SPARK-4445, Don't display storage level in toDebugString unless RDD is persisted.

Author: Prashant Sharma <prashant.s@imaginea.com>

Closes #3310 from ScrapCodes/SPARK-4445/rddDebugStringFix and squashes the following commits:

4e57c52 [Prashant Sharma] SPARK-4445, Don't display storage level in toDebugString unless RDD is persisted
SPARK-2811 upgrade algebird to 0.8.1

Author: Adam Pingel <adam@axle-lang.org>

Closes #3282 from adampingel/master and squashes the following commits:

70c8d3c [Adam Pingel] relocate the algebird example back to example/src
7a9d8be [Adam Pingel] SPARK-2811 upgrade algebird to 0.8.1
[SPARK-4444] Drop VD type parameter from EdgeRDD

Due to vertex attribute caching, EdgeRDD previously took two type parameters: ED and VD. However, this is an implementation detail that should not be exposed in the interface, so this PR drops the VD type parameter.

This requires removing the `filter` method from the EdgeRDD interface, because it depends on vertex attribute caching.

Author: Ankur Dave <ankurdave@gmail.com>

Closes #3303 from ankurdave/edgerdd-drop-tparam and squashes the following commits:

38dca9b [Ankur Dave] Leave EdgeRDD.fromEdges public
fafeb51 [Ankur Dave] Drop VD type parameter from EdgeRDD
Revert "[SPARK-4075] [Deploy] Jar url validation is not enough for Jar file"

This reverts commit 098f83c7ccd7dad9f9228596da69fe5f55711a52.
[DOCS][SQL] Fix broken link to Row class scaladoc

Author: Andy Konwinski <andykonwinski@gmail.com>

Closes #3323 from andyk/patch-2 and squashes the following commits:

4699fdc [Andy Konwinski] Fix broken link to Row class scaladoc
[SPARK-4180] [Core] Prevent creation of multiple active SparkContexts

This patch adds error-detection logic to throw an exception when attempting to create multiple active SparkContexts in the same JVM, since this is currently unsupported and has been known to cause confusing behavior (see SPARK-2243 for more details).

**The solution implemented here is only a partial fix.**  A complete fix would have the following properties:

1. Only one SparkContext may ever be under construction at any given time.
2. Once a SparkContext has been successfully constructed, any subsequent construction attempts should fail until the active SparkContext is stopped.
3. If the SparkContext constructor throws an exception, then all resources created in the constructor should be cleaned up (SPARK-4194).
4. If a user attempts to create a SparkContext but the creation fails, then the user should be able to create new SparkContexts.

This PR only provides 2) and 4); we should be able to provide all of these properties, but the correct fix will involve larger changes to SparkContext's construction / initialization, so we'll target it for a different Spark release.

### The correct solution:

I think that the correct way to do this would be to move the construction of SparkContext's dependencies into a static method in the SparkContext companion object.  Specifically, we could make the default SparkContext constructor `private` and change it to accept a `SparkContextDependencies` object that contains all of SparkContext's dependencies (e.g. DAGScheduler, ContextCleaner, etc.).  Secondary constructors could call a method on the SparkContext companion object to create the `SparkContextDependencies` and pass the result to the primary SparkContext constructor.  For example:

```scala
class SparkContext private (deps: SparkContextDependencies) {
  def this(conf: SparkConf) {
    this(SparkContext.getDeps(conf))
  }
}

object SparkContext(
  private[spark] def getDeps(conf: SparkConf): SparkContextDependencies = synchronized {
    if (anotherSparkContextIsActive) { throw Exception(...) }
    var dagScheduler: DAGScheduler = null
    try {
        dagScheduler = new DAGScheduler(...)
        [...]
    } catch {
      case e: Exception =>
         Option(dagScheduler).foreach(_.stop())
          [...]
    }
    SparkContextDependencies(dagScheduler, ....)
  }
}
```

This gives us mutual exclusion and ensures that any resources created during the failed SparkContext initialization are properly cleaned up.

This indirection is necessary to maintain binary compatibility.  In retrospect, it would have been nice if SparkContext had no private constructors and could only be created through builder / factory methods on its companion object, since this buys us lots of flexibility and makes dependency injection easier.

### Alternative solutions:

As an alternative solution, we could refactor SparkContext's primary constructor to perform all object creation in a giant `try-finally` block.  Unfortunately, this will require us to turn a bunch of `vals` into `vars` so that they can be assigned from the `try` block.  If we still want `vals`, we could wrap each `val` in its own `try` block (since the try block can return a value), but this will lead to extremely messy code and won't guard against the introduction of future code which doesn't properly handle failures.

The more complex approach outlined above gives us some nice dependency injection benefits, so I think that might be preferable to a `var`-ification.

### This PR's solution:

- At the start of the constructor, check whether some other SparkContext is active; if so, throw an exception.
- If another SparkContext might be under construction (or has thrown an exception during construction), allow the new SparkContext to begin construction but log a warning (since resources might have been leaked from a failed creation attempt).
- At the end of the SparkContext constructor, check whether some other SparkContext constructor has raced and successfully created an active context.  If so, throw an exception.

This guarantees that no two SparkContexts will ever be active and exposed to users (since we check at the very end of the constructor).  If two threads race to construct SparkContexts, then one of them will win and another will throw an exception.

This exception can be turned into a warning by setting `spark.driver.allowMultipleContexts = true`.  The exception is disabled in unit tests, since there are some suites (such as Hive) that may require more significant refactoring to clean up their SparkContexts.  I've made a few changes to other suites' test fixtures to properly clean up SparkContexts so that the unit test logs contain fewer warnings.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #3121 from JoshRosen/SPARK-4180 and squashes the following commits:

23c7123 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
d38251b [Josh Rosen] Address latest round of feedback.
c0987d3 [Josh Rosen] Accept boolean instead of SparkConf in methods.
85a424a [Josh Rosen] Incorporate more review feedback.
372d0d3 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
f5bb78c [Josh Rosen] Update mvn build, too.
d809cb4 [Josh Rosen] Improve handling of failed SparkContext creation attempts.
79a7e6f [Josh Rosen] Fix commented out test
a1cba65 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
7ba6db8 [Josh Rosen] Add utility to set system properties in tests.
4629d5c [Josh Rosen] Set spark.driver.allowMultipleContexts=true in tests.
ed17e14 [Josh Rosen] Address review feedback; expose hack workaround for existing unit tests.
1c66070 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-4180
06c5c54 [Josh Rosen] Add / improve SparkContext cleanup in streaming BasicOperationsSuite
d0437eb [Josh Rosen] StreamingContext.stop() should stop SparkContext even if StreamingContext has not been started yet.
c4d35a2 [Josh Rosen] Log long form of creation site to aid debugging.
918e878 [Josh Rosen] Document "one SparkContext per JVM" limitation.
afaa7e3 [Josh Rosen] [SPARK-4180] Prevent creations of multiple active SparkContexts.
[SQL] Makes conjunction pushdown more aggressive for in-memory table

This is inspired by the [Parquet record filter generation code](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala#L387-L400).

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Author: Cheng Lian <lian@databricks.com>

Closes #3318 from liancheng/aggresive-conj-pushdown and squashes the following commits:

78b69d2 [Cheng Lian] Makes conjunction pushdown more aggressive
[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
SPARK-4457. Document how to build for Hadoop versions greater than 2.4
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