[SPARK-4420][SQL] Change nullability of Cast from DoubleType/FloatType to DecimalType.

This is follow-up of [SPARK-4390](https://issues.apache.org/jira/browse/SPARK-4390) (#3256).

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

Closes #3278 from ueshin/issues/SPARK-4420 and squashes the following commits:

7fea558 [Takuya UESHIN] Add some tests.
cb2301a [Takuya UESHIN] Fix tests.
133bad5 [Takuya UESHIN] Change nullability of Cast from DoubleType/FloatType to DecimalType.
[SPARK-4425][SQL] Handle NaN or Infinity cast to Timestamp correctly.

`Cast` from `NaN` or `Infinity` of `Double` or `Float` to `TimestampType` throws `NumberFormatException`.

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

Closes #3283 from ueshin/issues/SPARK-4425 and squashes the following commits:

14def0c [Takuya UESHIN] Fix Cast to be able to handle NaN or Infinity to TimestampType.
[SQL] Construct the MutableRow from an Array

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

Closes #3217 from chenghao-intel/mutablerow and squashes the following commits:

e8a10bd [Cheng Hao] revert the change of Row object
4681aea [Cheng Hao] Add toMutableRow method in object Row
a751838 [Cheng Hao] Construct the MutableRow from an existed row
[SPARK-4309][SPARK-4407][SQL] Date type support for Thrift server, and fixes for complex types

This PR is exactly the same as #3178 except it reverts the `FileStatus.isDir` to `FileStatus.isDirectory` change, since it doesn't compile with Hadoop 1.

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Author: Cheng Lian <lian@databricks.com>

Closes #3298 from liancheng/date-for-thriftserver and squashes the following commits:

866037e [Cheng Lian] Revers isDirectory to isDir (it breaks Hadoop 1 profile)
6f71d0b [Cheng Lian] Makes toHiveString static
26fa955 [Cheng Lian] Fixes complex type support in Hive 0.13.1 shim
a92882a [Cheng Lian] Updates HiveShim for 0.13.1
73f442b [Cheng Lian] Adds Date support for HiveThriftServer2 (Hive 0.12.0)
[SPARK-4443][SQL] Fix statistics for external table in spark sql hive

The `totalSize` of external table  is always zero, which will influence join strategy(always use broadcast join for external table).

Author: w00228970 <wangfei1@huawei.com>

Closes #3304 from scwf/statistics and squashes the following commits:

568f321 [w00228970] fix statistics for external table
[SPARK-4448] [SQL] unwrap for the ConstantObjectInspector

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

Closes #3308 from chenghao-intel/unwrap_constant_oi and squashes the following commits:

156b500 [Cheng Hao] rebase the master
c5b20ab [Cheng Hao] unwrap for the ConstantObjectInspector
[SPARK-4453][SPARK-4213][SQL] Simplifies Parquet filter generation code

While reviewing PR #3083 and #3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification.

While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala#L213-L228)]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot.

The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type.

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Author: Cheng Lian <lian@databricks.com>

Closes #3317 from liancheng/simplify-parquet-filters and squashes the following commits:

d6a9499 [Cheng Lian] Fixes import styling issue
43760e8 [Cheng Lian] Simplifies Parquet filter generation logic
SPARK-4466: Provide support for publishing Scala 2.11 artifacts to Maven

The maven release plug-in does not have support for publishing two separate sets of artifacts for a single release. Because of the way that Scala 2.11 support in Spark works, we have to write some customized code to do this. The good news is that the Maven release API is just a thin wrapper on doing git commits and pushing artifacts to the HTTP API of Apache's Sonatype server and this might overall make our deployment easier to understand.

This was already used for the 1.2 snapshot, so I think it is working well. One other nice thing is this could be pretty easily extended to publish nightly snapshots.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #3332 from pwendell/releases and squashes the following commits:

2fedaed [Patrick Wendell] Automate the opening and closing of Sonatype repos
e2a24bb [Patrick Wendell] Fixing issue where we overrode non-spark version numbers
9df3a50 [Patrick Wendell] Adding TODO
1cc1749 [Patrick Wendell] Don't build the thriftserver for 2.11
933201a [Patrick Wendell] Make tagging of release commit eager
d0388a6 [Patrick Wendell] Support Scala 2.11 build
4f4dc62 [Patrick Wendell] Change to 2.11 should not be included when committing new patch
bf742e1 [Patrick Wendell] Minor fixes
ffa1df2 [Patrick Wendell] Adding a Scala 2.11 package to test it
9ac4381 [Patrick Wendell] Addressing TODO
b3105ff [Patrick Wendell] Removing commented out code
d906803 [Patrick Wendell] Small fix
3f4d985 [Patrick Wendell] More work
fcd54c2 [Patrick Wendell] Consolidating use of keys
df2af30 [Patrick Wendell] Changes to release stuff
Merge branch 'master' of git://git.apache.org/spark into add-triple-slash-testcase
Fixed wrong grammar in comment