## What changes were proposed in this pull request?

Add lost `<tr>` tag for `configuration.md`.

## How was this patch tested?
N/A

Author: Yuming Wang <wgyumg@gmail.com>

Closes #18372 from wangyum/docs-missing-tr.

## What changes were proposed in this pull request?

Currently the shuffle service registration timeout and retry has been hardcoded. This works well for small workloads but under heavy workload when the shuffle service is busy transferring large amount of data we see significant delay in responding to the registration request, as a result we often see the executors fail to register with the shuffle service, eventually failing the job. We need to make these two parameters configurable.

## How was this patch tested?

* Updated `BlockManagerSuite` to test registration timeout and max attempts configuration actually works.

cc sitalkedia

Author: Li Yichao <lyc@zhihu.com>

Closes #18092 from liyichao/SPARK-20640.

## What changes were proposed in this pull request?

The description for several options of File Source for structured streaming appeared in the File Sink description instead.

This pull request has two commits: The first includes changes to the version as it appeared in spark 2.1 and the second handled an additional option added for spark 2.2

## How was this patch tested?

Built the documentation by SKIP_API=1 jekyll build and visually inspected the structured streaming programming guide.

The original documentation was written by tdas and lw-lin

Author: assafmendelson <assaf.mendelson@gmail.com>

Closes #18342 from assafmendelson/spark-21123.

[SPARK-21126] The configuration which named "spark.core.connection.auth.wait.timeout" hasn't been used in spark

[https://issues.apache.org/jira/browse/SPARK-21126](https://issues.apache.org/jira/browse/SPARK-21126)
The configuration which named "spark.core.connection.auth.wait.timeout" hasn't been used in spark,so I think it should be removed from configuration.md.

Author: liuzhaokun <liu.zhaokun@zte.com.cn>

Closes #18333 from liu-zhaokun/new3.

## What changes were proposed in this pull request?

Update Running R Tests dependence packages to:
```bash
R -e "install.packages(c('knitr', 'rmarkdown', 'testthat', 'e1071', 'survival'), repos='http://cran.us.r-project.org')"
```

## How was this patch tested?
manual tests

Author: Yuming Wang <wgyumg@gmail.com>

Closes #18271 from wangyum/building-spark.

## What changes were proposed in this pull request?

Move Hadoop delegation token code from `spark-yarn` to `spark-core`, so that other schedulers (such as Mesos), may use it.  In order to avoid exposing Hadoop interfaces in spark-core, the new Hadoop delegation token classes are kept private.  In order to provider backward compatiblity, and to allow YARN users to continue to load their own delegation token providers via Java service loading, the old YARN interfaces, as well as the client code that uses them, have been retained.

Summary:
- Move registered `yarn.security.ServiceCredentialProvider` classes from `spark-yarn` to `spark-core`.  Moved them into a new, private hierarchy under `HadoopDelegationTokenProvider`.  Client code in `HadoopDelegationTokenManager` now loads credentials from a whitelist of three providers (`HadoopFSDelegationTokenProvider`, `HiveDelegationTokenProvider`, `HBaseDelegationTokenProvider`), instead of service loading, which means that users are not able to implement their own delegation token providers, as they are in the `spark-yarn` module.

- The `yarn.security.ServiceCredentialProvider` interface has been kept for backwards compatibility, and to continue to allow YARN users to implement their own delegation token provider implementations.  Client code in YARN now fetches tokens via the new `YARNHadoopDelegationTokenManager` class, which fetches tokens from the core providers through `HadoopDelegationTokenManager`, as well as service loads them from `yarn.security.ServiceCredentialProvider`.

Old Hierarchy:

```
yarn.security.ServiceCredentialProvider (service loaded)
  HadoopFSCredentialProvider
  HiveCredentialProvider
  HBaseCredentialProvider
yarn.security.ConfigurableCredentialManager
```

New Hierarchy:

```
HadoopDelegationTokenManager
HadoopDelegationTokenProvider (not service loaded)
  HadoopFSDelegationTokenProvider
  HiveDelegationTokenProvider
  HBaseDelegationTokenProvider

yarn.security.ServiceCredentialProvider (service loaded)
yarn.security.YARNHadoopDelegationTokenManager
```
## How was this patch tested?

unit tests

Author: Michael Gummelt <mgummelt@mesosphere.io>
Author: Dr. Stefan Schimanski <sttts@mesosphere.io>

Closes #17723 from mgummelt/SPARK-20434-refactor-kerberos.

## What changes were proposed in this pull request?

doc only change

## How was this patch tested?

manually

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #18312 from felixcheung/sqljsonwholefiledoc.

## What changes were proposed in this pull request?

`df.groupBy.count()` should be `df.groupBy().count()` , otherwise there is an error :

ambiguous reference to overloaded definition, both method groupBy in class Dataset of type (col1: String, cols: String*) and method groupBy in class Dataset of type (cols: org.apache.spark.sql.Column*)

## How was this patch tested?

```scala
val df = spark.readStream.schema(...).json(...)
val dfCounts = df.groupBy().count()
```

Author: Ziyue Huang <zyhuang94@gmail.com>

Closes #18272 from ZiyueHuang/master.

## What changes were proposed in this pull request?

Add Mesos labels support to the Spark Dispatcher

## How was this patch tested?

unit tests

Author: Michael Gummelt <mgummelt@mesosphere.io>

Closes #18220 from mgummelt/SPARK-21000-dispatcher-labels.

## What changes were proposed in this pull request?

I fixed some incorrect formatting on a link in the docs

## How was this patch tested?

I looked at the markdown preview before and after, and the link was fixed

Before:
<img width="593" alt="screen shot 2017-06-08 at 6 37 32 pm" src="https://user-images.githubusercontent.com/17733030/26956272-a62cd558-4c79-11e7-862f-9d0e0184b18a.png">
After:
<img width="587" alt="screen shot 2017-06-08 at 6 37 44 pm" src="https://user-images.githubusercontent.com/17733030/26956276-b1135ef6-4c79-11e7-8028-84d19c392fda.png">

Author: Corey Woodfield <coreywoodfield@gmail.com>

Closes #18246 from coreywoodfield/master.

## What changes were proposed in this pull request?

Add a new property `spark.streaming.kafka.consumer.cache.enabled` that allows users to enable or disable the cache for Kafka consumers. This property can be especially handy in cases where issues like SPARK-19185 get hit, for which there isn't a solution committed yet. By default, the cache is still on, so this change doesn't change any out-of-box behavior.

## How was this patch tested?
Running unit tests

Author: Mark Grover <mark@apache.org>
Author: Mark Grover <grover.markgrover@gmail.com>

Closes #18234 from markgrover/spark-19185.

## What changes were proposed in this pull request?

We had better update the deprecation notes about Python 2.6, Hadoop (before 2.6.5) and Scala 2.10 in [2.2.0-RC4](http://people.apache.org/~pwendell/spark-releases/spark-2.2.0-rc4-docs/) documentation. Since this is a doc only update, I think we can update the doc during publishing.

**BEFORE (2.2.0-RC4)**
    ![before](https://cloud.githubusercontent.com/assets/9700541/26799758/aea0dc06-49eb-11e7-8ca3-ed8ce1cc6147.png)

**AFTER**
    ![after](https://cloud.githubusercontent.com/assets/9700541/26799761/b3fef818-49eb-11e7-83c5-334f0e4768ed.png)

## How was this patch tested?

Manual.
```
SKIP_API=1 jekyll build
```

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #18207 from dongjoon-hyun/minor_doc_deprecation.

[SPARK-20981][SPARKSUBMIT] Add new configuration spark.jars.repositories as equivalence of --repositories

## What changes were proposed in this pull request?

In our use case of launching Spark applications via REST APIs (Livy), there's no way for user to specify command line arguments, all Spark configurations are set through configurations map. For "--repositories" because there's no equivalent Spark configuration, so we cannot specify the custom repository through configuration.

So here propose to add "--repositories" equivalent configuration in Spark.

## How was this patch tested?

New UT added.

Author: jerryshao <sshao@hortonworks.com>

Closes #18201 from jerryshao/SPARK-20981.

## What changes were proposed in this pull request?

- Add Scala, Python and Java examples for `partitionBy`, `sortBy` and `bucketBy`.
- Add _Bucketing, Sorting and Partitioning_ section to SQL Programming Guide
- Remove bucketing from Unsupported Hive Functionalities.

## How was this patch tested?

Manual tests, docs build.

Author: zero323 <zero323@users.noreply.github.com>

Closes #17938 from zero323/DOCS-BUCKETING-AND-PARTITIONING.

Now that Structured Streaming has been out for several Spark release and has large production use cases, the `Experimental` label is no longer appropriate.  I've left `InterfaceStability.Evolving` however, as I think we may make a few changes to the pluggable Source & Sink API in Spark 2.3.

Author: Michael Armbrust <michael@databricks.com>

Closes #18065 from marmbrus/streamingGA.

## What changes were proposed in this pull request?
1, add an example for sparkr `decisionTree`
2, document it in user guide

## How was this patch tested?
local submit

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #18067 from zhengruifeng/dt_example.

[SPARK-20888][SQL][DOCS] Document change of default setting of spark.sql.hive.caseSensitiveInferenceMode

(Link to Jira: https://issues.apache.org/jira/browse/SPARK-20888)

## What changes were proposed in this pull request?

Document change of default setting of spark.sql.hive.caseSensitiveInferenceMode configuration key from NEVER_INFO to INFER_AND_SAVE in the Spark SQL 2.1 to 2.2 migration notes.

Author: Michael Allman <michael@videoamp.com>

Closes #18112 from mallman/spark-20888-document_infer_and_save.

## What changes were proposed in this pull request?

Currently the whole block is fetched into memory(off heap by default) when shuffle-read. A block is defined by (shuffleId, mapId, reduceId). Thus it can be large when skew situations. If OOM happens during shuffle read, job will be killed and users will be notified to "Consider boosting spark.yarn.executor.memoryOverhead". Adjusting parameter and allocating more memory can resolve the OOM. However the approach is not perfectly suitable for production environment, especially for data warehouse.
Using Spark SQL as data engine in warehouse, users hope to have a unified parameter(e.g. memory) but less resource wasted(resource is allocated but not used). The hope is strong especially when migrating data engine to Spark from another one(e.g. Hive). Tuning the parameter for thousands of SQLs one by one is very time consuming.
It's not always easy to predict skew situations, when happen, it make sense to fetch remote blocks to disk for shuffle-read, rather than kill the job because of OOM.

In this pr, I propose to fetch big blocks to disk(which is also mentioned in SPARK-3019):

1. Track average size and also the outliers(which are larger than 2*avgSize) in MapStatus;
2. Request memory from `MemoryManager` before fetch blocks and release the memory to `MemoryManager` when `ManagedBuffer` is released.
3. Fetch remote blocks to disk when failing acquiring memory from `MemoryManager`, otherwise fetch to memory.

This is an improvement for memory control when shuffle blocks and help to avoid OOM in scenarios like below:
1. Single huge block;
2. Sizes of many blocks are underestimated in `MapStatus` and the actual footprint of blocks is much larger than the estimated.

## How was this patch tested?
Added unit test in `MapStatusSuite` and `ShuffleBlockFetcherIteratorSuite`.

Author: jinxing <jinxing6042@126.com>

Closes #16989 from jinxing64/SPARK-19659.

## What changes were proposed in this pull request?

Currently, when number of reduces is above 2000, HighlyCompressedMapStatus is used to store size of blocks. in HighlyCompressedMapStatus, only average size is stored for non empty blocks. Which is not good for memory control when we shuffle blocks. It makes sense to store the accurate size of block when it's above threshold.

## How was this patch tested?

Added test in MapStatusSuite.

Author: jinxing <jinxing6042@126.com>

Closes #18031 from jinxing64/SPARK-20801.

Quick follow up to #17996 - forgot to add the HTML links to the relevant sections of the guide in the highlights list.

## How was this patch tested?

Built docs locally and tested links.

Author: Nick Pentreath <nickp@za.ibm.com>

Closes #18043 from MLnick/SPARK-20506-2.2-migration-guide-2.

Update ML guide for migration `2.1` -> `2.2` and the previous version migration guide section.

## How was this patch tested?

Build doc locally.

Author: Nick Pentreath <nickp@za.ibm.com>

Closes #17996 from MLnick/SPARK-20506-2.2-migration-guide.

[https://issues.apache.org/jira/browse/SPARK-20759](https://issues.apache.org/jira/browse/SPARK-20759)
SCALA_VERSION in _config.yml is 2.11.7, but 2.11.8 in pom.xml. So I think SCALA_VERSION in _config.yml should be consistent with pom.xml.

Author: liuzhaokun <liu.zhaokun@zte.com.cn>

Closes #17992 from liu-zhaokun/new.

## What changes were proposed in this pull request?

The changes were merged as part of - https://github.com/apache/spark/pull/17467.
The documentation was missed somewhere in the review iterations. Adding the documentation where it belongs.

## How was this patch tested?
Docs. Not tested.

cc budde , brkyvz

Author: Yash Sharma <ysharma@atlassian.com>

Closes #18028 from yssharma/ysharma/kinesis_retry_docs.

[https://issues.apache.org/jira/browse/SPARK-20796](https://issues.apache.org/jira/browse/SPARK-20796)
the location of start-master.sh in spark-standalone.md should be "sbin/start-master.sh" rather than "bin/start-master.sh".

Author: liuzhaokun <liu.zhaokun@zte.com.cn>

Closes #18027 from liu-zhaokun/sbin.

## What changes were proposed in this pull request?
Add docs and examples for ```ml.stat.Correlation``` and ```ml.stat.ChiSquareTest```.

## How was this patch tested?
Generate docs and run examples manually, successfully.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #17994 from yanboliang/spark-20505.

## What changes were proposed in this pull request?

SPARK-13973 incorrectly removed the required PYSPARK_DRIVER_PYTHON_OPTS=notebook from documentation to use pyspark with Jupyter notebook. This patch corrects the documentation error.

## How was this patch tested?

Tested invocation locally with
```bash
PYSPARK_DRIVER_PYTHON=jupyter PYSPARK_DRIVER_PYTHON_OPTS=notebook ./bin/pyspark
```

Author: Andrew Ray <ray.andrew@gmail.com>

Closes #18001 from aray/patch-1.

## What changes were proposed in this pull request?

Any Dataset/DataFrame batch query with the operation `withWatermark` does not execute because the batch planner does not have any rule to explicitly handle the EventTimeWatermark logical plan.
The right solution is to simply remove the plan node, as the watermark should not affect any batch query in any way.

Changes:
- In this PR, we add a new rule `EliminateEventTimeWatermark` to check if we need to ignore the event time watermark. We will ignore watermark in any batch query.

Depends upon:
- [SPARK-20672](https://issues.apache.org/jira/browse/SPARK-20672). We can not add this rule into analyzer directly, because streaming query will be copied to `triggerLogicalPlan ` in every trigger, and the rule will be applied to `triggerLogicalPlan` mistakenly.

Others:
- A typo fix in example.

## How was this patch tested?

add new unit test.

Author: uncleGen <hustyugm@gmail.com>

Closes #17896 from uncleGen/SPARK-20373.

## What changes were proposed in this pull request?

After SPARK-10997, client mode Netty RpcEnv doesn't require to start server, so port configurations are not used any more, here propose to remove these two configurations: "spark.executor.port" and "spark.am.port".

## How was this patch tested?

Existing UTs.

Author: jerryshao <sshao@hortonworks.com>

Closes #17866 from jerryshao/SPARK-20605.

## What changes were proposed in this pull request?

Add a new `spark-hadoop-cloud` module and maven profile to pull in object store support from `hadoop-openstack`, `hadoop-aws` and `hadoop-azure` (Hadoop 2.7+) JARs, along with their dependencies, fixing up the dependencies so that everything works, in particular Jackson.

It restores `s3n://` access to S3, adds its `s3a://` replacement, OpenStack `swift://` and azure `wasb://`.

There's a documentation page, `cloud_integration.md`, which covers the basic details of using Spark with object stores, referring the reader to the supplier's own documentation, with specific warnings on security and the possible mismatch between a store's behavior and that of a filesystem. In particular, users are advised be very cautious when trying to use an object store as the destination of data, and to consult the documentation of the storage supplier and the connector.

(this is the successor to #12004; I can't re-open it)

## How was this patch tested?

Downstream tests exist in [https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples](https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples)

Those verify that the dependencies are sufficient to allow downstream applications to work with s3a, azure wasb and swift storage connectors, and perform basic IO & dataframe operations thereon. All seems well.

Manually clean build & verify that assembly contains the relevant aws-* hadoop-* artifacts on Hadoop 2.6; azure on a hadoop-2.7 profile.

SBT build: `build/sbt -Phadoop-cloud -Phadoop-2.7 package`
maven build `mvn install -Phadoop-cloud -Phadoop-2.7`

This PR *does not* update `dev/deps/spark-deps-hadoop-2.7` or `dev/deps/spark-deps-hadoop-2.6`, because unless the hadoop-cloud profile is enabled, no extra JARs show up in the dependency list. The dependency check in Jenkins isn't setting the property, so the new JARs aren't visible.

Author: Steve Loughran <stevel@apache.org>
Author: Steve Loughran <stevel@hortonworks.com>

Closes #17834 from steveloughran/cloud/SPARK-7481-current.

[SPARK-20015][SPARKR][SS][DOC][EXAMPLE] Document R Structured Streaming (experimental) in R vignettes and R & SS programming guide, R example

## What changes were proposed in this pull request?

Add
- R vignettes
- R programming guide
- SS programming guide
- R example

Also disable spark.als in vignettes for now since it's failing (SPARK-20402)

## How was this patch tested?

manually

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #17814 from felixcheung/rdocss.

Add PCA and SVD to PySpark's wrappers for `RowMatrix` and `IndexedRowMatrix` (SVD only).

Based on #7963, updated.

## How was this patch tested?

New doc tests and unit tests. Ran all examples locally.

Author: MechCoder <manojkumarsivaraj334@gmail.com>
Author: Nick Pentreath <nickp@za.ibm.com>

Closes #17621 from MLnick/SPARK-6227-pyspark-svd-pca.

## What changes were proposed in this pull request?

Updating R Programming Guide

## How was this patch tested?

manually

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #17816 from felixcheung/r22relnote.

[SPARK-20521][DOC][CORE] The default of 'spark.worker.cleanup.appDataTtl' should be 604800 in spark-standalone.md

## What changes were proposed in this pull request?

Currently, our project needs to be set to clean up the worker directory cleanup cycle is three days.
When I follow http://spark.apache.org/docs/latest/spark-standalone.html, configure the 'spark.worker.cleanup.appDataTtl' parameter, I configured to 3 * 24 * 3600.
When I start the spark service, the startup fails, and the worker log displays the error log as follows:

2017-04-28 15:02:03,306 INFO Utils: Successfully started service 'sparkWorker' on port 48728.
Exception in thread "main" java.lang.NumberFormatException: For input string: "3 * 24 * 3600"
	at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
	at java.lang.Long.parseLong(Long.java:430)
	at java.lang.Long.parseLong(Long.java:483)
	at scala.collection.immutable.StringLike$class.toLong(StringLike.scala:276)
	at scala.collection.immutable.StringOps.toLong(StringOps.scala:29)
	at org.apache.spark.SparkConf$$anonfun$getLong$2.apply(SparkConf.scala:380)
	at org.apache.spark.SparkConf$$anonfun$getLong$2.apply(SparkConf.scala:380)
	at scala.Option.map(Option.scala:146)
	at org.apache.spark.SparkConf.getLong(SparkConf.scala:380)
	at org.apache.spark.deploy.worker.Worker.<init>(Worker.scala:100)
	at org.apache.spark.deploy.worker.Worker$.startRpcEnvAndEndpoint(Worker.scala:730)
	at org.apache.spark.deploy.worker.Worker$.main(Worker.scala:709)
	at org.apache.spark.deploy.worker.Worker.main(Worker.scala)

**Because we put 7 * 24 * 3600 as a string, forced to convert to the dragon type,  will lead to problems in the program.**

**So I think the default value of the current configuration should be a specific long value, rather than 7 * 24 * 3600,should be 604800. Because it would mislead users for similar configurations, resulting in spark start failure.**

## How was this patch tested?
manual tests

Please review http://spark.apache.org/contributing.html before opening a pull request.

Author: 郭小龙 10207633 <guo.xiaolong1@zte.com.cn>
Author: guoxiaolong <guo.xiaolong1@zte.com.cn>
Author: guoxiaolongzte <guo.xiaolong1@zte.com.cn>

Closes #17798 from guoxiaolongzte/SPARK-20521.

## What changes were proposed in this pull request?

Add a new section for fpm
Add Example for FPGrowth in scala and Java

updated: Rewrite transform to be more compact.

## How was this patch tested?

local doc generation.

Author: Yuhao Yang <yuhao.yang@intel.com>

Closes #17130 from hhbyyh/fpmdoc.

## What changes were proposed in this pull request?

Add hyper link in the SparkR programming guide.

## How was this patch tested?

Build doc and manually check the doc link.

Author: wangmiao1981 <wm624@hotmail.com>

Closes #17805 from wangmiao1981/doc.

## What changes were proposed in this pull request?

add link to svmLinear in the SparkR programming document.

## How was this patch tested?

Build doc manually and click the link to the document. It looks good.

Author: wangmiao1981 <wm624@hotmail.com>

Closes #17797 from wangmiao1981/doc.

## What changes were proposed in this pull request?

Add `spark.fpGrowth` to SparkR programming guide.

## How was this patch tested?

Manual tests.

Author: zero323 <zero323@users.noreply.github.com>

Closes #17775 from zero323/SPARK-20208-FOLLOW-UP.

This change does a more thorough redaction of sensitive information from logs and UI
Add unit tests that ensure that no regressions happen that leak sensitive information to the logs.

The motivation for this change was appearance of password like so in `SparkListenerEnvironmentUpdate` in event logs under some JVM configurations:
`"sun.java.command":"org.apache.spark.deploy.SparkSubmit ... --conf spark.executorEnv.HADOOP_CREDSTORE_PASSWORD=secret_password ..."
`
Previously redaction logic was only checking if the key matched the secret regex pattern, it'd redact it's value. That worked for most cases. However, in the above case, the key (sun.java.command) doesn't tell much, so the value needs to be searched. This PR expands the check to check for values as well.

## How was this patch tested?

New unit tests added that ensure that no sensitive information is present in the event logs or the yarn logs. Old unit test in UtilsSuite was modified because the test was asserting that a non-sensitive property's value won't be redacted. However, the non-sensitive value had the literal "secret" in it which was causing it to redact. Simply updating the non-sensitive property's value to another arbitrary value (that didn't have "secret" in it) fixed it.

Author: Mark Grover <mark@apache.org>

Closes #17725 from markgrover/spark-20435.

## What changes were proposed in this pull request?

Simple documentation change to remove explicit vendor references.

## How was this patch tested?

NA

Please review http://spark.apache.org/contributing.html before opening a pull request.

Author: anabranch <bill@databricks.com>

Closes #17695 from anabranch/remove-vendor.

## What changes were proposed in this pull request?

- Add `rollup` and `cube` methods and corresponding generics.
- Add short description to the vignette.

## How was this patch tested?

- Existing unit tests.
- Additional unit tests covering new features.
- `check-cran.sh`.

Author: zero323 <zero323@users.noreply.github.com>

Closes #17728 from zero323/SPARK-20437.