[HOT FIX] Yarn stable tests don't compile

This is caused by this commit: acd4ac7c9a503445e27739708cf36e19119b8ddc

Author: andrewor14 <andrew@databricks.com>
Author: Andrew Or <andrew@databricks.com>

Closes #3041 from andrewor14/yarn-hot-fix and squashes the following commits:

e5deba1 [andrewor14] Add new line at the end (minor)
aa998e8 [Andrew Or] Compilation hot fix
SPARK-4175. Exception on stage page

Author: Sandy Ryza <sandy@cloudera.com>

Closes #3043 from sryza/sandy-spark-4175 and squashes the following commits:

e327340 [Sandy Ryza] SPARK-4175. Exception on stage page
[MLLIB] SPARK-2329 Add multi-label evaluation metrics

Implementation of various multi-label classification measures, including: Hamming-loss, strict and default Accuracy, macro-averaged Precision, Recall and F1-measure based on documents and labels, micro-averaged measures: https://issues.apache.org/jira/browse/SPARK-2329

Multi-class measures are currently in the following pull request: https://github.com/apache/spark/pull/1155

Author: Alexander Ulanov <nashb@yandex.ru>
Author: avulanov <nashb@yandex.ru>

Closes #1270 from avulanov/multilabelmetrics and squashes the following commits:

fc8175e [Alexander Ulanov] Merge with previous updates
43a613e [Alexander Ulanov] Addressing reviewers comments: change Set to Array
517a594 [avulanov] Addressing reviewers comments: Scala style
cf4222bc [avulanov] Addressing reviewers comments: renaming. Added label method that returns the list of labels
1843f73 [Alexander Ulanov] Scala style fix
79e8476 [Alexander Ulanov] Replacing fold(_ + _) with sum as suggested by srowen
ca46765 [Alexander Ulanov] Cosmetic changes: Apache header and parameter explanation
40593f5 [Alexander Ulanov] Multi-label metrics: Hamming-loss, strict and normal accuracy, fix to macro measures, bunch of tests
ad62df0 [Alexander Ulanov] Comments and scala style check
154164b [Alexander Ulanov] Multilabel evaluation metics and tests: macro precision and recall averaged by docs, micro and per-class precision and recall averaged by class
[SPARK-3838][examples][mllib][python] Word2Vec example in python

This pull request refers to issue: https://issues.apache.org/jira/browse/SPARK-3838

Python example for word2vec
mengxr

Author: Anant <anant.asty@gmail.com>

Closes #2952 from anantasty/SPARK-3838 and squashes the following commits:

87bd723 [Anant] remove stop line
4bd439e [Anant] Changes as per code review. Fized error in word2vec python example, simplified example in docs.
3d3c9ee [Anant] Added empty line after python imports
0c90c31 [Anant] Fixed erroneous code. I was still treating each line to be a single word instead of 16 words
ee4f5f6 [Anant] Fixes from code review comments
c637bcf [Anant] Added word2vec python example to docs
269f31f [Anant] added example in docs
c015b14 [Anant] Added python example for word2vec
[MLLIB] SPARK-1547: Add Gradient Boosting to MLlib

Given the popular demand for gradient boosting and AdaBoost in MLlib, I am creating a WIP branch for early feedback on gradient boosting with AdaBoost to follow soon after this PR is accepted. This is based on work done along with hirakendu that was pending due to decision tree optimizations and random forests work.

Ideally, boosting algorithms should work with any base learners.  This will soon be possible once the MLlib API is finalized -- we want to ensure we use a consistent interface for the underlying base learners. In the meantime, this PR uses decision trees as base learners for the gradient boosting algorithm. The current PR allows "pluggable" loss functions and provides least squares error and least absolute error by default.

Here is the task list:
- [x] Gradient boosting support
- [x] Pluggable loss functions
- [x] Stochastic gradient boosting support – Re-use the BaggedPoint approach used for RandomForest.
- [x] Binary classification support
- [x] Support configurable checkpointing – This approach will avoid long lineage chains.
- [x] Create classification and regression APIs
- [x] Weighted Ensemble Model -- created a WeightedEnsembleModel class that can be used by ensemble algorithms such as random forests and boosting.
- [x] Unit Tests

Future work:
+ Multi-class classification is currently not supported by this PR since it requires discussion on the best way to support "deviance" as a loss function.
+ BaggedRDD caching -- Avoid repeating feature to bin mapping for each tree estimator after standard API work is completed.

cc: jkbradley hirakendu mengxr etrain atalwalkar chouqin

Author: Manish Amde <manish9ue@gmail.com>
Author: manishamde <manish9ue@gmail.com>

Closes #2607 from manishamde/gbt and squashes the following commits:

991c7b5 [Manish Amde] public api
ff2a796 [Manish Amde] addressing comments
b4c1318 [Manish Amde] removing spaces
8476b6b [Manish Amde] fixing line length
0183cb9 [Manish Amde] fixed naming and formatting issues
1c40c33 [Manish Amde] add newline, removed spaces
e33ab61 [Manish Amde] minor comment
eadbf09 [Manish Amde] parameter renaming
035a2ed [Manish Amde] jkbradley formatting suggestions
9f7359d [Manish Amde] simplified gbt logic and added more tests
49ba107 [Manish Amde] merged from master
eff21fe [Manish Amde] Added gradient boosting tests
3fd0528 [Manish Amde] moved helper methods to new class
a32a5ab [Manish Amde] added test for subsampling without replacement
781542a [Manish Amde] added support for fractional subsampling with replacement
3a18cc1 [Manish Amde] cleaned up api for conversion to bagged point and moved tests to it's own test suite
0e81906 [Manish Amde] improving caching unpersisting logic
d971f73 [Manish Amde] moved RF code to use WeightedEnsembleModel class
fee06d3 [Manish Amde] added weighted ensemble model
1b01943 [Manish Amde] add weights for base learners
9bc6e74 [Manish Amde] adding random seed as parameter
d2c8323 [Manish Amde] Merge branch 'master' into gbt
2ae97b7 [Manish Amde] added documentation for the loss classes
9366b8f [Manish Amde] minor: using numTrees instead of trees.size
3b43896 [Manish Amde] added learning rate for prediction
9b2e35e [Manish Amde] Merge branch 'master' into gbt
6a11c02 [manishamde] fixing formatting
823691b [Manish Amde] fixing RF test
1f47941 [Manish Amde] changing access modifier
5b67102 [Manish Amde] shortened parameter list
5ab3796 [Manish Amde] minor reformatting
9155a9d [Manish Amde] consolidated boosting configuration and added public API
631baea [Manish Amde] Merge branch 'master' into gbt
2cb1258 [Manish Amde] public API support
3b8ffc0 [Manish Amde] added documentation
8e10c63 [Manish Amde] modified unpersist strategy
f62bc48 [Manish Amde] added unpersist
bdca43a [Manish Amde] added timing parameters
2fbc9c7 [Manish Amde] fixing binomial classification prediction
6dd4dd8 [Manish Amde] added support for log loss
9af0231 [Manish Amde] classification attempt
62cc000 [Manish Amde] basic checkpointing
4784091 [Manish Amde] formatting
78ed452 [Manish Amde] added newline and fixed if statement
3973dd1 [Manish Amde] minor indicating subsample is double during comparison
aa8fae7 [Manish Amde] minor refactoring
1a8031c [Manish Amde] sampling with replacement
f1c9ef7 [Manish Amde] Merge branch 'master' into gbt
cdceeef [Manish Amde] added documentation
6251fd5 [Manish Amde] modified method name
5538521 [Manish Amde] disable checkpointing for now
0ae1c0a [Manish Amde] basic gradient boosting code from earlier branches
Streaming KMeans [MLLIB][SPARK-3254]

This adds a Streaming KMeans algorithm to MLlib. It uses an update rule that generalizes the mini-batch KMeans update to incorporate a decay factor, which allows past data to be forgotten. The decay factor can be specified explicitly, or via a more intuitive "fractional decay" setting, in units of either data points or batches.

The PR includes:
- StreamingKMeans algorithm with decay factor settings
- Usage example
- Additions to documentation clustering page
- Unit tests of basic behavior and decay behaviors

tdas mengxr rezazadeh

Author: freeman <the.freeman.lab@gmail.com>
Author: Jeremy Freeman <the.freeman.lab@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes #2942 from freeman-lab/streaming-kmeans and squashes the following commits:

b2e5b4a [freeman] Fixes to docs / examples
078617c [Jeremy Freeman] Merge pull request #1 from mengxr/SPARK-3254
2e682c0 [Xiangrui Meng] take discount on previous weights; use BLAS; detect dying clusters
0411bf5 [freeman] Change decay parameterization
9f7aea9 [freeman] Style fixes
374a706 [freeman] Formatting
ad9bdc2 [freeman] Use labeled points and predictOnValues in examples
77dbd3f [freeman] Make initialization check an assertion
9cfc301 [freeman] Make random seed an argument
44050a9 [freeman] Simpler constructor
c7050d5 [freeman] Fix spacing
2899623 [freeman] Use pattern matching for clarity
a4a316b [freeman] Use collect
1472ec5 [freeman] Doc formatting
ea22ec8 [freeman] Fix imports
2086bdc [freeman] Log cluster center updates
ea9877c [freeman] More documentation
9facbe3 [freeman] Bug fix
5db7074 [freeman] Example usage for StreamingKMeans
f33684b [freeman] Add explanation and example to docs
b5b5f8d [freeman] Add better documentation
a0fd790 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans
9fd9c15 [freeman] Merge remote-tracking branch 'upstream/master' into streaming-kmeans
b93350f [freeman] Streaming KMeans with decay
Upgrading to roaring 0.4.5 (bug fix release)

I recommend upgrading roaring to 0.4.5 as it fixes a rarely occurring bug in iterators (that would otherwise throw an unwarranted exception). The upgrade should have no other consequence.

Author: Daniel Lemire <lemire@gmail.com>

Closes #3044 from lemire/master and squashes the following commits:

54018c5 [Daniel Lemire] Recommended update to roaring 0.4.5 (bug fix release)
048933e [Daniel Lemire] Merge remote-tracking branch 'upstream/master'
431f3a0 [Daniel Lemire] Recommended bug fix release
[SPARK-4142][GraphX] Default numEdgePartitions

Changing the default number of edge partitions to match spark parallelism.

Author: Joseph E. Gonzalez <joseph.e.gonzalez@gmail.com>

Closes #3006 from jegonzal/default_partitions and squashes the following commits:

a9a5c4f [Joseph E. Gonzalez] Changing the default number of edge partitions to match spark parallelism
[SPARK-4115][GraphX] Add overrided count for edge counting of EdgeRDD.

Accumulate sizes of all the EdgePartitions just like the VertexRDD.

Author: luluorta <luluorta@gmail.com>

Closes #2975 from luluorta/graph-edge-count and squashes the following commits:

86ef0e5 [luluorta] Add overrided count for edge counting of EdgeRDD.
[SPARK-2759][CORE] Generic Binary File Support in Spark

The additions add the abstract BinaryFileInputFormat and BinaryRecordReader classes for reading in data as a byte stream and converting it to another format using the ```def parseByteArray(inArray: Array[Byte]): T``` function.
As a trivial example ```ByteInputFormat``` and ```ByteRecordReader``` are included which just return the Array[Byte] from a given file.
Finally a RDD for ```BinaryFileInputFormat``` (to allow for easier partitioning changes as was done for WholeFileInput) was added and the appropriate byteFiles to the ```SparkContext``` so the functions can be easily used by others.
A common use case might be to read in a folder
```
sc.byteFiles("s3://mydrive/tif/*.tif").map(rawData => ReadTiffFromByteArray(rawData))
```

Author: Kevin Mader <kevinmader@gmail.com>
Author: Kevin Mader <kmader@users.noreply.github.com>

Closes #1658 from kmader/master and squashes the following commits:

3c49a30 [Kevin Mader] fixing wholetextfileinput to it has the same setMinPartitions function as in BinaryData files
359a096 [Kevin Mader] making the final corrections suggested by @mateiz and renaming a few functions to make their usage clearer
6379be4 [Kevin Mader] reorganizing code
7b9d181 [Kevin Mader] removing developer API, cleaning up imports
8ac288b [Kevin Mader] fixed a single slightly over 100 character line
92bda0d [Kevin Mader] added new tests, renamed files, fixed several of the javaapi functions, formatted code more nicely
a32fef7 [Kevin Mader] removed unneeded classes added DeveloperApi note to portabledatastreams since the implementation might change
49174d9 [Kevin Mader] removed unneeded classes added DeveloperApi note to portabledatastreams since the implementation might change
c27a8f1 [Kevin Mader] jenkins crashed before running anything last time, so making minor change
b348ce1 [Kevin Mader] fixed order in check (prefix only appears on jenkins not when I run unit tests locally)
0588737 [Kevin Mader] filename check in "binary file input as byte array" test now ignores prefixes and suffixes which might get added by Hadoop
4163e38 [Kevin Mader] fixing line length and output from FSDataInputStream to DataInputStream to minimize sensitivity to Hadoop API changes
19812a8 [Kevin Mader] Fixed the serialization issue with PortableDataStream since neither CombineFileSplit nor TaskAttemptContext implement the Serializable interface, by using ByteArrays for storing both and then recreating the objects from these bytearrays as needed.
238c83c [Kevin Mader] fixed several scala-style issues, changed structure of binaryFiles, removed excessive classes added new tests. The caching tests still have a serialization issue, but that should be easily fixed as well.
932a206 [Kevin Mader] Update RawFileInput.scala
a01c9cf [Kevin Mader] Update RawFileInput.scala
441f79a [Kevin Mader] fixed a few small comments and dependency
12e7be1 [Kevin Mader] removing imglib from maven (definitely not ready yet)
5deb79e [Kevin Mader] added new portabledatastream to code so that it can be serialized correctly
f032bc0 [Kevin Mader] fixed bug in path name, renamed tests
bc5c0b9 [Kevin Mader] made minor stylistic adjustments from mateiz
df8e528 [Kevin Mader] fixed line lengths and changed java test
9a313d5 [Kevin Mader] making classes that needn't be public private, adding automatic file closure, adding new tests
edf5829 [Kevin Mader] fixing line lengths, adding new lines
f4841dc [Kevin Mader] un-optimizing imports, silly intellij
eacfaa6 [Kevin Mader] Added FixedLengthBinaryInputFormat and RecordReader from freeman-lab and added them to both the JavaSparkContext and the SparkContext as fixedLengthBinaryFile
1622935 [Kevin Mader] changing the line lengths to make jenkins happy
1cfa38a [Kevin Mader] added apache headers, added datainputstream directly as an output option for more complicated readers (HDF5 perhaps), and renamed several of the functions and files to be more consistent. Also added parallel functions to the java api
84035f1 [Kevin Mader] adding binary and byte file support spark
81c5f12 [Kevin Mader] Merge pull request #1 from apache/master
[SPARK-4183] Enable NettyBlockTransferService by default

Note that we're turning this on for at least the first part of the QA period as a trial. We want to enable this (and deprecate the NioBlockTransferService) as soon as possible in the hopes that NettyBlockTransferService will be more stable and easier to maintain. We will turn it off if we run into major issues.

Author: Aaron Davidson <aaron@databricks.com>

Closes #3049 from aarondav/enable-netty and squashes the following commits:

bb981cc [Aaron Davidson] [SPARK-4183] Enable NettyBlockTransferService by default
[SPARK-3569][SQL] Add metadata field to StructField

Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON.

Metadata is preserved through simple operations like `SELECT`.

marmbrus liancheng

Author: Xiangrui Meng <meng@databricks.com>
Author: Michael Armbrust <michael@databricks.com>

Closes #2701 from mengxr/structfield-metadata and squashes the following commits:

dedda56 [Xiangrui Meng] merge remote
5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701
886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages.
589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
1e2abcf [Xiangrui Meng] change default value of metadata to None in python
611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr
ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility
3f49aab [Xiangrui Meng] remove StructField.toString
24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
473a7c5 [Xiangrui Meng] merge master
c9d7301 [Xiangrui Meng] organize imports
1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java
60cc131 [Xiangrui Meng] add doc and header
60614c7 [Xiangrui Meng] add metadata
e42c452 [Xiangrui Meng] merge master
93518fb [Xiangrui Meng] support metadata in python
905bb89 [Xiangrui Meng] java conversions
618e349 [Xiangrui Meng] make tests work in scala
61b8e0f [Xiangrui Meng] merge master
7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString
c41a664 [Xiangrui Meng] merge master
d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite
67fdebb [Xiangrui Meng] add test on join
d65072e [Xiangrui Meng] remove Map.empty
367d237 [Xiangrui Meng] add test
c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute
[SPARK-3796] Create external service which can serve shuffle files

This patch introduces the tooling necessary to construct an external shuffle service which is independent of Spark executors, and then use this service inside Spark. An example (just for the sake of this PR) of the service creation can be found in Worker, and the service itself is used by plugging in the StandaloneShuffleClient as Spark's ShuffleClient (setup in BlockManager).

This PR continues the work from #2753, which extracted out the transport layer of Spark's block transfer into an independent package within Spark. A new package was created which contains the Spark business logic necessary to retrieve the actual shuffle data, which is completely independent of the transport layer introduced in the previous patch. Similar to the transport layer, this package must not depend on Spark as we anticipate plugging this service as a lightweight process within, say, the YARN NodeManager, and do not wish to include Spark's dependencies (including Scala itself).

There are several outstanding tasks which must be complete before this PR can be merged:
- [x] Complete unit testing of network/shuffle package.
- [x] Performance and correctness testing on a real cluster.
- [x] Remove example service instantiation from Worker.scala.

There are even more shortcomings of this PR which should be addressed in followup patches:
- Don't use Java serializer for RPC layer! It is not cross-version compatible.
- Handle shuffle file cleanup for dead executors once the application terminates or the ContextCleaner triggers.
- Documentation of the feature in the Spark docs.
- Improve behavior if the shuffle service itself goes down (right now we don't blacklist it, and new executors cannot spawn on that machine).
- SSL and SASL integration
- Nice to have: Handle shuffle file consolidation (this would requires changes to Spark's implementation).

Author: Aaron Davidson <aaron@databricks.com>

Closes #3001 from aarondav/shuffle-service and squashes the following commits:

4d1f8c1 [Aaron Davidson] Remove changes to Worker
705748f [Aaron Davidson] Rename Standalone* to External*
fd3928b [Aaron Davidson] Do not unregister executor outputs unduly
9883918 [Aaron Davidson] Make suggested build changes
3d62679 [Aaron Davidson] Add Spark integration test
7fe51d5 [Aaron Davidson] Fix SBT integration
56caa50 [Aaron Davidson] Address comments
c8d1ac3 [Aaron Davidson] Add unit tests
2f70c0c [Aaron Davidson] Fix unit tests
5483e96 [Aaron Davidson] Fix unit tests
46a70bf [Aaron Davidson] Whoops, bracket
5ea4df6 [Aaron Davidson] [SPARK-3796] Create external service which can serve shuffle files
[SPARK-4037][SQL] Removes the SessionState instance created in HiveThriftServer2

`HiveThriftServer2` creates a global singleton `SessionState` instance and overrides `HiveContext` to inject the `SessionState` object. This messes up `SessionState` initialization and causes problems.

This PR replaces the global `SessionState` with `HiveContext.sessionState` to avoid the initialization conflict. Also `HiveContext` reuses existing started `SessionState` if any (this is required by `SparkSQLCLIDriver`, which uses specialized `CliSessionState`).

Author: Cheng Lian <lian@databricks.com>

Closes #2887 from liancheng/spark-4037 and squashes the following commits:

8446675 [Cheng Lian] Removes redundant Driver initialization
a28fef5 [Cheng Lian] Avoid starting HiveContext.sessionState multiple times
49b1c5b [Cheng Lian] Reuses existing started SessionState if any
3cd6fab [Cheng Lian] Fixes SPARK-4037
Revert "[SPARK-4183] Enable NettyBlockTransferService by default"

This reverts commit 59e626c701227634336110e1bc23afd94c535ede.
[SPARK-4121] Set commons-math3 version based on hadoop profiles, instead of shading

In #2928 , we shade commons-math3 to prevent future conflicts with hadoop. It caused problems with our Jenkins master build with maven. Some tests used local-cluster mode, where the assembly jar contains relocated math3 classes, while mllib test code still compiles with core and the untouched math3 classes.

This PR sets commons-math3 version based on hadoop profiles.

pwendell JoshRosen srowen

Author: Xiangrui Meng <meng@databricks.com>

Closes #3023 from mengxr/SPARK-4121-alt and squashes the following commits:

580f6d9 [Xiangrui Meng] replace tab by spaces
7f71f08 [Xiangrui Meng] revert changes to PoissonSampler to avoid conflicts
d3353d9 [Xiangrui Meng] do not shade commons-math3
b4180dc [Xiangrui Meng] temp work
[SPARK-3161][MLLIB] Adding a node Id caching mechanism for training deci...

...sion trees. jkbradley mengxr chouqin Please review this.

Author: Sung Chung <schung@alpinenow.com>

Closes #2868 from codedeft/SPARK-3161 and squashes the following commits:

5f5a156 [Sung Chung] [SPARK-3161][MLLIB] Adding a node Id caching mechanism for training decision trees.
[SPARK-3930] [SPARK-3933] Support fixed-precision decimal in SQL, and some optimizations

- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf)
- Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs

This is still marked WIP because there are a few TODOs, but I'll remove that tag when done.

Author: Matei Zaharia <matei@databricks.com>

Closes #2983 from mateiz/decimal-1 and squashes the following commits:

35e6b02 [Matei Zaharia] Fix issues after merge
227f24a [Matei Zaharia] Review comments
31f915e [Matei Zaharia] Implement Davies's suggestions in Python
eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet
4dc6bae [Matei Zaharia] Fix decimal support in PySpark
d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase
b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore
2118c0d [Matei Zaharia] Some test and bug fixes
81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions
7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now
ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double
[SPARK-3466] Limit size of results that a driver collects for each action

Right now, operations like collect() and take() can crash the driver with an OOM if they bring back too many data.

This PR will introduce spark.driver.maxResultSize, after setting it, the driver will abort a job if its result is bigger than it.

By default, it's 1g (for backward compatibility for most the cases).

In local mode, the driver and executor share the same JVM, the default setting can not protect JVM from OOM.

cc mateiz

Author: Davies Liu <davies@databricks.com>

Closes #3003 from davies/collect and squashes the following commits:

248ed5e [Davies Liu] fix compile
272522e [Davies Liu] address comments
2c35773 [Davies Liu] add sizes in message of abort()
5d62303 [Davies Liu] address comments
bc3c077 [Davies Liu] Merge branch 'master' of github.com:apache/spark into collect
11f97c5 [Davies Liu] address comments
47b144f [Davies Liu] check the size of result before send and fetch
3d81af2 [Davies Liu] address comments
ca8267d [Davies Liu] limit the size of data by collect
[SPARK-4166][Core][WebUI] Display the executor ID in the Web UI when ExecutorLostFailure happens

Now when ExecutorLostFailure happens, it only displays `ExecutorLostFailure (executor lost)`. Adding the executor id will help locate the faulted executor.

Author: zsxwing <zsxwing@gmail.com>

Closes #3033 from zsxwing/SPARK-4166 and squashes the following commits:

ff4664c [zsxwing] Backward-compatible support
c5c4cf2 [zsxwing] Display the executor ID in the Web UI when ExecutorLostFailure happens