[SPARK-2412] CoalescedRDD throws exception with certain pref locs

If the first pass of CoalescedRDD does not find the target number of locations AND the second pass finds new locations, an exception is thrown, as "groupHash.get(nxt_replica).get" is not valid.

The fix is just to add an ArrayBuffer to groupHash for that replica if it didn't already exist.

Author: Aaron Davidson <aaron@databricks.com>

Closes #1337 from aarondav/2412 and squashes the following commits:

f587b5d [Aaron Davidson] getOrElseUpdate
3ad8a3c [Aaron Davidson] [SPARK-2412] CoalescedRDD throws exception with certain pref locs
SPARK-2526: Simplify options in make-distribution.sh

Right now we have a bunch of parallel logic in make-distribution.sh
that's just extra work to maintain. We should just pass through
Maven profiles in this case and keep the script simple. See
the JIRA for more details.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #1445 from pwendell/make-distribution.sh and squashes the following commits:

f1294ea [Patrick Wendell] Simplify options in make-distribution.sh.
[SPARK-2423] Clean up SparkSubmit for readability

It is currently non-trivial to trace through how different combinations of cluster managers (e.g. yarn) and deploy modes (e.g. cluster) are processed in SparkSubmit. Moving forward, it will be easier to extend SparkSubmit if we first re-organize the code by grouping related logic together.

This is a precursor to fixing standalone-cluster mode, which is currently broken (SPARK-2260).

Author: Andrew Or <andrewor14@gmail.com>

Closes #1349 from andrewor14/submit-cleanup and squashes the following commits:

8f99200 [Andrew Or] script -> program (minor)
30f2e65 [Andrew Or] Merge branch 'master' of github.com:apache/spark into submit-cleanup
fe484a1 [Andrew Or] Move deploy mode checks after yarn code
7167824 [Andrew Or] Re-order config options and update comments
0b01ff8 [Andrew Or] Clean up SparkSubmit for readability
[SPARK-2534] Avoid pulling in the entire RDD in various operators

This should go into both master and branch-1.0.

Author: Reynold Xin <rxin@apache.org>

Closes #1450 from rxin/agg-closure and squashes the following commits:

e40f363 [Reynold Xin] Mima check excludes.
9186364 [Reynold Xin] Define the return type more explicitly.
38e348b [Reynold Xin] Fixed the cases in RDD.scala.
ea6b34d [Reynold Xin] Blah
89b9c43 [Reynold Xin] Fix other instances of accidentally pulling in extra stuff in closures.
73b2783 [Reynold Xin] [SPARK-2534] Avoid pulling in the entire RDD in groupByKey.
SPARK-1478.2 Fix incorrect NioServerSocketChannelFactory constructor call

The line break inadvertently means this was interpreted as a call to the no-arg constructor. This doesn't exist in older Netty even. (Also fixed a val name typo.)

Author: Sean Owen <srowen@gmail.com>

Closes #1466 from srowen/SPARK-1478.2 and squashes the following commits:

59c3501 [Sean Owen] Line break caused Scala to interpret NioServerSocketChannelFactory constructor as the no-arg version, which is not even present in some versions of Netty
SPARK-1215 [MLLIB]: Clustering: Index out of bounds error (2)

Added check to LocalKMeans.scala: kMeansPlusPlus initialization to handle case with fewer distinct data points than clusters k.  Added two related unit tests to KMeansSuite.  (Re-submitting PR after tangling commits in PR 1407 https://github.com/apache/spark/pull/1407 )

Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>

Closes #1468 from jkbradley/kmeans-fix and squashes the following commits:

4e9bd1e [Joseph K. Bradley] Updated PR per comments from mengxr
6c7a2ec [Joseph K. Bradley] Added check to LocalKMeans.scala: kMeansPlusPlus initialization to handle case with fewer distinct data points than clusters k.  Added two related unit tests to KMeansSuite.
[SPARK-2299] Consolidate various stageIdTo* hash maps in JobProgressListener

This should reduce memory usage for the web ui as well as slightly increase its speed in draining the UI event queue.

@andrewor14

Author: Reynold Xin <rxin@apache.org>

Closes #1262 from rxin/ui-consolidate-hashtables and squashes the following commits:

1ac3f97 [Reynold Xin] Oops. Properly handle description.
f5736ad [Reynold Xin] Code review comments.
b8828dc [Reynold Xin] Merge branch 'master' into ui-consolidate-hashtables
7a7b6c4 [Reynold Xin] Revert css change.
f959bb8 [Reynold Xin] [SPARK-2299] Consolidate various stageIdTo* hash maps in JobProgressListener to speed it up.
63256f5 [Reynold Xin] [SPARK-2320] Reduce <pre> block font size.
[SPARK-2411] Add a history-not-found page to standalone Master

**Problem.** Right now, if you click on an application after it has finished, it simply refreshes the page if there are no event logs for the application. This is not super intuitive especially because event logging is not enabled by default. We should direct the user to enable this if they attempt to view a SparkUI after the fact without event logs.

**Fix.** The new page conveys different messages in each of the following scenarios:
(1) Application did not enable event logging,
(2) Event logs are not found in the specified directory, and
(3) Exception is thrown while replaying the logs

Here are screenshots of what the page looks like in each of the above scenarios:

(1)
<img src="https://issues.apache.org/jira/secure/attachment/12656204/Event%20logging%20not%20enabled.png" width="75%">

(2)
<img src="https://issues.apache.org/jira/secure/attachment/12656203/Application%20history%20not%20found.png">

(3)
<img src="https://issues.apache.org/jira/secure/attachment/12656202/Application%20history%20load%20error.png" width="95%">

Author: Andrew Or <andrewor14@gmail.com>

Closes #1336 from andrewor14/master-link and squashes the following commits:

2f06206 [Andrew Or] Merge branch 'master' of github.com:apache/spark into master-link
97cddc0 [Andrew Or] Add different severity levels
832b687 [Andrew Or] Mention spark.eventLog.dir in error message
51980c3 [Andrew Or] Merge branch 'master' of github.com:apache/spark into master-link
ded208c [Andrew Or] Merge branch 'master' of github.com:apache/spark into master-link
89d6405 [Andrew Or] Reword message
e7df7ed [Andrew Or] Add a history not found page to standalone Master
[SPARK-2570] [SQL] Fix the bug of ClassCastException

Exception thrown when running the example of HiveFromSpark.
Exception in thread "main" java.lang.ClassCastException: java.lang.Long cannot be cast to java.lang.Integer
	at scala.runtime.BoxesRunTime.unboxToInt(BoxesRunTime.java:106)
	at org.apache.spark.sql.catalyst.expressions.GenericRow.getInt(Row.scala:145)
	at org.apache.spark.examples.sql.hive.HiveFromSpark$.main(HiveFromSpark.scala:45)
	at org.apache.spark.examples.sql.hive.HiveFromSpark.main(HiveFromSpark.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:606)
	at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:303)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:55)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

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

Closes #1475 from chenghao-intel/hive_from_spark and squashes the following commits:

d4c0500 [Cheng Hao] Fix the bug of ClassCastException
SPARK-2553. CoGroupedRDD unnecessarily allocates a Tuple2 per dependency...

... per key

My humble opinion is that avoiding allocations in this performance-critical section is worth the extra code.

Author: Sandy Ryza <sandy@cloudera.com>

Closes #1461 from sryza/sandy-spark-2553 and squashes the following commits:

7eaf7f2 [Sandy Ryza] SPARK-2553. CoGroupedRDD unnecessarily allocates a Tuple2 per dependency per key
SPARK-2553. Fix compile error

Author: Sandy Ryza <sandy@cloudera.com>

Closes #1479 from sryza/sandy-spark-2553 and squashes the following commits:

2cb5ed8 [Sandy Ryza] SPARK-2553. Fix compile error
Added t2 instance types

New t2 instance types require HVM amis, bailout assumption of pvm
causes failures when using t2 instance types.

Author: Basit Mustafa <basitmustafa@computes-things-for-basit.local>

Closes #1446 from 24601/master and squashes the following commits:

01fe128 [Basit Mustafa] Makin' it pretty
392a95e [Basit Mustafa] Added t2 instance types
Reservoir sampling implementation.

This is going to be used in https://issues.apache.org/jira/browse/SPARK-2568

Author: Reynold Xin <rxin@apache.org>

Closes #1478 from rxin/reservoirSample and squashes the following commits:

17bcbf3 [Reynold Xin] Added seed.
badf20d [Reynold Xin] Renamed the method.
6940010 [Reynold Xin] Reservoir sampling implementation.
[MLlib] SPARK-1536: multiclass classification support for decision tree

The ability to perform multiclass classification is a big advantage for using decision trees and was a highly requested feature for mllib. This pull request adds multiclass classification support to the MLlib decision tree. It also adds sample weights support using WeightedLabeledPoint class for handling unbalanced datasets during classification. It will also support algorithms such as AdaBoost which requires instances to be weighted.

It handles the special case where the categorical variables cannot be ordered for multiclass classification and thus the optimizations used for speeding up binary classification cannot be directly used for multiclass classification with categorical variables. More specifically, for m categories in a categorical feature, it analyses all the ```2^(m-1) - 1``` categorical splits provided that #splits are less than the maxBins provided in the input. This condition will not be met for features with large number of categories -- using decision trees is not recommended for such datasets in general since the categorical features are favored over continuous features. Moreover, the user can use a combination of tricks (increasing bin size of the tree algorithms, use binary encoding for categorical features or use one-vs-all classification strategy) to avoid these constraints.

The new code is accompanied by unit tests and has also been tested on the iris and covtype datasets.

cc: mengxr, etrain, hirakendu, atalwalkar, srowen

Author: Manish Amde <manish9ue@gmail.com>
Author: manishamde <manish9ue@gmail.com>
Author: Evan Sparks <sparks@cs.berkeley.edu>

Closes #886 from manishamde/multiclass and squashes the following commits:

26f8acc [Manish Amde] another attempt at fixing mima
c5b2d04 [Manish Amde] more MIMA fixes
1ce7212 [Manish Amde] change problem filter for mima
10fdd82 [Manish Amde] fixing MIMA excludes
e1c970d [Manish Amde] merged master
abf2901 [Manish Amde] adding classes to MimaExcludes.scala
45e767a [Manish Amde] adding developer api annotation for overriden methods
c8428c4 [Manish Amde] fixing weird multiline bug
afced16 [Manish Amde] removed label weights support
2d85a48 [Manish Amde] minor: fixed scalastyle issues reprise
4e85f2c [Manish Amde] minor: fixed scalastyle issues
b2ae41f [Manish Amde] minor: scalastyle
e4c1321 [Manish Amde] using while loop for regression histograms
d75ac32 [Manish Amde] removed WeightedLabeledPoint from this PR
0fecd38 [Manish Amde] minor: add newline to EOF
2061cf5 [Manish Amde] merged from master
06b1690 [Manish Amde] fixed off-by-one error in bin to split conversion
9cc3e31 [Manish Amde] added implicit conversion import
5c1b2ca [Manish Amde] doc for PointConverter class
485eaae [Manish Amde] implicit conversion from LabeledPoint to WeightedLabeledPoint
3d7f911 [Manish Amde] updated doc
8e44ab8 [Manish Amde] updated doc
adc7315 [Manish Amde] support ordered categorical splits for multiclass classification
e3e8843 [Manish Amde] minor code formatting
23d4268 [Manish Amde] minor: another minor code style
34ee7b9 [Manish Amde] minor: code style
237762d [Manish Amde] renaming functions
12e6d0a [Manish Amde] minor: removing line in doc
9a90c93 [Manish Amde] Merge branch 'master' into multiclass
1892a2c [Manish Amde] tests and use multiclass binaggregate length when atleast one categorical feature is present
f5f6b83 [Manish Amde] multiclass for continous variables
8cfd3b6 [Manish Amde] working for categorical multiclass classification
828ff16 [Manish Amde] added categorical variable test
bce835f [Manish Amde] code cleanup
7e5f08c [Manish Amde] minor doc
1dd2735 [Manish Amde] bin search logic for multiclass
f16a9bb [Manish Amde] fixing while loop
d811425 [Manish Amde] multiclass bin aggregate logic
ab5cb21 [Manish Amde] multiclass logic
d8e4a11 [Manish Amde] sample weights
ed5a2df [Manish Amde] fixed classification requirements
d012be7 [Manish Amde] fixed while loop
18d2835 [Manish Amde] changing default values for num classes
6b912dc [Manish Amde] added numclasses to tree runner, predict logic for multiclass, add multiclass option to train
75f2bfc [Manish Amde] minor code style fix
e547151 [Manish Amde] minor modifications
34549d0 [Manish Amde] fixing error during merge
098e8c5 [Manish Amde] merged master
e006f9d [Manish Amde] changing variable names
5c78e1a [Manish Amde] added multiclass support
6c7af22 [Manish Amde] prepared for multiclass without breaking binary classification
46e06ee [Manish Amde] minor mods
3f85a17 [Manish Amde] tests for multiclass classification
4d5f70c [Manish Amde] added multiclass support for find splits bins
46f909c [Manish Amde] todo for multiclass support
455bea9 [Manish Amde] fixed tests
14aea48 [Manish Amde] changing instance format to weighted labeled point
a1a6e09 [Manish Amde] added weighted point class
968ca9d [Manish Amde] merged master
7fc9545 [Manish Amde] added docs
ce004a1 [Manish Amde] minor formatting
b27ad2c [Manish Amde] formatting
426bb28 [Manish Amde] programming guide blurb
8053fed [Manish Amde] more formatting
5eca9e4 [Manish Amde] grammar
4731cda [Manish Amde] formatting
5e82202 [Manish Amde] added documentation, fixed off by 1 error in max level calculation
cbd9f14 [Manish Amde] modified scala.math to math
dad9652 [Manish Amde] removed unused imports
e0426ee [Manish Amde] renamed parameter
718506b [Manish Amde] added unit test
1517155 [Manish Amde] updated documentation
9dbdabe [Manish Amde] merge from master
719d009 [Manish Amde] updating user documentation
fecf89a [manishamde] Merge pull request #6 from etrain/deep_tree
0287772 [Evan Sparks] Fixing scalastyle issue.
2f1e093 [Manish Amde] minor: added doc for maxMemory parameter
2f6072c [manishamde] Merge pull request #5 from etrain/deep_tree
abc5a23 [Evan Sparks] Parameterizing max memory.
50b143a [Manish Amde] adding support for very deep trees
[SPARK-2535][SQL] Add StringComparison case to NullPropagation.

`StringComparison` expressions including `null` literal cases could be added to `NullPropagation`.

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

Closes #1451 from ueshin/issues/SPARK-2535 and squashes the following commits:

e99c237 [Takuya UESHIN] Add some tests.
8f9b984 [Takuya UESHIN] Add StringComparison case to NullPropagation.
[SPARK-2540] [SQL] Add HiveDecimal & HiveVarchar support in unwrapping data

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

Closes #1436 from chenghao-intel/unwrapdata and squashes the following commits:

34cc21a [Cheng Hao] update the table scan accodringly since the unwrapData function changed
afc39da [Cheng Hao] Polish the code
39d6475 [Cheng Hao] Add HiveDecimal & HiveVarchar support in unwrap data
[SPARK-2571] Correctly report shuffle read metrics.

Currently, shuffle read metrics are incorrectly reported when stages have multiple shuffle dependencies (they are set to be the metrics from just one of the shuffle dependencies, rather than the accumulated metrics from all of the shuffle dependencies).  This fixes that problem, and should probably be back-ported to the 0.9 branch.

Thanks ryanra for discovering this problem!

cc rxin andrewor14

Author: Kay Ousterhout <kayousterhout@gmail.com>

Closes #1476 from kayousterhout/join_bug and squashes the following commits:

0203a16 [Kay Ousterhout] Fix broken unit tests.
f463c2e [Kay Ousterhout] [SPARK-2571] Correctly report shuffle read metrics.
[SPARK-2359][MLlib] Correlations

Implementation for Pearson and Spearman's correlation.

Author: Doris Xin <doris.s.xin@gmail.com>

Closes #1367 from dorx/correlation and squashes the following commits:

c0dd7dc [Doris Xin] here we go
32d83a3 [Doris Xin] Reviewer comments
4db0da1 [Doris Xin] added private[stat] to Spearman
b716f70 [Doris Xin] minor fixes
6e1b42a [Doris Xin] More comments addressed. Still some open questions
8104f44 [Doris Xin] addressed comments. some open questions still
39387c2 [Doris Xin] added missing header
bd3cf19 [Doris Xin] Merge branch 'master' into correlation
6341884 [Doris Xin] race condition bug squished
bd2bacf [Doris Xin] Race condition bug
b775ff9 [Doris Xin] old wrong impl
534ebf2 [Doris Xin] Merge branch 'master' into correlation
818fa31 [Doris Xin] wip units
9d808ee [Doris Xin] wip units
b843a13 [Doris Xin] revert change in stat counter
28561b6 [Doris Xin] wip
bb2e977 [Doris Xin] minor fix
8e02c63 [Doris Xin] Merge branch 'master' into correlation
2a40aa1 [Doris Xin] initial, untested implementation of Pearson
dfc4854 [Doris Xin] WIP
[SPARK-2521] Broadcast RDD object (instead of sending it along with every task).

Currently (as of Spark 1.0.1), Spark sends RDD object (which contains closures) using Akka along with the task itself to the executors. This is inefficient because all tasks in the same stage use the same RDD object, but we have to send RDD object multiple times to the executors. This is especially bad when a closure references some variable that is very large. The current design led to users having to explicitly broadcast large variables.

The patch uses broadcast to send RDD objects and the closures to executors, and use Akka to only send a reference to the broadcast RDD/closure along with the partition specific information for the task. For those of you who know more about the internals, Spark already relies on broadcast to send the Hadoop JobConf every time it uses the Hadoop input, because the JobConf is large.

The user-facing impact of the change include:

1. Users won't need to decide what to broadcast anymore, unless they would want to use a large object multiple times in different operations
2. Task size will get smaller, resulting in faster scheduling and higher task dispatch throughput.

In addition, the change will simplify some internals of Spark, eliminating the need to maintain task caches and the complex logic to broadcast JobConf (which also led to a deadlock recently).

A simple way to test this:
```scala
val a = new Array[Byte](1000*1000); scala.util.Random.nextBytes(a);
sc.parallelize(1 to 1000, 1000).map { x => a; x }.groupBy { x => a; x }.count
```

Numbers on 3 r3.8xlarge instances on EC2
```
master branch: 5.648436068 s, 4.715361895 s, 5.360161877 s
with this change: 3.416348793 s, 1.477846558 s, 1.553432156 s
```

Author: Reynold Xin <rxin@apache.org>

Closes #1452 from rxin/broadcast-task and squashes the following commits:

762e0be [Reynold Xin] Warn large broadcasts.
ade6eac [Reynold Xin] Log broadcast size.
c3b6f11 [Reynold Xin] Added a unit test for clean up.
754085f [Reynold Xin] Explain why broadcasting serialized copy of the task.
04b17f0 [Reynold Xin] [SPARK-2521] Broadcast RDD object once per TaskSet (instead of sending it for every task).
put 'curRequestSize = 0' after 'logDebug' it

This is a minor change. We should first logDebug($curRequestSize) and then set it to 0.

Author: Lijie Xu <csxulijie@gmail.com>

Closes #1477 from JerryLead/patch-1 and squashes the following commits:

aed722d [Lijie Xu] put 'curRequestSize = 0' after 'logDebug' it