Adding STDDEV support for DataFrame using 1-pass online /parallel algorithm to compute variance. Please review the code change.

Author: JihongMa <linlin200605@gmail.com>
Author: Jihong MA <linlin200605@gmail.com>
Author: Jihong MA <jihongma@jihongs-mbp.usca.ibm.com>
Author: Jihong MA <jihongma@Jihongs-MacBook-Pro.local>

Closes #6297 from JihongMA/SPARK-SQL.

Fix a few Java API test style issues: unused generic types, exceptions, wrong assert argument order

Author: Sean Owen <sowen@cloudera.com>

Closes #8706 from srowen/SPARK-10547.

https://issues.apache.org/jira/browse/SPARK-10554

Fixes NPE when ShutdownHook tries to cleanup temporary folders

Author: Nithin Asokan <Nithin.Asokan@Cerner.com>

Closes #8720 from nasokan/SPARK-10554.

[SPARK-10566] [CORE] SnappyCompressionCodec init exception handling masks important error information

When throwing an IllegalArgumentException in SnappyCompressionCodec.init, chain the existing exception. This allows potentially important debugging info to be passed to the user.

Manual testing shows the exception chained properly, and the test suite still looks fine as well.

This contribution is my original work and I license the work to the project under the project's open source license.

Author: Daniel Imfeld <daniel@danielimfeld.com>

Closes #8725 from dimfeld/dimfeld-patch-1.

This PR addresses (SPARK-9014)[https://issues.apache.org/jira/browse/SPARK-9014]
Added functionality: `Column` object in Python now supports exponential operator `**`
Example:
```
from pyspark.sql import *
df = sqlContext.createDataFrame([Row(a=2)])
df.select(3**df.a,df.a**3,df.a**df.a).collect()
```
Outputs:
```
[Row(POWER(3.0, a)=9.0, POWER(a, 3.0)=8.0, POWER(a, a)=4.0)]
```

Author: 0x0FFF <programmerag@gmail.com>

Closes #8658 from 0x0FFF/SPARK-9014.

This commit ensures if an assertion fails within a thread, it will ultimately fail the test. Otherwise we end up potentially masking real bugs by not propagating assertion failures properly.

Author: Andrew Or <andrew@databricks.com>

Closes #8723 from andrewor14/fix-threading-suite.

1. Hide `LocalNodeIterator` behind the `LocalNode#asIterator` method
2. Add tests for this

Author: Andrew Or <andrew@databricks.com>

Closes #8708 from andrewor14/local-hash-join-follow-up.

[SPARK-9992] [SPARK-9994] [SPARK-9998] [SQL] Implement the local TopK, sample and intersect operators

This PR is in conflict with #8535. I will update this one when #8535 gets merged.

Author: zsxwing <zsxwing@gmail.com>

Closes #8573 from zsxwing/more-local-operators.

[SPARK-7142] [SQL] Minor enhancement to BooleanSimplification Optimizer rule. Incorporate review comments

Adding changes suggested by cloud-fan  in #5700

cc marmbrus

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

Closes #8716 from saucam/bool_simp.

When we cast string to boolean in hive, it returns `true` if the length of string is > 0, and spark SQL follows this behavior.

However, this behavior is very different from other SQL systems:

1. [presto](https://github.com/facebook/presto/blob/master/presto-main/src/main/java/com/facebook/presto/type/VarcharOperators.java#L89-L118) will return `true` for 't' 'true' '1', `false` for 'f' 'false' '0', throw exception for others.
2. [redshift](http://docs.aws.amazon.com/redshift/latest/dg/r_Boolean_type.html) will return `true` for 't' 'true' 'y' 'yes' '1', `false` for 'f' 'false' 'n' 'no' '0', null for others.
3. [postgresql](http://www.postgresql.org/docs/devel/static/datatype-boolean.html) will return `true` for 't' 'true' 'y' 'yes' 'on' '1', `false` for 'f' 'false' 'n' 'no' 'off' '0', throw exception for others.
4. [vertica](https://my.vertica.com/docs/5.0/HTML/Master/2983.htm) will return `true` for 't' 'true' 'y' 'yes' '1', `false` for 'f' 'false' 'n' 'no' '0', null for others.
5. [impala](http://www.cloudera.com/content/cloudera/en/documentation/cloudera-impala/latest/topics/impala_boolean.html) throw exception when try to cast string to boolean.
6. mysql, oracle, sqlserver don't have boolean type

Whether we should change the cast behavior according to other SQL system or not is not decided yet, this PR is a test to see if we changed, how many compatibility tests will fail.

Author: Wenchen Fan <cloud0fan@outlook.com>

Closes #8698 from cloud-fan/string2boolean.

Just fixing a typo in exception message, raised when attempting to pickle SparkContext.

Author: Icaro Medeiros <icaro.medeiros@gmail.com>

Closes #8724 from icaromedeiros/master.

See this thread for background:
http://search-hadoop.com/m/q3RTt0rWvIkHAE81

We should check the range of partition Id and provide meaningful message through exception.

Alternatively, we can use abs() and modulo to force the partition Id into legitimate range. However, expectation is that user should correct the logic error in his / her code.

Author: tedyu <yuzhihong@gmail.com>

Closes #8703 from tedyu/master.

jira: https://issues.apache.org/jira/browse/SPARK-8530

add python API for MinMaxScaler
jira for MinMaxScaler: https://issues.apache.org/jira/browse/SPARK-7514

Author: Yuhao Yang <hhbyyh@gmail.com>

Closes #7150 from hhbyyh/pythonMinMax.

If hadoopFsRelationSuites's "test all data types" is too flaky we can disable it for now.

https://issues.apache.org/jira/browse/SPARK-10540

Author: Yin Huai <yhuai@databricks.com>

Closes #8705 from yhuai/SPARK-10540-ignore.

Changes:
* Make Scala doc for StringIndexerInverse clearer.  Also remove Scala doc from transformSchema, so that the doc is inherited.
* MetadataUtils.scala: “ Helper utilities for tree-based algorithms” —> not just trees anymore

CC: holdenk mengxr

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

Closes #8679 from jkbradley/doc-fixes-1.5.

We should document options in public API doc. Otherwise, it is hard to find out the options without looking at the code. I tried to make `DefaultSource` private and put the documentation to package doc. However, since then there exists no public class under `source.libsvm`, the Java package doc doesn't show up in the generated html file (http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4492654). So I put the doc to `DefaultSource` instead. There are several minor updates in this PR:

1. Do `vectorType == "sparse"` only once.
2. Update `hashCode` and `equals`.
3. Remove inherited doc.
4. Delete temp dir in `afterAll`.

Lewuathe

Author: Xiangrui Meng <meng@databricks.com>

Closes #8699 from mengxr/SPARK-10537.

Add Python API for ```MultilayerPerceptronClassifier```.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8067 from yanboliang/SPARK-9773.

LinearRegression and LogisticRegression lack of some Params for Python, and some Params are not shared classes which lead we need to write them for each class. These kinds of Params are list here:
```scala
HasElasticNetParam
HasFitIntercept
HasStandardization
HasThresholds
```
Here we implement them in shared params at Python side and make LinearRegression/LogisticRegression parameters peer with Scala one.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8508 from yanboliang/spark-10026.

[SPARK-10518] [DOCS] Update code examples in spark.ml user guide to use LIBSVM data source instead of MLUtils

I fixed to use LIBSVM data source in the example code in spark.ml instead of MLUtils

Author: y-shimizu <y.shimizu0429@gmail.com>

Closes #8697 from y-shimizu/SPARK-10518.

Previously, project/plugins.sbt explicitly set scalaVersion to 2.10.4. This can cause issues when using a version of sbt that is compiled against a different version of Scala (for example sbt 0.13.9 uses 2.10.5). Removing this explicit setting will cause build files to be compiled and run against the same version of Scala that sbt is compiled against.

Note that this only applies to the project build files (items in project/), it is distinct from the version of Scala we target for the actual spark compilation.

Author: Ahir Reddy <ahirreddy@gmail.com>

Closes #8709 from ahirreddy/sbt-scala-version-fix.

Before this fix, `MyDenseVectorUDT.typeName` gives `mydensevecto`, which is not desirable.

Author: Cheng Lian <lian@databricks.com>

Closes #8640 from liancheng/spark-10472/udt-type-name.

Missing method of ml.feature are listed here:
```StringIndexer``` lacks of parameter ```handleInvalid```.
```StringIndexerModel``` lacks of method ```labels```.
```VectorIndexerModel``` lacks of methods ```numFeatures``` and ```categoryMaps```.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8313 from yanboliang/spark-10027.

[SPARK-10023] [ML] [PySpark] Unified DecisionTreeParams checkpointInterval between Scala and Python API.

"checkpointInterval" is member of DecisionTreeParams in Scala API which is inconsistency with Python API, we should unified them.
```
member of DecisionTreeParams <-> Scala API
shared param for all ML Transformer/Estimator <-> Python API
```
Proposal:
"checkpointInterval" is also used by ALS, so we make it shared params at Scala.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8528 from yanboliang/spark-10023.

ShuffleManager implementations are currently not given type information for
the key, value and combiner classes. Serialization of shuffle objects relies
on objects being JavaSerializable, with methods defined for reading/writing
the object or, alternatively, serialization via Kryo which uses reflection.

Serialization systems like Avro, Thrift and Protobuf generate classes with
zero argument constructors and explicit schema information
(e.g. IndexedRecords in Avro have get, put and getSchema methods).

By serializing the key, value and combiner class names in ShuffleDependency,
shuffle implementations will have access to schema information when
registerShuffle() is called.

Author: Matt Massie <massie@cs.berkeley.edu>

Closes #7403 from massie/shuffle-classtags.

pyspark.sql.types.Row implements ```__getitem__```

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8333 from yanboliang/spark-7544.

This change brings it to par with `branch-1.5` (and 1.5.0 release)

Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>

Closes #8704 from shivaram/ec2-1.5-update.

`LeftOutputIterator` and `RightOutputIterator` are symmetrically identical and can share a lot of code. If someone makes a change in one but forgets to do the same thing in the other we'll end up with inconsistent behavior. This patch also adds inline comments to clarify the intention of the code.

Author: Andrew Or <andrew@databricks.com>

Closes #8596 from andrewor14/smoj-cleanup.

this PR :
1.  Enhance reflection in RBackend. Automatically matching a Java array to Scala Seq when finding methods. Util functions like seq(), listToSeq() in R side can be removed, as they will conflict with the Serde logic that transferrs a Scala seq to R side.

2.  Enhance the SerDe to support transferring  a Scala seq to R side. Data of ArrayType in DataFrame
after collection is observed to be of Scala Seq type.

3.  Support ArrayType in createDataFrame().

Author: Sun Rui <rui.sun@intel.com>

Closes #8458 from sun-rui/SPARK-10049.

This PR includes the following changes:
- Add SQLConf to LocalNode
- Add HashJoinNode
- Add ConvertToUnsafeNode and ConvertToSafeNode.scala to test unsafe hash join.

Author: zsxwing <zsxwing@gmail.com>

Closes #8535 from zsxwing/SPARK-9990.

[SPARK-10514] [MESOS] waiting for min no of total cores acquired by Spark by implementing the sufficientResourcesRegistered method

spark.scheduler.minRegisteredResourcesRatio configuration parameter works for YARN mode but not for Mesos Coarse grained mode.

If the parameter specified default value of 0 will be set for spark.scheduler.minRegisteredResourcesRatio in base class and this method will always return true.

There are no existing test for YARN mode too. Hence not added test for the same.

Author: Akash Mishra <akash.mishra20@gmail.com>

Closes #8672 from SleepyThread/master.

This is a regression introduced in #4960, this commit fixes it and adds a test.

tnachen andrewor14 please review, this should be an easy one.

Author: Iulian Dragos <jaguarul@gmail.com>

Closes #8653 from dragos/issue/mesos/fine-grained-maxExecutorCores.

The architecture is that, in YARN mode, if the driver detects that an executor has disconnected, it asks the ApplicationMaster why the executor died. If the ApplicationMaster is aware that the executor died because of preemption, all tasks associated with that executor are not marked as failed. The executor
is still removed from the driver's list of available executors, however.

There's a few open questions:
1. Should standalone mode have a similar "get executor loss reason" as well? I localized this change as much as possible to affect only YARN, but there could be a valid case to differentiate executor losses in standalone mode as well.
2. I make a pretty strong assumption in YarnAllocator that getExecutorLossReason(executorId) will only be called once per executor id; I do this so that I can remove the metadata from the in-memory map to avoid object accumulation. It's not clear if I'm being overly zealous to save space, however.

cc vanzin specifically for review because it collided with some earlier YARN scheduling work.
cc JoshRosen because it's similar to output commit coordination we did in the past
cc andrewor14 for our discussion on how to get executor exit codes and loss reasons

Author: mcheah <mcheah@palantir.com>

Closes #8007 from mccheah/feature/preemption-handling.

From JIRA:
Add documentation for tungsten-sort.
From the mailing list "I saw a new "spark.shuffle.manager=tungsten-sort" implemented in
https://issues.apache.org/jira/browse/SPARK-7081, but it can't be found its
corresponding description in
http://people.apache.org/~pwendell/spark-releases/spark-1.5.0-rc3-docs/configuration.html(Currenlty
there are only 'sort' and 'hash' two options)."

Author: Holden Karau <holden@pigscanfly.ca>

Closes #8638 from holdenk/SPARK-10469-document-tungsten-sort.

Data Spill with UnsafeRow causes assert failure.

```
java.lang.AssertionError: assertion failed
	at scala.Predef$.assert(Predef.scala:165)
	at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2.writeKey(UnsafeRowSerializer.scala:75)
	at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:180)
	at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2$$anonfun$apply$1.apply(ExternalSorter.scala:688)
	at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2$$anonfun$apply$1.apply(ExternalSorter.scala:687)
	at scala.collection.Iterator$class.foreach(Iterator.scala:727)
	at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
	at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2.apply(ExternalSorter.scala:687)
	at org.apache.spark.util.collection.ExternalSorter$$anonfun$writePartitionedFile$2.apply(ExternalSorter.scala:683)
	at scala.collection.Iterator$class.foreach(Iterator.scala:727)
	at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
	at org.apache.spark.util.collection.ExternalSorter.writePartitionedFile(ExternalSorter.scala:683)
	at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:80)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
	at org.apache.spark.scheduler.Task.run(Task.scala:88)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
```

To reproduce that with code (thanks andrewor14):
```scala
bin/spark-shell --master local
  --conf spark.shuffle.memoryFraction=0.005
  --conf spark.shuffle.sort.bypassMergeThreshold=0

sc.parallelize(1 to 2 * 1000 * 1000, 10)
  .map { i => (i, i) }.toDF("a", "b").groupBy("b").avg().count()
```

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

Closes #8635 from chenghao-intel/unsafe_spill.

Author: Cheng Lian <lian@databricks.com>

Closes #8670 from liancheng/spark-10301/address-pr-comments.

Use these in the optimizer as well:

            A and (not(A) or B) => A and B
            not(A and B) => not(A) or not(B)
            not(A or B) => not(A) and not(B)

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

Closes #5700 from saucam/bool_simp.

The reason for this extra copy is that we iterate the array twice: calculate elements data size and copy elements to array buffer.

A simple solution is to follow `createCodeForStruct`, we can dynamically grow the buffer when needed and thus don't need to know the data size ahead.

This PR also include some typo and style fixes, and did some minor refactor to make sure `input.primitive` is always variable name not code when generate unsafe code.

Author: Wenchen Fan <cloud0fan@outlook.com>

Closes #8496 from cloud-fan/avoid-copy.

Location of JIRAError has moved between old and new versions of python-jira package.
Longer term it probably makes sense to pin to specific versions (as mentioned in https://issues.apache.org/jira/browse/SPARK-10498 ) but for now, making release tools works with both new and old versions of python-jira.

Author: Holden Karau <holden@pigscanfly.ca>

Closes #8661 from holdenk/SPARK-10497-release-utils-does-not-work-with-new-jira-python.

Small typo in the example for `LabelledPoint` in the MLLib docs.

Author: Sean Paradiso <seanparadiso@gmail.com>

Closes #8680 from sparadiso/docs_mllib_smalltypo.

Add Python API for ml.feature.VectorSlicer.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8102 from yanboliang/SPARK-9772.