[SPARK-2841][MLlib] Documentation for feature transformations

Documentation for newly added feature transformations:
1. TF-IDF
2. StandardScaler
3. Normalizer

Author: DB Tsai <dbtsai@alpinenow.com>

Closes #2068 from dbtsai/transformer-documentation and squashes the following commits:

109f324 [DB Tsai] address feedback
[MLlib][SPARK-2997] Update SVD documentation to reflect roughly square

Update the documentation to reflect the fact we can handle roughly square matrices.

Author: Reza Zadeh <rizlar@gmail.com>

Closes #2070 from rezazadeh/svddocs and squashes the following commits:

826b8fe [Reza Zadeh] left singular vectors
3f34fc6 [Reza Zadeh] PCA is still TS
7ffa2aa [Reza Zadeh] better title
aeaf39d [Reza Zadeh] More docs
788ed13 [Reza Zadeh] add computational cost explanation
6429c59 [Reza Zadeh] Add link to rowmatrix docs
1eeab8b [Reza Zadeh] Update SVD documentation to reflect roughly square
[SPARK-2871] [PySpark] add zipWithIndex() and zipWithUniqueId()

RDD.zipWithIndex()

        Zips this RDD with its element indices.

        The ordering is first based on the partition index and then the
        ordering of items within each partition. So the first item in
        the first partition gets index 0, and the last item in the last
        partition receives the largest index.

        This method needs to trigger a spark job when this RDD contains
        more than one partitions.

        >>> sc.parallelize(range(4), 2).zipWithIndex().collect()
        [(0, 0), (1, 1), (2, 2), (3, 3)]

RDD.zipWithUniqueId()

        Zips this RDD with generated unique Long ids.

        Items in the kth partition will get ids k, n+k, 2*n+k, ..., where
        n is the number of partitions. So there may exist gaps, but this
        method won't trigger a spark job, which is different from
        L{zipWithIndex}

        >>> sc.parallelize(range(4), 2).zipWithUniqueId().collect()
        [(0, 0), (2, 1), (1, 2), (3, 3)]

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

Closes #2092 from davies/zipWith and squashes the following commits:

cebe5bf [Davies Liu] improve test cases, reverse the order of index
0d2a128 [Davies Liu] add zipWithIndex() and zipWithUniqueId()
[SPARK-2495][MLLIB] make KMeans constructor public

to re-construct k-means models freeman-lab

Author: Xiangrui Meng <meng@databricks.com>

Closes #2112 from mengxr/public-constructors and squashes the following commits:

18d53a9 [Xiangrui Meng] make KMeans constructor public
SPARK-2798 [BUILD] Correct several small errors in Flume module pom.xml files

(EDIT) Since the scalatest issue was since resolved, this is now about a few small problems in the Flume Sink `pom.xml`

- `scalatest` is not declared as a test-scope dependency
- Its Avro version doesn't match the rest of the build
- Its Flume version is not synced with the other Flume module
- The other Flume module declares its dependency on Flume Sink slightly incorrectly, hard-coding the Scala 2.10 version
- It depends on Scala Lang directly, which it shouldn't

Author: Sean Owen <sowen@cloudera.com>

Closes #1726 from srowen/SPARK-2798 and squashes the following commits:

a46e2c6 [Sean Owen] scalatest to test scope, harmonize Avro and Flume versions, remove direct Scala dependency, fix '2.10' in Flume dependency
SPARK-3180  - Better control of security groups

Adds the --authorized-address and --additional-security-group options as explained in the issue.

Author: Allan Douglas R. de Oliveira <allan@chaordicsystems.com>

Closes #2088 from douglaz/configurable_sg and squashes the following commits:

e3e48ca [Allan Douglas R. de Oliveira] Adds the option to specify the address authorized to access the SG and another option to provide an additional existing SG
[FIX] fix error message in sendMessageReliably

rxin

Author: Xiangrui Meng <meng@databricks.com>

Closes #2120 from mengxr/sendMessageReliably and squashes the following commits:

b14400c [Xiangrui Meng] fix error message in sendMessageReliably
Fixed a typo in docs/running-on-mesos.md

It should be `spark-env.sh` rather than `spark.env.sh`.

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

Closes #2119 from liancheng/fix-mesos-doc and squashes the following commits:

f360548 [Cheng Lian] Fixed a typo in docs/running-on-mesos.md
[SPARK-3204][SQL] MaxOf would be foldable if both left and right are foldable.

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

Closes #2116 from ueshin/issues/SPARK-3204 and squashes the following commits:

7d9b107 [Takuya UESHIN] Make MaxOf foldable if both left and right are foldable.
[SPARK-2929][SQL] Refactored Thrift server and CLI suites

Removed most hard coded timeout, timing assumptions and all `Thread.sleep`. Simplified IPC and synchronization with `scala.sys.process` and future/promise so that the test suites can run more robustly and faster.

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

Closes #1856 from liancheng/thriftserver-tests and squashes the following commits:

2d914ca [Cheng Lian] Minor refactoring
0e12e71 [Cheng Lian] Cleaned up test output
0ee921d [Cheng Lian] Refactored Thrift server and CLI suites
[SPARK-3058] [SQL] Support EXTENDED for EXPLAIN

Provide `extended` keyword support for `explain` command in SQL. e.g.
```
explain extended select key as a1, value as a2 from src where key=1;
== Parsed Logical Plan ==
Project ['key AS a1#3,'value AS a2#4]
 Filter ('key = 1)
  UnresolvedRelation None, src, None

== Analyzed Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
 Filter (CAST(key#8, DoubleType) = CAST(1, DoubleType))
  MetastoreRelation default, src, None

== Optimized Logical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
 Filter (CAST(key#8, DoubleType) = 1.0)
  MetastoreRelation default, src, None

== Physical Plan ==
Project [key#8 AS a1#3,value#9 AS a2#4]
 Filter (CAST(key#8, DoubleType) = 1.0)
  HiveTableScan [key#8,value#9], (MetastoreRelation default, src, None), None

Code Generation: false
== RDD ==
(2) MappedRDD[14] at map at HiveContext.scala:350
  MapPartitionsRDD[13] at mapPartitions at basicOperators.scala:42
  MapPartitionsRDD[12] at mapPartitions at basicOperators.scala:57
  MapPartitionsRDD[11] at mapPartitions at TableReader.scala:112
  MappedRDD[10] at map at TableReader.scala:240
  HadoopRDD[9] at HadoopRDD at TableReader.scala:230
```

It's the sub task of #1847. But can go without any dependency.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #1962 from chenghao-intel/explain_extended and squashes the following commits:

295db74 [Cheng Hao] Fix bug in printing the simple execution plan
48bc989 [Cheng Hao] Support EXTENDED for EXPLAIN
[SQL] logWarning should be logInfo in getResultSetSchema

Author: wangfei <wangfei_hello@126.com>

Closes #1939 from scwf/patch-5 and squashes the following commits:

f952d10 [wangfei] [SQL] logWarning should be logInfo in getResultSetSchema
[SPARK-3011][SQL] _temporary directory should be filtered out by sqlContext.parquetFile

fix compile error on hadoop 0.23 for the pull request #1924.

Author: Chia-Yung Su <chiayung@appier.com>

Closes #1959 from joesu/bugfix-spark3011 and squashes the following commits:

be30793 [Chia-Yung Su] remove .* and _* except _metadata
8fe2398 [Chia-Yung Su] add note to explain
40ea9bd [Chia-Yung Su] fix hadoop-0.23 compile error
c7e44f2 [Chia-Yung Su] match syntax
f8fc32a [Chia-Yung Su] filter out tmp dir
SPARK-2481: The environment variables SPARK_HISTORY_OPTS is covered in spark-env.sh

Author: witgo <witgo@qq.com>
Author: GuoQiang Li <witgo@qq.com>

Closes #1341 from witgo/history_env and squashes the following commits:

b4fd9f8 [GuoQiang Li] review commit
0ebe401 [witgo] *-history-server.sh load spark-config.sh
[SPARK-2976] Replace tabs with spaces

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

Closes #1895 from sarutak/SPARK-2976 and squashes the following commits:

1cf7e69 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-2976
d1e0666 [Kousuke Saruta] Modified styles
c5e80a4 [Kousuke Saruta] Remove tab from JavaPageRank.java and JavaKinesisWordCountASL.java
c003b36 [Kousuke Saruta] Removed tab from sorttable.js
[Spark-3222] [SQL] Cross join support in HiveQL

We can simple treat cross join as inner join without join conditions.

Author: Daoyuan Wang <daoyuan.wang@intel.com>
Author: adrian-wang <daoyuanwong@gmail.com>

Closes #2124 from adrian-wang/crossjoin and squashes the following commits:

8c9b7c5 [Daoyuan Wang] add a test
7d47bbb [adrian-wang] add cross join support for hql
[SPARK-2886] Use more specific actor system name than "spark"

As of #1777 we log the name of the actor system when it binds to a port. The current name "spark" is super general and does not convey any meaning. For instance, the following line is taken from my driver log after setting `spark.driver.port` to 5001.
```
14/08/13 19:33:29 INFO Remoting: Remoting started; listening on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/13 19:33:29 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://sparkandrews-mbp:5001]
14/08/06 13:40:05 INFO Utils: Successfully started service 'spark' on port 5001.
```
This commit renames this to "sparkDriver" and "sparkExecutor". The goal of this unambitious PR is simply to make the logged information more explicit without introducing any change in functionality.

Author: Andrew Or <andrewor14@gmail.com>

Closes #1810 from andrewor14/service-name and squashes the following commits:

8c459ed [Andrew Or] Use a common variable for driver/executor actor system names
3a92843 [Andrew Or] Change actor name to sparkDriver and sparkExecutor
921363e [Andrew Or] Merge branch 'master' of github.com:apache/spark into service-name
c8c6a62 [Andrew Or] Do not include hyphens in actor name
1c1b42e [Andrew Or] Avoid spaces in akka system name
f644b55 [Andrew Or] Use more specific service name
[SPARK-3131][SQL] Allow user to set parquet compression codec for writing ParquetFile in SQLContext

There are 4 different compression codec available for ```ParquetOutputFormat```

in Spark SQL, it was set as a hard-coded value in ```ParquetRelation.defaultCompression```

original discuss:
https://github.com/apache/spark/pull/195#discussion-diff-11002083

i added a new config property in SQLConf to allow user to change this compression codec, and i used similar short names syntax as described in SPARK-2953 #1873 (https://github.com/apache/spark/pull/1873/files#diff-0)

btw, which codec should we use as default? it was set to GZIP (https://github.com/apache/spark/pull/195/files#diff-4), but i think maybe we should change this to SNAPPY, since SNAPPY is already the default codec for shuffling in spark-core (SPARK-2469, #1415), and parquet-mr supports Snappy codec natively (https://github.com/Parquet/parquet-mr/commit/e440108de57199c12d66801ca93804086e7f7632).

Author: chutium <teng.qiu@gmail.com>

Closes #2039 from chutium/parquet-compression and squashes the following commits:

2f44964 [chutium] [SPARK-3131][SQL] parquet compression default codec set to snappy, also in test suite
e578e21 [chutium] [SPARK-3131][SQL] compression codec config property name and default codec set to snappy
21235dc [chutium] [SPARK-3131][SQL] Allow user to set parquet compression codec for writing ParquetFile in SQLContext
[SPARK-2871] [PySpark] add histgram() API

RDD.histogram(buckets)

        Compute a histogram using the provided buckets. The buckets
        are all open to the right except for the last which is closed.
        e.g. [1,10,20,50] means the buckets are [1,10) [10,20) [20,50],
        which means 1<=x<10, 10<=x<20, 20<=x<=50. And on the input of 1
        and 50 we would have a histogram of 1,0,1.

        If your histogram is evenly spaced (e.g. [0, 10, 20, 30]),
        this can be switched from an O(log n) inseration to O(1) per
        element(where n = # buckets).

        Buckets must be sorted and not contain any duplicates, must be
        at least two elements.

        If `buckets` is a number, it will generates buckets which is
        evenly spaced between the minimum and maximum of the RDD. For
        example, if the min value is 0 and the max is 100, given buckets
        as 2, the resulting buckets will be [0,50) [50,100]. buckets must
        be at least 1 If the RDD contains infinity, NaN throws an exception
        If the elements in RDD do not vary (max == min) always returns
        a single bucket.

        It will return an tuple of buckets and histogram.

        >>> rdd = sc.parallelize(range(51))
        >>> rdd.histogram(2)
        ([0, 25, 50], [25, 26])
        >>> rdd.histogram([0, 5, 25, 50])
        ([0, 5, 25, 50], [5, 20, 26])
        >>> rdd.histogram([0, 15, 30, 45, 60], True)
        ([0, 15, 30, 45, 60], [15, 15, 15, 6])
        >>> rdd = sc.parallelize(["ab", "ac", "b", "bd", "ef"])
        >>> rdd.histogram(("a", "b", "c"))
        (('a', 'b', 'c'), [2, 2])

closes #122, it's duplicated.

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

Closes #2091 from davies/histgram and squashes the following commits:

a322f8a [Davies Liu] fix deprecation of e.message
84e85fa [Davies Liu] remove evenBuckets, add more tests (including str)
d9a0722 [Davies Liu] address comments
0e18a2d [Davies Liu] add histgram() API
[SPARK-2969][SQL] Make ScalaReflection be able to handle ArrayType.containsNull and MapType.valueContainsNull.

Make `ScalaReflection` be able to handle like:

- `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)`
- `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)`
- `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)`
- `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)`

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

Closes #1889 from ueshin/issues/SPARK-2969 and squashes the following commits:

24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API.
79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API.
7cd1a7a [Takuya UESHIN] Fix json test failures.
2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true.
2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull.
9fa02f5 [Takuya UESHIN] Fix a test failure.
1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.