[SPARK-4982][DOC] `spark.ui.retainedJobs` description is wrong in Spark UI configuration guide

Author: wangxiaojing <u9jing@gmail.com>

Closes #3818 from wangxiaojing/SPARK-4982 and squashes the following commits:

fe2ad5f [wangxiaojing] change stages to jobs
Adde LICENSE Header to build/mvn, build/sbt and sbt/sbt

Recently, build/mvn and build/sbt are added, and sbt/sbt is changed but there are no license headers. Should we add license headers to the scripts right?
If it's not right, please let me correct.

This PR doesn't affect behavior of Spark, I don't file in JIRA.

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

Closes #3817 from sarutak/add-license-header and squashes the following commits:

1abc972 [Kousuke Saruta] Added LICENSE Header
[SPARK-4946] [CORE] Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem

Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem

Author: YanTangZhai <hakeemzhai@tencent.com>
Author: yantangzhai <tyz0303@163.com>

Closes #3785 from YanTangZhai/SPARK-4946 and squashes the following commits:

9ca6541 [yantangzhai] [SPARK-4946] [CORE] Using AkkaUtils.askWithReply in MapOutputTracker.askTracker to reduce the chance of the communicating problem
e4c2c0a [YanTangZhai] Merge pull request #15 from apache/master
718afeb [YanTangZhai] Merge pull request #12 from apache/master
6e643f8 [YanTangZhai] Merge pull request #11 from apache/master
e249846 [YanTangZhai] Merge pull request #10 from apache/master
d26d982 [YanTangZhai] Merge pull request #9 from apache/master
76d4027 [YanTangZhai] Merge pull request #8 from apache/master
03b62b0 [YanTangZhai] Merge pull request #7 from apache/master
8a00106 [YanTangZhai] Merge pull request #6 from apache/master
cbcba66 [YanTangZhai] Merge pull request #3 from apache/master
cdef539 [YanTangZhai] Merge pull request #1 from apache/master
[Minor] Fix a typo of type parameter in JavaUtils.scala

In JavaUtils.scala, thare is a typo of type parameter. In addition, the type information is removed at the time of compile by erasure.

This issue is really minor so I don't  file in JIRA.

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

Closes #3789 from sarutak/fix-typo-in-javautils and squashes the following commits:

e20193d [Kousuke Saruta] Fixed a typo of type parameter
82bc5d9 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into fix-typo-in-javautils
99f6f63 [Kousuke Saruta] Fixed a typo of type parameter in JavaUtils.scala
[SPARK-4409][MLlib] Additional Linear Algebra Utils

Addition of a very limited number of local matrix manipulation and generation methods that would be helpful in the further development for algorithms on top of BlockMatrix (SPARK-3974), such as Randomized SVD, and Multi Model Training (SPARK-1486).
The proposed methods for addition are:

For `Matrix`
 - map: maps the values in the matrix with a given function. Produces a new matrix.
 - update: the values in the matrix are updated with a given function. Occurs in place.

Factory methods for `DenseMatrix`:
 - *zeros: Generate a matrix consisting of zeros
 - *ones: Generate a matrix consisting of ones
 - *eye: Generate an identity matrix
 - *rand: Generate a matrix consisting of i.i.d. uniform random numbers
 - *randn: Generate a matrix consisting of i.i.d. gaussian random numbers
 - *diag: Generate a diagonal matrix from a supplied vector
*These methods already exist in the factory methods for `Matrices`, however for cases where we require a `DenseMatrix`, you constantly have to add `.asInstanceOf[DenseMatrix]` everywhere, which makes the code "dirtier". I propose moving these functions to factory methods for `DenseMatrix` where the putput will be a `DenseMatrix` and the factory methods for `Matrices` will call these functions directly and output a generic `Matrix`.

Factory methods for `SparseMatrix`:
 - speye: Identity matrix in sparse format. Saves a ton of memory when dimensions are large, especially in Multi Model Training, where each row requires being multiplied by a scalar.
 - sprand: Generate a sparse matrix with a given density consisting of i.i.d. uniform random numbers.
 - sprandn: Generate a sparse matrix with a given density consisting of i.i.d. gaussian random numbers.
 - diag: Generate a diagonal matrix from a supplied vector, but is memory efficient, because it just stores the diagonal. Again, very helpful in Multi Model Training.

Factory methods for `Matrices`:
 - Include all the factory methods given above, but return a generic `Matrix` rather than `SparseMatrix` or `DenseMatrix`.
 - horzCat: Horizontally concatenate matrices to form one larger matrix. Very useful in both Multi Model Training, and for the repartitioning of BlockMatrix.
 - vertCat: Vertically concatenate matrices to form one larger matrix. Very useful for the repartitioning of BlockMatrix.

The names for these methods were selected from MATLAB

Author: Burak Yavuz <brkyvz@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes #3319 from brkyvz/SPARK-4409 and squashes the following commits:

b0354f6 [Burak Yavuz] [SPARK-4409] Incorporated mengxr's code
04c4829 [Burak Yavuz] Merge pull request #1 from mengxr/SPARK-4409
80cfa29 [Xiangrui Meng] minor changes
ecc937a [Xiangrui Meng] update sprand
4e95e24 [Xiangrui Meng] simplify fromCOO implementation
10a63a6 [Burak Yavuz] [SPARK-4409] Fourth pass of code review
f62d6c7 [Burak Yavuz] [SPARK-4409] Modified genRandMatrix
3971c93 [Burak Yavuz] [SPARK-4409] Third pass of code review
75239f8 [Burak Yavuz] [SPARK-4409] Second pass of code review
e4bd0c0 [Burak Yavuz] [SPARK-4409] Modified horzcat and vertcat
65c562e [Burak Yavuz] [SPARK-4409] Hopefully fixed Java Test
d8be7bc [Burak Yavuz] [SPARK-4409] Organized imports
065b531 [Burak Yavuz] [SPARK-4409] First pass after code review
a8120d2 [Burak Yavuz] [SPARK-4409] Finished updates to API according to SPARK-4614
f798c82 [Burak Yavuz] [SPARK-4409] Updated API according to SPARK-4614
c75f3cd [Burak Yavuz] [SPARK-4409] Added JavaAPI Tests, and fixed a couple of bugs
d662f9d [Burak Yavuz] [SPARK-4409] Modified according to remote repo
83dfe37 [Burak Yavuz] [SPARK-4409] Scalastyle error fixed
a14c0da [Burak Yavuz] [SPARK-4409] Initial commit to add methods
SPARK-4968: takeOrdered to skip reduce step in case mappers return no partitions

takeOrdered should skip reduce step in case mapped RDDs have no partitions. This prevents the mentioned exception :

4. run query
SELECT * FROM testTable WHERE market = 'market2' ORDER BY End_Time DESC LIMIT 100;
Error trace
java.lang.UnsupportedOperationException: empty collection
at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:863)
at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:863)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.reduce(RDD.scala:863)
at org.apache.spark.rdd.RDD.takeOrdered(RDD.scala:1136)

Author: Yash Datta <Yash.Datta@guavus.com>

Closes #3830 from saucam/fix_takeorder and squashes the following commits:

5974d10 [Yash Datta] SPARK-4968: takeOrdered to skip reduce step in case mappers return no partitions