[SPARK-4880] remove spark.locality.wait in Analytics

spark.locality.wait set to 100000 in examples/graphx/Analytics.scala.
Should be left to the user.

Author: Ernest <earneyzxl@gmail.com>

Closes #3730 from Earne/SPARK-4880 and squashes the following commits:

d79ed04 [Ernest] remove spark.locality.wait in Analytics
[SPARK-4884]: Improve Partition docs

Rewording was based on this discussion: http://apache-spark-developers-list.1001551.n3.nabble.com/RDD-data-flow-td9804.html
This is the associated JIRA ticket: https://issues.apache.org/jira/browse/SPARK-4884

Author: Madhu Siddalingaiah <madhu@madhu.com>

Closes #3722 from msiddalingaiah/master and squashes the following commits:

79e679f [Madhu Siddalingaiah] [DOC]: improve documentation
51d14b9 [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master'
38faca4 [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master'
cbccbfe [Madhu Siddalingaiah] Documentation: replace <b> with <code> (again)
332f7a2 [Madhu Siddalingaiah] Documentation: replace <b> with <code>
cd2b05a [Madhu Siddalingaiah] Merge remote-tracking branch 'upstream/master'
0fc12d7 [Madhu Siddalingaiah] Documentation: add description for repartitionAndSortWithinPartitions
SPARK-4743 - Use SparkEnv.serializer instead of closureSerializer in aggregateByKey and foldByKey

Author: Ivan Vergiliev <ivan@leanplum.com>

Closes #3605 from IvanVergiliev/change-serializer and squashes the following commits:

a49b7cf [Ivan Vergiliev] Use serializer instead of closureSerializer in aggregate/foldByKey.
[SPARK-4837] NettyBlockTransferService should use spark.blockManager.port config

This is used in NioBlockTransferService here:
https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/network/nio/NioBlockTransferService.scala#L66

Author: Aaron Davidson <aaron@databricks.com>

Closes #3688 from aarondav/SPARK-4837 and squashes the following commits:

ebd2007 [Aaron Davidson] [SPARK-4837] NettyBlockTransferService should use spark.blockManager.port config
[SPARK-4754] Refactor SparkContext into ExecutorAllocationClient

This is such that the `ExecutorAllocationManager` does not take in the `SparkContext` with all of its dependencies as an argument. This prevents future developers of this class to tie down this class further with the `SparkContext`, which has really become quite a monstrous object.

cc'ing pwendell who originally suggested this, and JoshRosen who may have thoughts about the trait mix-in style of `SparkContext`.

Author: Andrew Or <andrew@databricks.com>

Closes #3614 from andrewor14/dynamic-allocation-sc and squashes the following commits:

187070d [Andrew Or] Merge branch 'master' of github.com:apache/spark into dynamic-allocation-sc
59baf6c [Andrew Or] Merge branch 'master' of github.com:apache/spark into dynamic-allocation-sc
347a348 [Andrew Or] Refactor SparkContext into ExecutorAllocationClient
[SPARK-2663] [SQL] Support the Grouping Set

Add support for `GROUPING SETS`, `ROLLUP`, `CUBE` and the the virtual column `GROUPING__ID`.

More details on how to use the `GROUPING SETS" can be found at: https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation,+Cube,+Grouping+and+Rollup
https://issues.apache.org/jira/secure/attachment/12676811/grouping_set.pdf

The generic idea of the implementations are :
1 Replace the `ROLLUP`, `CUBE` with `GROUPING SETS`
2 Explode each of the input row, and then feed them to `Aggregate`
  * Each grouping set are represented as the bit mask for the `GroupBy Expression List`, for each bit, `1` means the expression is selected, otherwise `0` (left is the lower bit, and right is the higher bit in the `GroupBy Expression List`)
  * Several of projections are constructed according to the grouping sets, and within each projection(Seq[Expression), we replace those expressions with `Literal(null)` if it's not selected in the grouping set (based on the bit mask)
  * Output Schema of `Explode` is `child.output :+ grouping__id`
  * GroupBy Expressions of `Aggregate` is `GroupBy Expression List :+ grouping__id`
  * Keep the `Aggregation expressions` the same for the `Aggregate`

The expressions substitutions happen in Logic Plan analyzing, so we will benefit from the Logical Plan optimization (e.g. expression constant folding, and map side aggregation etc.), Only an `Explosive` operator added for Physical Plan, which will explode the rows according the pre-set projections.

A known issue will be done in the follow up PR:
* Optimization `ColumnPruning` is not supported yet for `Explosive` node.

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

Closes #1567 from chenghao-intel/grouping_sets and squashes the following commits:

fe65fcc [Cheng Hao] Remove the extra space
3547056 [Cheng Hao] Add more doc and Simplify the Expand
a7c869d [Cheng Hao] update code as feedbacks
d23c672 [Cheng Hao] Add GroupingExpression to replace the Seq[Expression]
414b165 [Cheng Hao] revert the unnecessary changes
ec276c6 [Cheng Hao] Support Rollup/Cube/GroupingSets
[SPARK-3928][SQL] Support wildcard matches on Parquet files.

...arquetFile accept hadoop glob pattern in path.

Author: Thu Kyaw <trk007@gmail.com>

Closes #3407 from tkyaw/master and squashes the following commits:

19115ad [Thu Kyaw] Merge https://github.com/apache/spark
ceded32 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
d322c28 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
ce677c6 [Thu Kyaw] [SPARK-3928][SQL] Support wildcard matches on Parquet files.
[SPARK-4756][SQL] FIX: sessionToActivePool grow infinitely, even as sessions expire

**sessionToActivePool** in **SparkSQLOperationManager** grow infinitely, even as sessions expire.
we should remove the pool value when the session closed, even though **sessionToActivePool** would not exist in all of sessions.

Author: guowei2 <guowei2@asiainfo.com>

Closes #3617 from guowei2/SPARK-4756 and squashes the following commits:

e9b97b8 [guowei2] fix compile bug with Shim12
cf0f521 [guowei2] Merge remote-tracking branch 'apache/master' into SPARK-4756
e070998 [guowei2] fix: remove active pool of the session when it expired
[SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references

The sql "select * from spark_test::for_test where abs(20141202) is not null" has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)) and
partitionKeyIds=AttributeSet(). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)). Then the exception "java.lang.IllegalArgumentException: requirement failed: Partition pruning predicates only supported for partitioned tables." is thrown.
The sql "select * from spark_test::for_test_partitioned_table where abs(20141202) is not null and type_id=11 and platform = 3" with partitioned key insert_date has predicates=List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202), (type_id#12 = 11), (platform#8 = 3)) and partitionKeyIds=AttributeSet(insert_date#24). PruningPredicates is List(IS NOT NULL HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFAbs(20141202)).

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

Closes #3556 from YanTangZhai/SPARK-4693 and squashes the following commits:

620ebe3 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references
37cfdf5 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references
70a3544 [yantangzhai] [SPARK-4693] [SQL] PruningPredicates may be wrong if predicates contains an empty AttributeSet() references
efa9b03 [YanTangZhai] Update HiveQuerySuite.scala
72accf1 [YanTangZhai] Update HiveQuerySuite.scala
e572b9a [YanTangZhai] Update HiveStrategies.scala
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-2554][SQL] Supporting SumDistinct partial aggregation

Adding support to the partial aggregation of SumDistinct

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #3348 from ravipesala/SPARK-2554 and squashes the following commits:

fd28e4d [ravipesala] Fixed review comments
e60e67f [ravipesala] Fixed test cases and made it as nullable
32fe234 [ravipesala] Supporting SumDistinct partial aggregation Conflicts: 	sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregates.scala
[SPARK-4573] [SQL] Add SettableStructObjectInspector support in "wrap" function

Hive UDAF may create an customized object constructed by SettableStructObjectInspector, this is critical when integrate Hive UDAF with the refactor-ed UDAF interface.

Performance issue in `wrap/unwrap` since more match cases added, will do it in another PR.

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

Closes #3429 from chenghao-intel/settable_oi and squashes the following commits:

9f0aff3 [Cheng Hao] update code style issues as feedbacks
2b0561d [Cheng Hao] Add more scala doc
f5a40e8 [Cheng Hao] add scala doc
2977e9b [Cheng Hao] remove the timezone setting for test suite
3ed284c [Cheng Hao] fix the date type comparison
f1b6749 [Cheng Hao] Update the comment
932940d [Cheng Hao] Add more unit test
72e4332 [Cheng Hao] Add settable StructObjectInspector support
[SPARK-4861][SQL] Refactory command in spark sql

Remove ```Command``` and use ```RunnableCommand``` instead.

Author: wangfei <wangfei1@huawei.com>
Author: scwf <wangfei1@huawei.com>

Closes #3712 from scwf/cmd and squashes the following commits:

51a82f2 [wangfei] fix test failure
0e03be8 [wangfei] address comments
4033bed [scwf] remove CreateTableAsSelect in hivestrategy
5d20010 [wangfei] address comments
125f542 [scwf] factory command in spark sql