[YARN] SPARK-2577: File upload to viewfs is broken due to mount point re...

Opting to the option 2 defined in SPARK-2577, i.e., retrieve and pass the correct file system object to addResource.

Author: Gera Shegalov <gera@twitter.com>

Closes #1483 from gerashegalov/master and squashes the following commits:

90c9087 [Gera Shegalov] [YARN] SPARK-2577: File upload to viewfs is broken due to mount point resolution
Remove GraphX MessageToPartition for compatibility with sort-based shuffle

MessageToPartition was used in `Graph#partitionBy`. Unlike a Tuple2, it marked the key as transient to avoid sending it over the network. However, it was incompatible with sort-based shuffle (SPARK-2045) and represented only a minor optimization: for partitionBy, it improved performance by 6.3% (30.4 s to 28.5 s) and reduced communication by 5.6% (114.2 MB to 107.8 MB).

Author: Ankur Dave <ankurdave@gmail.com>

Closes #1537 from ankurdave/remove-MessageToPartition and squashes the following commits:

f9d0054 [Ankur Dave] Remove MessageToPartition
ab71364 [Ankur Dave] Remove unused VertexBroadcastMsg
[SPARK-2617] Correct doc and usages of preservesPartitioning

The name `preservesPartitioning` is ambiguous: 1) preserves the indices of partitions, 2) preserves the partitioner. The latter is correct and `preservesPartitioning` should really be called `preservesPartitioner` to avoid confusion. Unfortunately, this is already part of the API and we cannot change. We should be clear in the doc and fix wrong usages.

This PR

1. adds notes in `maPartitions*`,
2. makes `RDD.sample` preserve partitioner,
3. changes `preservesPartitioning` to false in  `RDD.zip` because the keys of the first RDD are no longer the keys of the zipped RDD,
4. fixes some wrong usages in MLlib.

Author: Xiangrui Meng <meng@databricks.com>

Closes #1526 from mengxr/preserve-partitioner and squashes the following commits:

b361e65 [Xiangrui Meng] update doc based on pwendell's comments
3b1ba19 [Xiangrui Meng] update doc
357575c [Xiangrui Meng] fix unit test
20b4816 [Xiangrui Meng] Merge branch 'master' into preserve-partitioner
d1caa65 [Xiangrui Meng] add doc to explain preservesPartitioning fix wrong usage of preservesPartitioning make sample preserse partitioning
[SPARK-2609] Log thread ID when spilling ExternalAppendOnlyMap

It's useful to know whether one thread is constantly spilling or multiple threads are spilling relatively infrequently. Right now everything looks a little jumbled and we can't tell which lines belong to the same thread. For instance:

```
06:14:37 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (194 times so far)
06:14:37 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (198 times so far)
06:14:37 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (198 times so far)
06:14:37 ExternalAppendOnlyMap: Spilling in-memory map of 10 MB to disk (197 times so far)
06:14:38 ExternalAppendOnlyMap: Spilling in-memory map of 9 MB to disk (45 times so far)
06:14:38 ExternalAppendOnlyMap: Spilling in-memory map of 23 MB to disk (198 times so far)
06:14:38 ExternalAppendOnlyMap: Spilling in-memory map of 38 MB to disk (25 times so far)
06:14:38 ExternalAppendOnlyMap: Spilling in-memory map of 161 MB to disk (25 times so far)
06:14:39 ExternalAppendOnlyMap: Spilling in-memory map of 0 MB to disk (199 times so far)
06:14:39 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (166 times so far)
06:14:39 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (199 times so far)
06:14:39 ExternalAppendOnlyMap: Spilling in-memory map of 4 MB to disk (200 times so far)
```

Author: Andrew Or <andrewor14@gmail.com>

Closes #1517 from andrewor14/external-log and squashes the following commits:

90e48bb [Andrew Or] Log thread ID when spilling
[CORE] SPARK-2640: In "local[N]", free cores of the only executor should be touched by "spark.task.cpus" for every finish/start-up of tasks.

Make spark's "local[N]" better.
In our company, we use "local[N]" in production. It works exellentlly. It's our best choice.

Author: woshilaiceshide <woshilaiceshide@qq.com>

Closes #1544 from woshilaiceshide/localX and squashes the following commits:

6c85154 [woshilaiceshide] [CORE] SPARK-2640: In "local[N]", free cores of the only executor should be touched by "spark.task.cpus" for every finish/start-up of tasks.
[SPARK-2588][SQL] Add some more DSLs.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #1491 from ueshin/issues/SPARK-2588 and squashes the following commits:

43d0a46 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-2588
1023ea0 [Takuya UESHIN] Modify tests to use DSLs.
2310bf1 [Takuya UESHIN] Add some more DSLs.
SPARK-2277: clear host->rack info properly

Hi mridulm, I just think of this issue of [#1212](https://github.com/apache/spark/pull/1212): I added FakeRackUtil to hold the host -> rack mapping. It should be cleaned up after use so that it won't mess up with test cases others may add later.
Really sorry about this.

Author: Rui Li <rui.li@intel.com>

Closes #1454 from lirui-intel/SPARK-2277-fix-UT and squashes the following commits:

f8ea25c [Rui Li] SPARK-2277: clear host->rack info properly
SPARK-2226:  [SQL] transform HAVING clauses with aggregate expressions that aren't in the aggregation list

This change adds an analyzer rule to
  1. find expressions in `HAVING` clause filters that depend on unresolved attributes,
  2. push these expressions down to the underlying aggregates, and then
  3. project them away above the filter.

It also enables the `HAVING` queries in the Hive compatibility suite.

Author: William Benton <willb@redhat.com>

Closes #1497 from willb/spark-2226 and squashes the following commits:

92c9a93 [William Benton] Removed unnecessary import
f1d4f34 [William Benton] Cleanups missed in prior commit
0e1624f [William Benton] Incorporated suggestions from @marmbrus; thanks!
541d4ee [William Benton] Cleanups from review
5a12647 [William Benton] Explanatory comments and stylistic cleanups.
c7f2b2c [William Benton] Whitelist HAVING queries.
29a26e3 [William Benton] Added rule to handle unresolved attributes in HAVING clauses (SPARK-2226)
[SPARK-2569][SQL] Fix shipping of TEMPORARY hive UDFs.

Instead of shipping just the name and then looking up the info on the workers, we now ship the whole classname.  Also, I refactored the file as it was getting pretty large to move out the type conversion code to its own file.

Author: Michael Armbrust <michael@databricks.com>

Closes #1552 from marmbrus/fixTempUdfs and squashes the following commits:

b695904 [Michael Armbrust] Make add jar execute with Hive.  Ship the whole function class name since sometimes we cannot lookup temporary functions on the workers.
[SPARK-2102][SQL][CORE] Add option for kryo registration required and use a resource pool in Spark SQL for Kryo instances.

Author: Ian O Connell <ioconnell@twitter.com>

Closes #1377 from ianoc/feature/SPARK-2102 and squashes the following commits:

5498566 [Ian O Connell] Docs update suggested by Patrick
20e8555 [Ian O Connell] Slight style change
f92c294 [Ian O Connell] Add docs for new KryoSerializer option
f3735c8 [Ian O Connell] Add using a kryo resource pool for the SqlSerializer
4e5c342 [Ian O Connell] Register the SparkConf for kryo, it gets swept into serialization
665805a [Ian O Connell] Add a spark.kryo.registrationRequired option for configuring the Kryo Serializer
[SPARK-2549] Functions defined inside of other functions trigger failures

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

Closes #1510 from ScrapCodes/SPARK-2549/fun-in-fun and squashes the following commits:

9458bc5 [Prashant Sharma] Tested by removing an inner function from excludes.
bc03b1c [Prashant Sharma] SPARK-2549 Functions defined inside of other functions trigger failures
[SPARK-2484][SQL] Build should not run hivecompatibility tests by default.

Author: witgo <witgo@qq.com>

Closes #1403 from witgo/hive_compatibility and squashes the following commits:

4e5ecdb [witgo] The default does not run hive compatibility tests
Replace RoutingTableMessage with pair

RoutingTableMessage was used to construct routing tables to enable
joining VertexRDDs with partitioned edges. It stored three elements: the
destination vertex ID, the source edge partition, and a byte specifying
the position in which the edge partition referenced the vertex to enable
join elimination.

However, this was incompatible with sort-based shuffle (SPARK-2045). It
was also slightly wasteful, because partition IDs are usually much
smaller than 2^32, though this was mitigated by a custom serializer that
used variable-length encoding.

This commit replaces RoutingTableMessage with a pair of (VertexId, Int)
where the Int encodes both the source partition ID (in the lower 30
bits) and the position (in the top 2 bits).

Author: Ankur Dave <ankurdave@gmail.com>

Closes #1553 from ankurdave/remove-RoutingTableMessage and squashes the following commits:

697e17b [Ankur Dave] Replace RoutingTableMessage with pair
SPARK-2662: Fix NPE for JsonProtocol

Author: GuoQiang Li <witgo@qq.com>

Closes #1511 from witgo/JsonProtocol and squashes the following commits:

2b6227f [GuoQiang Li] Fix NPE for JsonProtocol
[SPARK-2658][SQL] Add rule for true = 1.

Author: Michael Armbrust <michael@databricks.com>

Closes #1556 from marmbrus/fixBooleanEqualsOne and squashes the following commits:

ad8edd4 [Michael Armbrust] Add rule for true = 1 and false = 0.
SPARK-2310. Support arbitrary Spark properties on the command line with ...

...spark-submit

The PR allows invocations like
  spark-submit --class org.MyClass --spark.shuffle.spill false myjar.jar

Author: Sandy Ryza <sandy@cloudera.com>

Closes #1253 from sryza/sandy-spark-2310 and squashes the following commits:

1dc9855 [Sandy Ryza] More doc and cleanup
00edfb9 [Sandy Ryza] Review comments
91b244a [Sandy Ryza] Change format to --conf PROP=VALUE
8fabe77 [Sandy Ryza] SPARK-2310. Support arbitrary Spark properties on the command line with spark-submit
[SPARK-2661][bagel]unpersist old processed rdd

Unpersist useless rdd during bagel iteration to make full use of memory.

Author: Daoyuan <daoyuan.wang@intel.com>

Closes #1519 from adrian-wang/bagelunpersist and squashes the following commits:

182c9dd [Daoyuan] rename var nextUseless to lastRDD
87fd3a4 [Daoyuan] bagel unpersist old processed rdd
SPARK-2150: Provide direct link to finished application UI in yarn resou...

...rce manager UI

Use the event logger directory to provide a direct link to finished
application UI in yarn resourcemanager UI.

Author: Rahul Singhal <rahul.singhal@guavus.com>

Closes #1094 from rahulsinghaliitd/SPARK-2150 and squashes the following commits:

95f230c [Rahul Singhal] SPARK-2150: Provide direct link to finished application UI in yarn resource manager UI
[Build] SPARK-2619: Configurable filemode for the spark/bin folder in debian package

Add  a `<deb.bin.filemode>744</deb.bin.filemode>` property to the `assembly/pom.xml` that defaults to `744`.
Use this property for ../bin folder <filemode>.

This patch doesn't change the current default modes but allows one override the modes at build time:
`-Ddeb.bin.filemode=<new mode>`

Author: tzolov <christian.tzolov@gmail.com>

Closes #1531 from tzolov/SPARK-2619 and squashes the following commits:

6d95343 [tzolov] [Build] SPARK-2619: Configurable filemode for the spark/bin folder in the .deb package
[SPARK-2603][SQL] Remove unnecessary toMap and toList in converting Java collections to Scala collections JsonRDD.scala

In JsonRDD.scalafy, we are using toMap/toList to convert a Java Map/List to a Scala one. These two operations are pretty expensive because they read elements from a Java Map/List and then load to a Scala Map/List. We can use Scala wrappers to wrap those Java collections instead of using toMap/toList.

I did a quick test to see the performance. I had a 2.9GB cached RDD[String] storing one JSON object per record (twitter dataset). My simple test program is attached below.
```scala
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._

val jsonData = sc.textFile("...")
jsonData.cache.count

val jsonSchemaRDD = sqlContext.jsonRDD(jsonData)
jsonSchemaRDD.registerAsTable("jt")

sqlContext.sql("select count(*) from jt").collect
```
Stages for the schema inference and the table scan both had 48 tasks. These tasks were executed sequentially. For the current implementation, scanning the JSON dataset will materialize values of all fields of a record. The inferred schema of the dataset can be accessed at https://gist.github.com/yhuai/05fe8a57c638c6666f8d.

From the result, there was no significant difference on running `jsonRDD`. For the simple aggregation query, results are attached below.
```
Original:
Run 1: 26.1s
Run 2: 27.03s
Run 3: 27.035s

With this change:
Run 1: 21.086s
Run 2: 21.035s
Run 3: 21.029s
```

JIRA: https://issues.apache.org/jira/browse/SPARK-2603

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

Closes #1504 from yhuai/removeToMapToList and squashes the following commits:

6831b77 [Yin Huai] Fix failed tests.
09b9bca [Yin Huai] Merge remote-tracking branch 'upstream/master' into removeToMapToList
d1abdb8 [Yin Huai] Remove unnecessary toMap and toList.