Indent license header properly for interfaces.scala.

A very small nit update.

Author: Reynold Xin <rxin@databricks.com>

Closes #3552 from rxin/license-header and squashes the following commits:

df8d1a4 [Reynold Xin] Indent license header properly for interfaces.scala.
[SPARK-4536][SQL] Add sqrt and abs to Spark SQL DSL

Spark SQL has embeded sqrt and abs but DSL doesn't support those functions.

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

Closes #3401 from sarutak/dsl-missing-operator and squashes the following commits:

07700cf [Kousuke Saruta] Modified Literal(null, NullType) to Literal(null) in DslQuerySuite
8f366f8 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
1b88e2e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator
0396f89 [Kousuke Saruta] Added sqrt and abs to Spark SQL DSL
[SPARK-4663][sql]add finally to avoid resource leak

Author: baishuo <vc_java@hotmail.com>

Closes #3526 from baishuo/master-trycatch and squashes the following commits:

d446e14 [baishuo] correct the code style
b36bf96 [baishuo] correct the code style
ae0e447 [baishuo] add finally to avoid resource leak
[SPARK-4676][SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null

val jsc = new org.apache.spark.api.java.JavaSparkContext(sc)
val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc)
val nrdd = jhc.hql("select null from spark_test.for_test")
println(nrdd.schema)
Then the error is thrown as follows:
scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$)
at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43)

Author: YanTangZhai <hakeemzhai@tencent.com>
Author: yantangzhai <tyz0303@163.com>
Author: Michael Armbrust <michael@databricks.com>

Closes #3538 from YanTangZhai/MatchNullType and squashes the following commits:

e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null
896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null
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
[SPARK-4593][SQL] Return null when denominator is 0

SELECT max(1/0) FROM src
would return a very large number, which is obviously not right.
For hive-0.12, hive would return `Infinity` for 1/0, while for hive-0.13.1, it is `NULL` for 1/0.
I think it is better to keep our behavior with newer Hive version.
This PR ensures that when the divider is 0, the result of expression should be NULL, same with hive-0.13.1

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

Closes #3443 from adrian-wang/div and squashes the following commits:

2e98677 [Daoyuan Wang] fix code gen for divide 0
85c28ba [Daoyuan Wang] temp
36236a5 [Daoyuan Wang] add test cases
6f5716f [Daoyuan Wang] fix comments
cee92bd [Daoyuan Wang] avoid evaluation 2 times
22ecd9a [Daoyuan Wang] fix style
cf28c58 [Daoyuan Wang] divide fix
2dfe50f [Daoyuan Wang] return null when divider is 0 of Double type
[SPARK-4670] [SQL] wrong symbol for bitwise not

We should use `~` instead of `-` for bitwise NOT.

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

Closes #3528 from adrian-wang/symbol and squashes the following commits:

affd4ad [Daoyuan Wang] fix code gen test case
56efb79 [Daoyuan Wang] ensure bitwise NOT over byte and short persist data type
f55fbae [Daoyuan Wang] wrong symbol for bitwise not
[SPARK-4695][SQL] Get result using executeCollect

Using ```executeCollect``` to collect the result, because executeCollect is a custom implementation of collect in spark sql which better than rdd's collect

Author: wangfei <wangfei1@huawei.com>

Closes #3547 from scwf/executeCollect and squashes the following commits:

a5ab68e [wangfei] Revert "adding debug info"
a60d680 [wangfei] fix test failure
0db7ce8 [wangfei] adding debug info
184c594 [wangfei] using executeCollect instead collect
Minor nit style cleanup in GraphX.
[Release] Translate unknown author names automatically
[SPARK-4672][GraphX]Perform checkpoint() on PartitionsRDD to shorten the lineage

The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672

Iterative GraphX applications always have long lineage, while checkpoint() on EdgeRDD and VertexRDD themselves cannot shorten the lineage. In contrast, if we perform checkpoint() on their ParitionsRDD, the long lineage can be cut off. Moreover, the existing operations such as cache() in this code is performed on the PartitionsRDD, so checkpoint() should do the same way. More details and explanation can be found in the JIRA.

Author: JerryLead <JerryLead@163.com>
Author: Lijie Xu <csxulijie@gmail.com>

Closes #3549 from JerryLead/my_graphX_checkpoint and squashes the following commits:

d1aa8d8 [JerryLead] Perform checkpoint() on PartitionsRDD not VertexRDD and EdgeRDD themselves
ff08ed4 [JerryLead] Merge branch 'master' of https://github.com/apache/spark
c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark
52799e3 [Lijie Xu] Merge pull request #1 from apache/master
[SPARK-4672][GraphX]Non-transient PartitionsRDDs will lead to StackOverflow error

The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672

In a nutshell, if `val partitionsRDD` in EdgeRDDImpl and VertexRDDImpl are non-transient, the serialization chain can become very long in iterative algorithms and finally lead to the StackOverflow error. More details and explanation can be found in the JIRA.

Author: JerryLead <JerryLead@163.com>
Author: Lijie Xu <csxulijie@gmail.com>

Closes #3544 from JerryLead/my_graphX and squashes the following commits:

628f33c [JerryLead] set PartitionsRDD to be transient in EdgeRDDImpl and VertexRDDImpl
c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark
52799e3 [Lijie Xu] Merge pull request #1 from apache/master
[SPARK-4672][Core]Checkpoint() should clear f to shorten the serialization chain

The related JIRA is https://issues.apache.org/jira/browse/SPARK-4672

The f closure of `PartitionsRDD(ZippedPartitionsRDD2)` contains a `$outer` that references EdgeRDD/VertexRDD, which causes task's serialization chain become very long in iterative GraphX applications. As a result, StackOverflow error will occur. If we set "f = null" in `clearDependencies()`, checkpoint() can cut off the long serialization chain. More details and explanation can be found in the JIRA.

Author: JerryLead <JerryLead@163.com>
Author: Lijie Xu <csxulijie@gmail.com>

Closes #3545 from JerryLead/my_core and squashes the following commits:

f7faea5 [JerryLead] checkpoint() should clear the f to avoid StackOverflow error
c0169da [JerryLead] Merge branch 'master' of https://github.com/apache/spark
52799e3 [Lijie Xu] Merge pull request #1 from apache/master
[SPARK-4397][Core] Change the 'since' value of '@deprecated' to '1.3.0'

As #3262 wasn't merged to branch 1.2, the `since` value of `deprecated` should be '1.3.0'.

Author: zsxwing <zsxwing@gmail.com>

Closes #3573 from zsxwing/SPARK-4397-version and squashes the following commits:

1daa03c [zsxwing] Change the 'since' value to '1.3.0'
[SPARK-4710] [mllib] Eliminate MLlib compilation warnings

Renamed StreamingKMeans to StreamingKMeansExample to avoid warning about name conflict with StreamingKMeans class.

Added import to DecisionTreeRunner to eliminate warning.

CC: mengxr

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

Closes #3568 from jkbradley/ml-compilation-warnings and squashes the following commits:

64d6bc4 [Joseph K. Bradley] Updated DecisionTreeRunner.scala and StreamingKMeans.scala to eliminate compilation warnings, including renaming StreamingKMeans to StreamingKMeansExample.
[SPARK-4708][MLLib] Make k-mean runs two/three times faster with dense/sparse sample

Note that the usage of `breezeSquaredDistance` in
`org.apache.spark.mllib.util.MLUtils.fastSquaredDistance`
is in the critical path, and `breezeSquaredDistance` is slow.
We should replace it with our own implementation.

Here is the benchmark against mnist8m dataset.

Before
DenseVector: 70.04secs
SparseVector: 59.05secs

With this PR
DenseVector: 30.58secs
SparseVector: 21.14secs

Author: DB Tsai <dbtsai@alpinenow.com>

Closes #3565 from dbtsai/kmean and squashes the following commits:

08bc068 [DB Tsai] restyle
de24662 [DB Tsai] address feedback
b185a77 [DB Tsai] cleanup
4554ddd [DB Tsai] first commit
[SPARK-4717][MLlib] Optimize BLAS library to avoid de-reference multiple times in loop

Have a local reference to `values` and `indices` array in the `Vector` object
so JVM can locate the value with one operation call. See `SPARK-4581`
for similar optimization, and the bytecode analysis.

Author: DB Tsai <dbtsai@alpinenow.com>

Closes #3577 from dbtsai/blasopt and squashes the following commits:

62d38c4 [DB Tsai] formating
0316cef [DB Tsai] first commit