for details, see: https://issues.apache.org/jira/browse/SPARK-3745

Author: shane knapp <incomplete@gmail.com>

Closes #2596 from shaneknapp/SPARK-3745 and squashes the following commits:

c95eea9 [shane knapp] SPARK-3745 - fix check-license to properly download and check jar

As suggested by mateiz , and because it came up on the mailing list again last week, this attempts to document that ordering of elements is not guaranteed across RDD evaluations in groupBy, zip, and partition-wise RDD methods. Suggestions welcome about the wording, or other methods that need a note.

Author: Sean Owen <sowen@cloudera.com>

Closes #2508 from srowen/SPARK-3356 and squashes the following commits:

b7c96fd [Sean Owen] Undo change to programming guide
ad4aeec [Sean Owen] Don't mention ordering in partition-wise methods, reword description of ordering for zip methods per review, and add similar note to programming guide, which mentions groupByKey (but not zip methods)
fce943b [Sean Owen] Note that ordering of elements is not guaranteed across RDD evaluations in groupBy, zip, and partition-wise RDD methods

This reverts commit 0bbe7fae.

When using spark-submit in `cluster` mode to submit a job to a Spark Standalone
cluster, if the JAVA_HOME environment variable was set on the submitting
machine then DriverRunner would attempt to use the submitter's JAVA_HOME to
launch the driver process (instead of the worker's JAVA_HOME), causing the
driver to fail unless the submitter and worker had the same Java location.

This commit fixes this by reading JAVA_HOME from sys.env instead of
command.environment.

Author: Josh Rosen <joshrosen@apache.org>

Closes #2586 from JoshRosen/SPARK-3734 and squashes the following commits:

e9513d9 [Josh Rosen] [SPARK-3734] DriverRunner should not read SPARK_HOME from submitter's environment.

The problem was that the 2nd argument in RemoveBroadcast is not tellMaster! It is "removeFromDriver". Basically when removeFromDriver is not true, we don't report broadcast block removal back to the driver, and then other executors mistakenly think that the executor would still have the block, and try to fetch from it.

cc @tdas

Author: Reynold Xin <rxin@apache.org>

Closes #2588 from rxin/debug and squashes the following commits:

6dab2e3 [Reynold Xin] Don't log random messages.
f430686 [Reynold Xin] Always report broadcast removal back to master.
2a13f70 [Reynold Xin] iii

This changes the way we send MapStatus from executors back to driver for large stages (>2000 tasks). For large stages, we no longer send one byte per block. Instead, we just send the average block size.

This makes large jobs (tens of thousands of tasks) much more reliable since the driver no longer sends huge amount of data.

Author: Reynold Xin <rxin@apache.org>

Closes #2470 from rxin/mapstatus and squashes the following commits:

822ff54 [Reynold Xin] Code review feedback.
3b86f56 [Reynold Xin] Added MimaExclude.
f89d182 [Reynold Xin] Fixed a bug in MapStatus
6a0401c [Reynold Xin] [SPARK-3613] Record only average block size in MapStatus for large stages.

Author: Reynold Xin <rxin@apache.org>

Closes #2581 from rxin/minor-cleanup and squashes the following commits:

736a91b [Reynold Xin] Minor cleanup of code.

Author: oded <oded@HP-DV6.c4internal.c4-security.com>

Closes #2486 from odedz/master and squashes the following commits:

dd7890a [oded] Fixed the condition in StronglyConnectedComponents Issue: SPARK-3635

When `numVertices > 50`, probability is set to 0. This would cause infinite loop.

Author: yingjieMiao <yingjie@42go.com>

Closes #2553 from yingjieMiao/graphx and squashes the following commits:

6adf3c8 [yingjieMiao] [graphX] GraphOps: random pick vertex bug

a new PR base on new master.  changes are the same as https://github.com/apache/spark/pull/1919

Author: baishuo(白硕) <vc_java@hotmail.com>
Author: baishuo <vc_java@hotmail.com>
Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #2226 from baishuo/patch-3007 and squashes the following commits:

e69ce88 [Cheng Lian] Adds tests to verify dynamic partitioning folder layout
b20a3dc [Cheng Lian] Addresses @yhuai's comments
096bbbc [baishuo(白硕)] Merge pull request #1 from liancheng/refactor-dp
1093c20 [Cheng Lian] Adds more tests
5004542 [Cheng Lian] Minor refactoring
fae9eff [Cheng Lian] Refactors InsertIntoHiveTable to a Command
528e84c [Cheng Lian] Fixes typo in test name, regenerated golden answer files
c464b26 [Cheng Lian] Refactors dynamic partitioning support
5033928 [baishuo] pass check style
2201c75 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name
b47c9bf [baishuo] modify according micheal's advice
c3ab36d [baishuo] modify for some bad indentation
7ce2d9f [baishuo] modify code to pass scala style checks
37c1c43 [baishuo] delete a empty else branch
66e33fc [baishuo] do a little modify
88d0110 [baishuo] update file after test
a3961d9 [baishuo(白硕)] Update Cast.scala
f7467d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala
c1a59dd [baishuo(白硕)] Update Cast.scala
0e18496 [baishuo(白硕)] Update HiveQuerySuite.scala
60f70aa [baishuo(白硕)] Update InsertIntoHiveTable.scala
0a50db9 [baishuo(白硕)] Update HiveCompatibilitySuite.scala
491c7d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala
a2374a8 [baishuo(白硕)] Update InsertIntoHiveTable.scala
701a814 [baishuo(白硕)] Update SparkHadoopWriter.scala
dc24c41 [baishuo(白硕)] Update HiveQl.scala

This is to help debug the error reported at http://apache-spark-user-list.1001560.n3.nabble.com/SQL-queries-fail-in-1-2-0-SNAPSHOT-td15327.html

Author: Reynold Xin <rxin@apache.org>

Closes #2580 from rxin/buffer-debug and squashes the following commits:

5814292 [Reynold Xin] Logging close() in case close() fails.
323dfec [Reynold Xin] Add more debug message.

Previous key comparison in `ExternalSorter` will get wrong sorting result or exception when key comparison overflows, details can be seen in [SPARK-3032](https://issues.apache.org/jira/browse/SPARK-3032). Here fix this and add a unit test to prove it.

Author: jerryshao <saisai.shao@intel.com>

Closes #2514 from jerryshao/SPARK-3032 and squashes the following commits:

6f3c302 [jerryshao] Improve the unit test according to comments
01911e6 [jerryshao] Change the test to show the contract violate exception
83acb38 [jerryshao] Minor changes according to comments
fa2a08f [jerryshao] Fix key comparison integer overflow introduced sorting exception

# All-pairs similarity via DIMSUM
Compute all pairs of similar vectors using brute force approach, and also DIMSUM sampling approach.

Laying down some notation: we are looking for all pairs of similar columns in an m x n RowMatrix whose entries are denoted a_ij, with the i’th row denoted r_i and the j’th column denoted c_j. There is an oversampling parameter labeled ɣ that should be set to 4 log(n)/s to get provably correct results (with high probability), where s is the similarity threshold.

The algorithm is stated with a Map and Reduce, with proofs of correctness and efficiency in published papers [1] [2]. The reducer is simply the summation reducer. The mapper is more interesting, and is also the heart of the scheme. As an exercise, you should try to see why in expectation, the map-reduce below outputs cosine similarities.

![dimsumv2](https://cloud.githubusercontent.com/assets/3220351/3807272/d1d9514e-1c62-11e4-9f12-3cfdb1d78b3a.png)

[1] Bosagh-Zadeh, Reza and Carlsson, Gunnar (2013), Dimension Independent Matrix Square using MapReduce, arXiv:1304.1467 http://arxiv.org/abs/1304.1467

[2] Bosagh-Zadeh, Reza and Goel, Ashish (2012), Dimension Independent Similarity Computation, arXiv:1206.2082 http://arxiv.org/abs/1206.2082

# Testing

Tests for all invocations included.

Added L1 and L2 norm computation to MultivariateStatisticalSummary since it was needed. Added tests for both of them.

Author: Reza Zadeh <rizlar@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes #1778 from rezazadeh/dimsumv2 and squashes the following commits:

404c64c [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2
4eb71c6 [Reza Zadeh] Add excludes for normL1 and normL2
ee8bd65 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2
976ddd4 [Reza Zadeh] Broadcast colMags. Avoid div by zero.
3467cff [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2
aea0247 [Reza Zadeh] Allow large thresholds to promote sparsity
9fe17c0 [Xiangrui Meng] organize imports
2196ba5 [Xiangrui Meng] Merge branch 'rezazadeh-dimsumv2' into dimsumv2
254ca08 [Reza Zadeh] Merge remote-tracking branch 'upstream/master' into dimsumv2
f2947e4 [Xiangrui Meng] some optimization
3c4cf41 [Xiangrui Meng] Merge branch 'master' into rezazadeh-dimsumv2
0e4eda4 [Reza Zadeh] Use partition index for RNG
251bb9c [Reza Zadeh] Documentation
25e9d0d [Reza Zadeh] Line length for style
fb296f6 [Reza Zadeh] renamed to normL1 and normL2
3764983 [Reza Zadeh] Documentation
e9c6791 [Reza Zadeh] New interface and documentation
613f261 [Reza Zadeh] Column magnitude summary
75a0b51 [Reza Zadeh] Use Ints instead of Longs in the shuffle
0f12ade [Reza Zadeh] Style changes
eb1dc20 [Reza Zadeh] Use Double.PositiveInfinity instead of Double.Max
f56a882 [Reza Zadeh] Remove changes to MultivariateOnlineSummarizer
dbc55ba [Reza Zadeh] Make colMagnitudes a method in RowMatrix
41e8ece [Reza Zadeh] style changes
139c8e1 [Reza Zadeh] Syntax changes
029aa9c [Reza Zadeh] javadoc and new test
75edb25 [Reza Zadeh] All tests passing!
05e59b8 [Reza Zadeh] Add test
502ce52 [Reza Zadeh] new interface
654c4fb [Reza Zadeh] default methods
3726ca9 [Reza Zadeh] Remove MatrixAlgebra
6bebabb [Reza Zadeh] remove changes to MatrixSuite
5b8cd7d [Reza Zadeh] Initial files

Similar to the work done in #2571, this PR just sorts the remaining manually-inputted dicts in the EC2 script so they are easier to maintain.

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #2578 from nchammas/ec2-dict-sort and squashes the following commits:

f55c692 [Nicholas Chammas] sort long dictionaries

Author: Zhang, Liye <liye.zhang@intel.com>

Closes #2572 from liyezhang556520/DAGLogErr and squashes the following commits:

5be2491 [Zhang, Liye] Bugfix: LogErr format in DAGScheduler.scala

Minor fixes:
* Remove unnecessary parens (Python style)
* Sort `disks_by_instance` dict and remove duplicate `t1.micro` key

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #2571 from nchammas/ec2-polish and squashes the following commits:

9d203d5 [Nicholas Chammas] paren and dict cleanup

This PR adds RandomForest to MLlib.  The implementation is basic, and future performance optimizations will be important.  (Note: RFs = Random Forests.)

# Overview

## RandomForest
* trains multiple trees at once to reduce the number of passes over the data
* allows feature subsets at each node
* uses a queue of nodes instead of fixed groups for each level

This implementation is based an implementation by manishamde and the [Alpine Labs Sequoia Forest](https://github.com/AlpineNow/SparkML2) by codedeft (in particular, the TreePoint, BaggedPoint, and node queue implementations).  Thank you for your inputs!

## Testing

Correctness: This has been tested for correctness with the test suites and with DecisionTreeRunner on example datasets.

Performance: This has been performance tested using [this branch of spark-perf](https://github.com/jkbradley/spark-perf/tree/rfs).  Results below.

### Regression tests for DecisionTree

Summary: For training 1 tree, there are small regressions, especially from feature subsampling.

In the table below, each row is a single (random) dataset.  The 2 different sets of result columns are for 2 different RF implementations:
* (numTrees): This is from an earlier commit, after implementing RandomForest to train multiple trees at once.  It does not include any code for feature subsampling.
* (feature subsets): This is from this current PR's code, after implementing feature subsampling.
These tests were to identify regressions in DecisionTree, so they are training 1 tree with all of the features (i.e., no feature subsampling).

These were run on an EC2 cluster with 15 workers, training 1 tree with maxDepth = 5 (= 6 levels).  Speedup values < 1 indicate slowdowns from the old DecisionTree implementation.

numInstances | numFeatures | runtime (sec) | speedup | runtime (sec) | speedup
---- | ---- | ---- | ---- | ---- | ----
 | | (numTrees) | (numTrees) | (feature subsets) | (feature subsets)
20000 | 100 | 4.051 | 1.044433473 | 4.478 | 0.9448414471
20000 | 500 | 8.472 | 1.104461756 | 9.315 | 1.004508857
20000 | 1500 | 19.354 | 1.05854087 | 20.863 | 0.9819776638
20000 | 3500 | 43.674 | 1.072033704 | 45.887 | 1.020332556
200000 | 100 | 4.196 | 1.171830315 | 4.848 | 1.014232673
200000 | 500 | 8.926 | 1.082791844 | 9.771 | 0.989151571
200000 | 1500 | 20.58 | 1.068415938 | 22.134 | 0.9934038131
200000 | 3500 | 48.043 | 1.075203464 | 52.249 | 0.9886505005
2000000 | 100 | 4.944 | 1.01355178 | 5.796 | 0.8645617667
2000000 | 500 | 11.11 | 1.016831683 | 12.482 | 0.9050632911
2000000 | 1500 | 31.144 | 1.017852556 | 35.274 | 0.8986789136
2000000 | 3500 | 79.981 | 1.085382778 | 101.105 | 0.8586123337
20000000 | 100 | 8.304 | 0.9270231214 | 9.073 | 0.8484514494
20000000 | 500 | 28.174 | 1.083268262 | 34.236 | 0.8914592826
20000000 | 1500 | 143.97 | 0.9579634646 | 159.275 | 0.8659111599

### Tests for forests

I have run other tests with numTrees=10 and with sqrt(numFeatures), and those indicate that multi-model training and feature subsets can speed up training for forests, especially when training deeper trees.

# Details on specific classes

## Changes to DecisionTree
* Main train() method is now in RandomForest.
* findBestSplits() is no longer needed.  (It split levels into groups, but we now use a queue of nodes.)
* Many small changes to support RFs.  (Note: These methods should be moved to RandomForest.scala in a later PR, but are in DecisionTree.scala to make code comparison easier.)

## RandomForest
* Main train() method is from old DecisionTree.
* selectNodesToSplit: Note that it selects nodes and feature subsets jointly to track memory usage.

## RandomForestModel
* Stores an Array[DecisionTreeModel]
* Prediction:
 * For classification, most common label.  For regression, mean.
 * We could support other methods later.

## examples/.../DecisionTreeRunner
* This now takes numTrees and featureSubsetStrategy, to support RFs.

## DTStatsAggregator
* 2 types of functionality (w/ and w/o subsampling features): These require different indexing methods.  (We could treat both as subsampling, but this is less efficient
  DTStatsAggregator is now abstract, and 2 child classes implement these 2 types of functionality.

## impurities
* These now take instance weights.

## Node
* Some vals changed to vars.
 * This is unfortunately a public API change (DeveloperApi).  This could be avoided by creating a LearningNode struct, but would be awkward.

## RandomForestSuite
Please let me know if there are missing tests!

## BaggedPoint
This wraps TreePoint and holds bootstrap weights/counts.

# Design decisions

* BaggedPoint: BaggedPoint is separate from TreePoint since it may be useful for other bagging algorithms later on.

* RandomForest public API: What options should be easily supported by the train* methods?  Should ALL options be in the Java-friendly constructors?  Should there be a constructor taking Strategy?

* Feature subsampling options: What options should be supported?  scikit-learn supports the same options, except for "onethird."  One option would be to allow users to specific fractions ("0.1"): the current options could be supported, and any unrecognized values would be parsed as Doubles in [0,1].

* Splits and bins are computed before bootstrapping, so all trees use the same discretization.

* One queue, instead of one queue per tree.

CC: mengxr manishamde codedeft chouqin  Please let me know if you have suggestions---thanks!

Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>
Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Author: chouqin <liqiping1991@gmail.com>

Closes #2435 from jkbradley/rfs-new and squashes the following commits:

c694174 [Joseph K. Bradley] Fixed typo
cc59d78 [Joseph K. Bradley] fixed imports
e25909f [Joseph K. Bradley] Simplified node group maps.  Specifically, created NodeIndexInfo to store node index in agg and feature subsets, and no longer create extra maps in findBestSplits
fbe9a1e [Joseph K. Bradley] Changed default featureSubsetStrategy to be sqrt for classification, onethird for regression.  Updated docs with references.
ef7c293 [Joseph K. Bradley] Updates based on code review.  Most substantial changes: * Simplified DTStatsAggregator * Made RandomForestModel.trees public * Added test for regression to RandomForestSuite
593b13c [Joseph K. Bradley] Fixed bug in metadata for computing log2(num features).  Now it checks >= 1.
a1a08df [Joseph K. Bradley] Removed old comments
866e766 [Joseph K. Bradley] Changed RandomForestSuite randomized tests to use multiple fixed random seeds.
ff8bb96 [Joseph K. Bradley] removed usage of null from RandomForest and replaced with Option
bf1a4c5 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
6b79c07 [Joseph K. Bradley] Added RandomForestSuite, and fixed small bugs, style issues.
d7753d4 [Joseph K. Bradley] Added numTrees and featureSubsetStrategy to DecisionTreeRunner (to support RandomForest).  Fixed bugs so that RandomForest now runs.
746d43c [Joseph K. Bradley] Implemented feature subsampling.  Tested DecisionTree but not RandomForest.
6309d1d [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new.  Added RandomForestModel.toString
b7ae594 [Joseph K. Bradley] Updated docs.  Small fix for bug which does not cause errors: No longer allocate unused child nodes for leaf nodes.
121c74e [Joseph K. Bradley] Basic random forests are implemented.  Random features per node not yet implemented.  Test suite not implemented.
325d18a [Joseph K. Bradley] Merge branch 'chouqin-dt-preprune' into rfs-new
4ef9bf1 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
61b2e72 [Joseph K. Bradley] Added max of 10GB for maxMemoryInMB in Strategy.
a95e7c8 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
6da8571 [Joseph K. Bradley] RFs partly implemented, not done yet
eddd1eb [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into rfs-new
5c4ac33 [Joseph K. Bradley] Added check in Strategy to make sure minInstancesPerNode >= 1
0dd4d87 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
95c479d [Joseph K. Bradley] * Fixed typo in tree suite test "do not choose split that does not satisfy min instance per node requirements" * small style fixes
e2628b6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into chouqin-dt-preprune
19b01af [Joseph K. Bradley] Merge remote-tracking branch 'chouqin/dt-preprune' into chouqin-dt-preprune
f1d11d1 [chouqin] fix typo
c7ebaf1 [chouqin] fix typo
39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test
c6e2dfc [Joseph K. Bradley] Added minInstancesPerNode and minInfoGain parameters to DecisionTreeRunner.scala and to Python API in tree.py
306120f [Joseph K. Bradley] Fixed typo in DecisionTreeModel.scala doc
eaa1dcf [Joseph K. Bradley] Added topNode doc in DecisionTree and scalastyle fix
d4d7864 [Joseph K. Bradley] Marked Node.build as deprecated
d4dbb99 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
1a8f0ad [Joseph K. Bradley] Eliminated pre-allocated nodes array in main train() method. * Nodes are constructed and added to the tree structure as needed during training.
0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree
d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1
2ab763b [Joseph K. Bradley] Simplifications to DecisionTree code:
efcc736 [qiping.lqp] fix bug
10b8012 [qiping.lqp] fix style
6728fad [qiping.lqp] minor fix: remove empty lines
bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune
cadd569 [qiping.lqp] add api docs
46b891f [qiping.lqp] fix bug
e72c7e4 [qiping.lqp] add comments
845c6fa [qiping.lqp] fix style
f195e83 [qiping.lqp] fix style
987cbf4 [qiping.lqp] fix bug
ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain
ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree

Author: Reynold Xin <rxin@apache.org>

Closes #2560 from rxin/TaskContext and squashes the following commits:

9eff95a [Reynold Xin] [SPARK-3543] remaining cleanup work.

Moved `#maybeSpill` in ExternalSorter and EAOM into `Spillable`.

Author: Jim Lim <jim@quixey.com>

Closes #2416 from jimjh/SPARK-2761 and squashes the following commits:

cf8be9a [Jim Lim] SPARK-2761 fix documentation, reorder code
f94d522 [Jim Lim] SPARK-2761 refactor Spillable to simplify sig
e75a24e [Jim Lim] SPARK-2761 use protected over protected[this]
7270e0d [Jim Lim] SPARK-2761 refactor #maybeSpill into Spillable

This reverts commit 2d972fd8.

The commit was hanging correlationoptimizer14.

https://issues.apache.org/jira/browse/SPARK-3715

Author: WangTaoTheTonic <barneystinson@aliyun.com>

Closes #2567 from WangTaoTheTonic/minortypo and squashes the following commits:

9cc3f7a [WangTaoTheTonic] minor typo

The sbt tasks sql/console and hive/console will now `stop()`
the `SparkContext` upon exit.  Previously, they left an ugly stack
trace when quitting.

Author: William Benton <willb@redhat.com>

Closes #2547 from willb/consoleCleanup and squashes the following commits:

d5e431f [William Benton] SQL and Hive console tasks now clean up.

from [SPARK-3651]
In CoarseGrainedSchedulerBackend, we have:

    private val executorActor = new HashMap[String, ActorRef]
    private val executorAddress = new HashMap[String, Address]
    private val executorHost = new HashMap[String, String]
    private val freeCores = new HashMap[String, Int]
    private val totalCores = new HashMap[String, Int]

We only ever put / remove stuff from these maps together. It would simplify the code if we consolidate these all into one map as we have done in JobProgressListener in https://issues.apache.org/jira/browse/SPARK-2299.

Author: Dale <tigerquoll@outlook.com>

Closes #2533 from tigerquoll/SPARK-3651 and squashes the following commits:

d1be0a9 [Dale] [SPARK-3651]  implemented suggested changes. Changed a reference from executorInfo to executorData to be consistent with other usages
6890663 [Dale] [SPARK-3651]  implemented suggested changes
7d671cf [Dale] [SPARK-3651]  Grouped variables under a ExecutorDataObject, and reference them via a map entry as they are all retrieved under the same key

https://issues.apache.org/jira/browse/SPARK-3389

Author: Uri Laserson <laserson@cloudera.com>

Closes #2256 from laserson/SPARK-3389 and squashes the following commits:

0ed363e [Uri Laserson] PEP8'd the python file
0b4b380 [Uri Laserson] Moved converter to examples and added python example
eecf4dc [Uri Laserson] [SPARK-3389] Add Converter for ease of Parquet reading in PySpark

This addresses some minor issues in https://github.com/apache/spark/pull/2425

Author: Reynold Xin <rxin@apache.org>

Closes #2557 from rxin/TaskContext and squashes the following commits:

a51e5f6 [Reynold Xin] [SPARK-3543] Clean up Java TaskContext implementation.

Currently, the schema of object in ArrayType or MapType is attached lazily, it will have better performance but introduce issues while serialization or accessing nested objects.

This patch will apply schema to the objects of ArrayType or MapType immediately when accessing them, will be a little bit slower, but much robust.

Author: Davies Liu <davies.liu@gmail.com>

Closes #2526 from davies/nested and squashes the following commits:

2399ae5 [Davies Liu] fix serialization of List and Map in SchemaRDD

Typing of UDFs should be lazy as it is often not valid to call `dataType` on an expression until after all of its children are `resolved`.

Author: Michael Armbrust <michael@databricks.com>

Closes #2525 from marmbrus/concatBug and squashes the following commits:

5b8efe7 [Michael Armbrust] fix bug with eager typing of udfs

This is a bug in JDK6: http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4428022

this is because jdk get different result to operate ```double```,
```System.out.println(1/500d)``` in different jdk get different result
jdk 1.6.0(_31) ---- 0.0020
jdk 1.7.0(_05) ---- 0.002
this leads to HiveQuerySuite failed when generate golden answer in jdk 1.7 and run tests in jdk 1.6, result did not match

Author: w00228970 <wangfei1@huawei.com>

Closes #2517 from scwf/HiveQuerySuite and squashes the following commits:

0cb5e8d [w00228970] delete golden answer of division-0 and timestamp cast #1
1df3964 [w00228970] Jdk version leads to different query output for Double, this make HiveQuerySuite failed

Author: CrazyJvm <crazyjvm@gmail.com>

Closes #2540 from CrazyJvm/standalone-core and squashes the following commits:

66d9fc6 [CrazyJvm] use "--total-executor-cores" rather than "--cores" after spark-shell

Author: Reynold Xin <rxin@apache.org>

Closes #2555 from rxin/cleanup and squashes the following commits:

6add199 [Reynold Xin] Minor cleanup to tighten visibility and remove compilation warning.

...rtByKey() until evaluation.

Author: Erik Erlandson <eerlands@redhat.com>

Closes #1689 from erikerlandson/spark-1021-pr and squashes the following commits:

50b6da6 [Erik Erlandson] use standard getIteratorSize in countAsync
4e334a9 [Erik Erlandson] exception mystery fixed by fixing bug in ComplexFutureAction
b88b5d4 [Erik Erlandson] tweak async actions to use ComplexFutureAction[T] so they handle RangePartitioner sampling job properly
b2b20e8 [Erik Erlandson] Fix bug in exception passing with ComplexFutureAction[T]
ca8913e [Erik Erlandson] RangePartition sampling job -> FutureAction
7143f97 [Erik Erlandson] [SPARK-1021] modify range bounds variable to be thread safe
ac67195 [Erik Erlandson] [SPARK-1021] Defer the data-driven computation of partition bounds in sortByKey() until evaluation.

i.e
./spark-ec2 --region=us-west-1 stop yourclustername

Author: Jeff Steinmetz <jeffrey.steinmetz@gmail.com>

Closes #2473 from jeffsteinmetz/master and squashes the following commits:

7491f2c [Jeff Steinmetz] fix case in EC2 cluster setup documentation
bd3d777 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args
2bf4a57 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args
68d8372 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args
d2ab6e2 [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args
520e6dc [Jeff Steinmetz] standardized ec2 documenation to use <lower-case> sample args
37fc876 [Jeff Steinmetz] stop, start and destroy require the EC2_REGION

Author: Michael Armbrust <michael@databricks.com>

Closes #2515 from marmbrus/jdbcExistingContext and squashes the following commits:

7866fad [Michael Armbrust] Allows starting a JDBC server on an existing context.

Author: Michael Armbrust <michael@databricks.com>

Closes #2527 from marmbrus/patch-1 and squashes the following commits:

a0f9f1c [Michael Armbrust] [SQL][DOCS] Clarify that the server is for JDBC and ODBC

Since 1.1.0 has published, remove spark-staging-1030.

Author: wangfei <wangfei1@huawei.com>

Closes #2532 from scwf/patch-2 and squashes the following commits:

bc9e00b [wangfei] remove spark-staging-1030

Change 0dc868e7 removed the `conf/slaves` file and made it a template like most of the other configuration files. This means you can no longer run `make-distribution.sh` unless you manually create a slaves file to be statically bundled in your distribution, which seems at odds with making it a template file.

Author: Sarah Gerweck <sarah.a180@gmail.com>

Closes #2549 from sarahgerweck/noMoreSlaves and squashes the following commits:

d11d99a [Sarah Gerweck] Slaves file is now a template.

Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Shashank Sharma <shashank21j@gmail.com>

Closes #2425 from ScrapCodes/SPARK-3543/withTaskContext and squashes the following commits:

8ae414c [Shashank Sharma] CR
ee8bd00 [Prashant Sharma] Added internal API in docs comments.
ddb8cbe [Prashant Sharma] Moved setting the thread local to where TaskContext is instantiated.
a7d5e23 [Prashant Sharma] Added doc comments.
edf945e [Prashant Sharma] Code review git add -A
f716fd1 [Prashant Sharma] introduced thread local for getting the task context.
333c7d6 [Prashant Sharma] Translated Task context from scala to java.