoss for GradientBoostedTrees fix + doc updates

Currently, the LogLoss used by GradientBoostedTrees has 2 issues:
* the gradient (and therefore loss) does not match that used by Friedman (1999)
* the error computation uses 0/1 accuracy, not log loss

This PR updates LogLoss.
It also adds some doc for boosting and forests.

I tested it on sample data and made sure the log loss is monotonically decreasing with each boosting iteration.

CC: mengxr manishamde codedeft

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

Closes #3439 from jkbradley/gbt-loss-fix and squashes the following commits:

cfec17e [Joseph K. Bradley] removed forgotten temp comments
a27eb6d [Joseph K. Bradley] corrections to last log loss commit
ed5da2c [Joseph K. Bradley] updated LogLoss (boosting) for numerical stability
5e52bff [Joseph K. Bradley] * Removed the 1/2 from SquaredError.  This also required updating the test suite since it effectively doubles the gradient and loss. * Added doc for developers within RandomForest. * Small cleanup in test suite (generating data only once)
e57897a [Joseph K. Bradley] Fixed LogLoss for GradientBoostedTrees, and updated doc for losses, forests, and boosting

(cherry picked from commit c251fd7405db57d3ab2686c38712601fd8f13ccd)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
[HOTFIX]: Adding back without-hive dist
[SPARK-4604][MLLIB] make MatrixFactorizationModel public

User could construct an MF model directly. I added a note about the performance.

Author: Xiangrui Meng <meng@databricks.com>

Closes #3459 from mengxr/SPARK-4604 and squashes the following commits:

f64bcd3 [Xiangrui Meng] organize imports
ed08214 [Xiangrui Meng] check preconditions and unit tests
a624c12 [Xiangrui Meng] make MatrixFactorizationModel public

(cherry picked from commit b5fb1410c5eed1156decb4f9fcc22436a658ce4d)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
[SPARK-4516] Cap default number of Netty threads at 8

In practice, only 2-4 cores should be required to transfer roughly 10 Gb/s, and each core that we use will have an initial overhead of roughly 32 MB of off-heap memory, which comes at a premium.

Thus, this value should still retain maximum throughput and reduce wasted off-heap memory allocation. It can be overridden by setting the number of serverThreads and clientThreads manually in Spark's configuration.

Author: Aaron Davidson <aaron@databricks.com>

Closes #3469 from aarondav/fewer-pools2 and squashes the following commits:

087c59f [Aaron Davidson] [SPARK-4516] Cap default number of Netty threads at 8

(cherry picked from commit f5f2d27385c243959f03a9d78a149d5f405b2f50)
Signed-off-by: Patrick Wendell <pwendell@gmail.com>
Revert "Preparing development version 1.2.1-SNAPSHOT"

This reverts commit d7ac6013483e83caff8ea54c228f37aeca159db8.
Revert "Preparing Spark release v1.2.0-snapshot1"

This reverts commit 38c1fbd9694430cefd962c90bc36b0d108c6124b.
Preparing Spark release v1.2.0-rc1
Preparing development version 1.2.1-SNAPSHOT
Revert "Preparing development version 1.2.1-SNAPSHOT"

This reverts commit d7b1ecb25676d228deb6fe05efdb4e2ab9c3e30b.
Revert "Preparing Spark release v1.2.0-rc1"

This reverts commit db7f4a898af22a02b36428507f8ef2b429d78dc1.
Preparing Spark release v1.2.0-rc1
Preparing development version 1.2.1-SNAPSHOT
Revert "Preparing development version 1.2.1-SNAPSHOT"

This reverts commit 79df6b43ae762263a8120f423ddb4a0811dd4b6f.
Revert "Preparing Spark release v1.2.0-rc1"

This reverts commit 5247dd859b95a440baa562b9827bdeb26aa6530e.