## What changes were proposed in this pull request?

Just added the Maven `test`goal.

## How was this patch tested?

No test needed, just a trivial documentation fix.

Author: Armin Braun <me@obrown.io>

Closes #17756 from original-brownbear/SPARK-20455.

## What changes were proposed in this pull request?

In `randomSplit`, It is possible that the underlying dataset doesn't guarantee the ordering of rows in its constituent partitions each time a split is materialized which could result in overlapping
splits.

To prevent this, as part of SPARK-12662, we explicitly sort each input partition to make the ordering deterministic. Given that `MapTypes` cannot be sorted this patch explicitly prunes them out from the sort order. Additionally, if the resulting sort order is empty, this patch then materializes the dataset to guarantee determinism.

## How was this patch tested?

Extended `randomSplit on reordered partitions` in `DataFrameStatSuite` to also test for dataframes with mapTypes nested mapTypes.

Author: Sameer Agarwal <sameerag@cs.berkeley.edu>

Closes #17751 from sameeragarwal/randomsplit2.

This patch bumps the master branch version to `2.3.0-SNAPSHOT`.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #17753 from JoshRosen/SPARK-20453.

## What changes were proposed in this pull request?

Current SHS (Spark History Server) two different ACLs:

* ACL of base URL, it is controlled by "spark.acls.enabled" or "spark.ui.acls.enabled", and with this enabled, only user configured with "spark.admin.acls" (or group) or "spark.ui.view.acls" (or group), or the user who started SHS could list all the applications, otherwise none of them can be listed. This will also affect REST APIs which listing the summary of all apps and one app.
* Per application ACL. This is controlled by "spark.history.ui.acls.enabled". With this enabled only history admin user and user/group who ran this app can access the details of this app.

With this two ACLs, we may encounter several unexpected behaviors:

1. if base URL's ACL (`spark.acls.enable`) is enabled but user A has no view permission. User "A" cannot see the app list but could still access details of it's own app.
2. if ACLs of base URL (`spark.acls.enable`) is disabled, then user "A" could download any application's event log, even it is not run by user "A".
3. The changes of Live UI's ACL will affect History UI's ACL which share the same conf file.

The unexpected behaviors is mainly because we have two different ACLs, ideally we should have only one to manage all.

So to improve SHS's ACL mechanism, here in this PR proposed to:

1. Disable "spark.acls.enable" and only use "spark.history.ui.acls.enable" for history server.
2. Check permission for event-log download REST API.

With this PR:

1. Admin user could see/download the list of all applications, as well as application details.
2. Normal user could see the list of all applications, but can only download and check the details of applications accessible to him.

## How was this patch tested?

New UTs are added, also verified in real cluster.

CC tgravescs vanzin please help to review, this PR changes the semantics you did previously. Thanks a lot.

Author: jerryshao <sshao@hortonworks.com>

Closes #17582 from jerryshao/SPARK-20239.

## What changes were proposed in this pull request?

Add wrappers for `o.a.s.sql.functions`:

- `split` as `split_string`
- `repeat` as `repeat_string`

## How was this patch tested?

Existing tests, additional unit tests, `check-cran.sh`

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

Closes #17729 from zero323/SPARK-20438.

## What changes were proposed in this pull request?

In MultivariateOnlineSummarizer,

`add` and `merge` have check for weights and feature sizes. The checks in LR are redundant, which are removed from this PR.

## How was this patch tested?

Existing tests.

Author: wm624@hotmail.com <wm624@hotmail.com>

Closes #17478 from wangmiao1981/logit.

### What changes were proposed in this pull request?

`spark.catalog.listTables` and `spark.catalog.getTable` does not work if we are unable to retrieve table metadata due to any reason (e.g., table serde class is not accessible or the table type is not accepted by Spark SQL). After this PR, the APIs still return the corresponding Table without the description and tableType)

### How was this patch tested?
Added a test case

Author: Xiao Li <gatorsmile@gmail.com>

Closes #17730 from gatorsmile/listTables.

## What changes were proposed in this pull request?
This pr proposed to close stale PRs. Currently, we have 400+ open PRs and there are some stale PRs whose JIRA tickets have been already closed and whose JIRA tickets does not exist (also, they seem not to be minor issues).

// Open PRs whose JIRA tickets have been already closed
Closes #11785
Closes #13027
Closes #13614
Closes #13761
Closes #15197
Closes #14006
Closes #12576
Closes #15447
Closes #13259
Closes #15616
Closes #14473
Closes #16638
Closes #16146
Closes #17269
Closes #17313
Closes #17418
Closes #17485
Closes #17551
Closes #17463
Closes #17625

// Open PRs whose JIRA tickets does not exist and they are not minor issues
Closes #10739
Closes #15193
Closes #15344
Closes #14804
Closes #16993
Closes #17040
Closes #15180
Closes #17238

## How was this patch tested?
N/A

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #17734 from maropu/resolved_pr.

[SPARK-20385][WEB-UI] Submitted Time' field, the date format needs to be formatted, in running Drivers table or Completed Drivers table in master web ui.

## What changes were proposed in this pull request?
Submitted Time' field, the date format **needs to be formatted**, in running Drivers table or Completed Drivers table in master web ui.
Before fix this problem  e.g.

Completed Drivers
Submission ID	             **Submitted Time**  	             Worker	                            State	   Cores	   Memory	       Main Class
driver-20170419145755-0005	 **Wed Apr 19 14:57:55 CST 2017**	 worker-20170419145250-zdh120-40412	FAILED	   1	       1024.0 MB	   cn.zte.HdfsTest

please see the  attachment:https://issues.apache.org/jira/secure/attachment/12863977/before_fix.png

After fix this problem e.g.

Completed Drivers
Submission ID	             **Submitted Time**  	             Worker	                            State	   Cores	   Memory	       Main Class
driver-20170419145755-0006	 **2017/04/19 16:01:25**	 worker-20170419145250-zdh120-40412	         FAILED	   1	       1024.0 MB	   cn.zte.HdfsTest

please see the  attachment:https://issues.apache.org/jira/secure/attachment/12863976/after_fix.png

'Submitted Time' field, the date format **has been formatted**, in running Applications table or Completed Applicationstable in master web ui, **it is correct.**
e.g.
Running Applications
Application ID	                Name	                Cores	Memory per Executor	   **Submitted Time**	      User	   State	        Duration
app-20170419160910-0000 (kill)	SparkSQL::10.43.183.120	1	    5.0 GB	               **2017/04/19 16:09:10**	  root	   RUNNING	    53 s

**Format after the time easier to observe, and consistent with the applications table,so I think it's worth fixing.**

## How was this patch tested?

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)

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 #17682 from guoxiaolongzte/SPARK-20385.

## What changes were proposed in this pull request?
Add docstrings to column.py for the Column functions `rlike`, `like`, `startswith`, and `endswith`. Pass these docstrings through `_bin_op`

There may be a better place to put the docstrings. I put them immediately above the Column class.

## How was this patch tested?

I ran `make html` on my local computer to remake the documentation, and verified that the html pages were displaying the docstrings correctly. I tried running `dev-tests`, and the formatting tests passed. However, my mvn build didn't work I think due to issues on my computer.

These docstrings are my original work and free license.

davies has done the most recent work reorganizing `_bin_op`

Author: Michael Patterson <map222@gmail.com>

Closes #17469 from map222/patterson-documentation.

## What changes were proposed in this pull request?
This pr initialised `RangeExec` parameters in a driver side.
In the current master, a query below throws `NullPointerException`;
```
sql("SET spark.sql.codegen.wholeStage=false")
sql("SELECT * FROM range(1)").show

17/04/20 17:11:05 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.NullPointerException
        at org.apache.spark.sql.execution.SparkPlan.sparkContext(SparkPlan.scala:54)
        at org.apache.spark.sql.execution.RangeExec.numSlices(basicPhysicalOperators.scala:343)
        at org.apache.spark.sql.execution.RangeExec$$anonfun$20.apply(basicPhysicalOperators.scala:506)
        at org.apache.spark.sql.execution.RangeExec$$anonfun$20.apply(basicPhysicalOperators.scala:505)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$26.apply(RDD.scala:844)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$26.apply(RDD.scala:844)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:108)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:320)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
```

## How was this patch tested?
Added a test in `DataFrameRangeSuite`.

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #17717 from maropu/SPARK-20430.

## What changes were proposed in this pull request?
Modify the added memory size to memSize-originalMemSize if the  block exists on the slave already
since if the  block exists, the added memory size should be memSize-originalMemSize; if originalMemSize is bigger than memSize ,then the log info should be Removed memory, removed size should be originalMemSize-memSize

## How was this patch tested?
Multiple runs on existing unit tests

(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)

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

Author: eatoncys <chen.yanshan@zte.com.cn>

Closes #17683 from eatoncys/SPARK-20386.

[SPARK-20401][DOC] In the spark official configuration document, the 'spark.driver.supervise' configuration parameter specification and default values are necessary.

## What changes were proposed in this pull request?
Use the REST interface submits the spark job.
e.g.
curl -X  POST http://10.43.183.120:6066/v1/submissions/create --header "Content-Type:application/json;charset=UTF-8" --data'{
    "action": "CreateSubmissionRequest",
    "appArgs": [
        "myAppArgument"
    ],
    "appResource": "/home/mr/gxl/test.jar",
    "clientSparkVersion": "2.2.0",
    "environmentVariables": {
        "SPARK_ENV_LOADED": "1"
    },
    "mainClass": "cn.zte.HdfsTest",
    "sparkProperties": {
        "spark.jars": "/home/mr/gxl/test.jar",
        **"spark.driver.supervise": "true",**
        "spark.app.name": "HdfsTest",
        "spark.eventLog.enabled": "false",
        "spark.submit.deployMode": "cluster",
        "spark.master": "spark://10.43.183.120:6066"
    }
}'

**I hope that make sure that the driver is automatically restarted if it fails with non-zero exit code.
But I can not find the 'spark.driver.supervise' configuration parameter specification and default values from the spark official document.**
## 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 #17696 from guoxiaolongzte/SPARK-20401.

## What changes were proposed in this pull request?

Adds wrappers for `collect_list` and `collect_set`.

## How was this patch tested?

Unit tests, `check-cran.sh`

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

Closes #17672 from zero323/SPARK-20371.

## What changes were proposed in this pull request?

When reg == 0, MLOR has multiple solutions and we need to centralize the coeffs to get identical result.
BUT current implementation centralize the `coefficientMatrix` by the global coeffs means.

In fact the `coefficientMatrix` should be centralized on each feature index itself.
Because, according to the MLOR probability distribution function, it can be proven easily that:
suppose `{ w0, w1, .. w(K-1) }` make up the `coefficientMatrix`,
then `{ w0 + c, w1 + c, ... w(K - 1) + c}` will also be the equivalent solution.
`c` is an arbitrary vector of `numFeatures` dimension.
reference
https://core.ac.uk/download/pdf/6287975.pdf

So that we need to centralize the `coefficientMatrix` on each feature dimension separately.

**We can also confirm this through R library `glmnet`, that MLOR in `glmnet` always generate coefficients result that the sum of each dimension is all `zero`, when reg == 0.**

## How was this patch tested?

Tests added.

Author: WeichenXu <WeichenXu123@outlook.com>

Closes #17706 from WeichenXu123/mlor_center.

## What changes were proposed in this pull request?

This PR avoids an exception in the case where `scala.math.BigInt` has a value that does not fit into long value range (e.g. `Long.MAX_VALUE+1`). When we run the following code by using the current Spark, the following exception is thrown.

This PR keeps the value using `BigDecimal` if we detect such an overflow case by catching `ArithmeticException`.

Sample program:
```
case class BigIntWrapper(value:scala.math.BigInt)```
spark.createDataset(BigIntWrapper(scala.math.BigInt("10000000000000000002"))::Nil).show
```
Exception:
```
Error while encoding: java.lang.ArithmeticException: BigInteger out of long range
staticinvoke(class org.apache.spark.sql.types.Decimal$, DecimalType(38,0), apply, assertnotnull(assertnotnull(input[0, org.apache.spark.sql.BigIntWrapper, true])).value, true) AS value#0
java.lang.RuntimeException: Error while encoding: java.lang.ArithmeticException: BigInteger out of long range
staticinvoke(class org.apache.spark.sql.types.Decimal$, DecimalType(38,0), apply, assertnotnull(assertnotnull(input[0, org.apache.spark.sql.BigIntWrapper, true])).value, true) AS value#0
	at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:290)
	at org.apache.spark.sql.SparkSession$$anonfun$2.apply(SparkSession.scala:454)
	at org.apache.spark.sql.SparkSession$$anonfun$2.apply(SparkSession.scala:454)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.immutable.List.foreach(List.scala:381)
	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
	at scala.collection.immutable.List.map(List.scala:285)
	at org.apache.spark.sql.SparkSession.createDataset(SparkSession.scala:454)
	at org.apache.spark.sql.Agg$$anonfun$18.apply$mcV$sp(MySuite.scala:192)
	at org.apache.spark.sql.Agg$$anonfun$18.apply(MySuite.scala:192)
	at org.apache.spark.sql.Agg$$anonfun$18.apply(MySuite.scala:192)
	at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
	at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
	at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
	at org.scalatest.Transformer.apply(Transformer.scala:22)
	at org.scalatest.Transformer.apply(Transformer.scala:20)
	at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
	at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:68)
	at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
	at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
	at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
	at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
	at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175)
...
Caused by: java.lang.ArithmeticException: BigInteger out of long range
	at java.math.BigInteger.longValueExact(BigInteger.java:4531)
	at org.apache.spark.sql.types.Decimal.set(Decimal.scala:140)
	at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:434)
	at org.apache.spark.sql.types.Decimal.apply(Decimal.scala)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
	at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:287)
	... 59 more
```

## How was this patch tested?

Add new test suite into `DecimalSuite`

Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>

Closes #17684 from kiszk/SPARK-20341.

[SPARK-20412] Throw ParseException from visitNonOptionalPartitionSpec instead of returning null values.

## What changes were proposed in this pull request?

If a partitionSpec is supposed to not contain optional values, a ParseException should be thrown, and not nulls returned.
The nulls can later cause NullPointerExceptions in places not expecting them.

## How was this patch tested?

A query like "SHOW PARTITIONS tbl PARTITION(col1='val1', col2)" used to throw a NullPointerException.
Now it throws a ParseException.

Author: Juliusz Sompolski <julek@databricks.com>

Closes #17707 from juliuszsompolski/SPARK-20412.

Hello
PR #10991 removed the built-in history view from Spark Standalone, so the history server is no longer useful to Yarn or Mesos only.

Author: Hervé <dud225@users.noreply.github.com>

Closes #17709 from dud225/patch-1.

## What changes were proposed in this pull request?
It is often useful to be able to track changes to the `ExternalCatalog`. This PR makes the `ExternalCatalog` emit events when a catalog object is changed. Events are fired before and after the change.

The following events are fired per object:

- Database
  - CreateDatabasePreEvent: event fired before the database is created.
  - CreateDatabaseEvent: event fired after the database has been created.
  - DropDatabasePreEvent: event fired before the database is dropped.
  - DropDatabaseEvent: event fired after the database has been dropped.
- Table
  - CreateTablePreEvent: event fired before the table is created.
  - CreateTableEvent: event fired after the table has been created.
  - RenameTablePreEvent: event fired before the table is renamed.
  - RenameTableEvent: event fired after the table has been renamed.
  - DropTablePreEvent: event fired before the table is dropped.
  - DropTableEvent: event fired after the table has been dropped.
- Function
  - CreateFunctionPreEvent: event fired before the function is created.
  - CreateFunctionEvent: event fired after the function has been created.
  - RenameFunctionPreEvent: event fired before the function is renamed.
  - RenameFunctionEvent: event fired after the function has been renamed.
  - DropFunctionPreEvent: event fired before the function is dropped.
  - DropFunctionPreEvent: event fired after the function has been dropped.

The current events currently only contain the names of the object modified. We add more events, and more details at a later point.

A user can monitor changes to the external catalog by adding a listener to the Spark listener bus checking for `ExternalCatalogEvent`s using the `SparkListener.onOtherEvent` hook. A more direct approach is add listener directly to the `ExternalCatalog`.

## How was this patch tested?
Added the `ExternalCatalogEventSuite`.

Author: Herman van Hovell <hvanhovell@databricks.com>

Closes #17710 from hvanhovell/SPARK-20420.

## What changes were proposed in this pull request?
This pr modified code to print the identical `Range` parameters of SparkContext APIs and SQL in `explain` output. In the current master, they internally use `defaultParallelism` for `splits` by default though, they print different strings in explain output;

```
scala> spark.range(4).explain
== Physical Plan ==
*Range (0, 4, step=1, splits=Some(8))

scala> sql("select * from range(4)").explain
== Physical Plan ==
*Range (0, 4, step=1, splits=None)
```

## How was this patch tested?
Added tests in `SQLQuerySuite` and modified some results in the existing tests.

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #17670 from maropu/SPARK-20281.

## What changes were proposed in this pull request?
A cast expression with a resolved time zone is not equal to a cast expression without a resolved time zone. The `ResolveAggregateFunction` assumed that these expression were the same, and would fail to resolve `HAVING` clauses which contain a `Cast` expression.

This is in essence caused by the fact that a `TimeZoneAwareExpression` can be resolved without a set time zone. This PR fixes this, and makes a `TimeZoneAwareExpression` unresolved as long as it has no TimeZone set.

## How was this patch tested?
Added a regression test to the `SQLQueryTestSuite.having` file.

Author: Herman van Hovell <hvanhovell@databricks.com>

Closes #17641 from hvanhovell/SPARK-20329.

## What changes were proposed in this pull request?

When infering partitioning schema from paths, the column in parsePartitionColumn should be unescaped with unescapePathName, just like it is being done in e.g. parsePathFragmentAsSeq.

## How was this patch tested?

Added a test to FileIndexSuite.

Author: Juliusz Sompolski <julek@databricks.com>

Closes #17703 from juliuszsompolski/SPARK-20367.

## What changes were proposed in this pull request?

In the current Spark's HistoryServer we expected to get `AccessControlException` during listing all the files, but unfortunately it was not worked because we actually doesn't check the access permission and no other calls will throw such exception. What was worse is that this check will be deferred until reading files, which is not necessary and quite verbose, since it will be printed out the exception in every 10 seconds when checking the files.

So here with this fix, we actually check the read permission during listing the files, which could avoid unnecessary file read later on and suppress the verbose log.

## How was this patch tested?

Add unit test to verify.

Author: jerryshao <sshao@hortonworks.com>

Closes #17495 from jerryshao/SPARK-20172.

## What changes were proposed in this pull request?
It is kind of annoying that `SharedSQLContext.sparkConf` is a val when overriding test cases, because you cannot call `super` on it. This PR makes it a function.

## How was this patch tested?
Existing tests.

Author: Herman van Hovell <hvanhovell@databricks.com>

Closes #17705 from hvanhovell/SPARK-20410.

[SPARK-20334][SQL] Return a better error message when correlated predicates contain aggregate expression that has mixture of outer and local references.

## What changes were proposed in this pull request?
Address a follow up in [comment](https://github.com/apache/spark/pull/16954#discussion_r105718880)
Currently subqueries with correlated predicates containing aggregate expression having mixture of outer references and local references generate a codegen error like following :

```SQL
SELECT t1a
FROM   t1
GROUP  BY 1
HAVING EXISTS (SELECT 1
               FROM  t2
               WHERE t2a < min(t1a + t2a));
```
Exception snippet.
```
Cannot evaluate expression: min((input[0, int, false] + input[4, int, false]))
	at org.apache.spark.sql.catalyst.expressions.Unevaluable$class.doGenCode(Expression.scala:226)
	at org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression.doGenCode(interfaces.scala:87)
	at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:106)
	at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:103)
	at scala.Option.getOrElse(Option.scala:121)
	at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:103)

```
After this PR, a better error message is issued.
```
org.apache.spark.sql.AnalysisException
Error in query: Found an aggregate expression in a correlated
predicate that has both outer and local references, which is not supported yet.
Aggregate expression: min((t1.`t1a` + t2.`t2a`)),
Outer references: t1.`t1a`,
Local references: t2.`t2a`.;
```
## How was this patch tested?
Added tests in SQLQueryTestSuite.

Author: Dilip Biswal <dbiswal@us.ibm.com>

Closes #17636 from dilipbiswal/subquery_followup1.

## What changes were proposed in this pull request?

This was a regression introduced by my earlier PR here: https://github.com/apache/spark/pull/17531

It turns out NonFatal() does not in fact catch InterruptedException.

## How was this patch tested?

Extended cancellation unit test coverage. The first test fails before this patch.

cc JoshRosen mridulm

Author: Eric Liang <ekl@databricks.com>

Closes #17659 from ericl/spark-20358.

## What changes were proposed in this pull request?

SharedSQLContext.afterEach now calls DebugFilesystem.assertNoOpenStreams inside eventually.
SQLTestUtils withTempDir calls waitForTasksToFinish before deleting the directory.

## How was this patch tested?
Added new test in ParquetQuerySuite based on the flaky test

Author: Bogdan Raducanu <bogdan@databricks.com>

Closes #17701 from bogdanrdc/SPARK-20407.

## What changes were proposed in this pull request?

It's illegal to have aggregate function in GROUP BY, and we should fail at analysis phase, if this happens.

## How was this patch tested?

new regression test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #17704 from cloud-fan/minor.

## What changes were proposed in this pull request?
Dataset.withNewExecutionId is only used in Dataset itself and should be private.

## How was this patch tested?
N/A - this is a simple visibility change.

Author: Reynold Xin <rxin@databricks.com>

Closes #17699 from rxin/SPARK-20405.

[SPARK-20156][SQL][FOLLOW-UP] Java String toLowerCase "Turkish locale bug" in Database and Table DDLs

### What changes were proposed in this pull request?
Database and Table names conform the Hive standard ("[a-zA-z_0-9]+"), i.e. if this name only contains characters, numbers, and _.

When calling `toLowerCase` on the names, we should add `Locale.ROOT` to the `toLowerCase`for avoiding inadvertent locale-sensitive variation in behavior (aka the "Turkish locale problem").

### How was this patch tested?
Added a test case

Author: Xiao Li <gatorsmile@gmail.com>

Closes #17655 from gatorsmile/locale.

## What changes were proposed in this pull request?

Adds wrappers for `o.a.s.sql.functions.array` and `o.a.s.sql.functions.map`

## How was this patch tested?

Unit tests, `check-cran.sh`

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

Closes #17674 from zero323/SPARK-20375.

## What changes were proposed in this pull request?

Typos at a couple of place in the docs.

## How was this patch tested?

build including docs

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

Author: ymahajan <ymahajan@snappydata.io>

Closes #17690 from ymahajan/master.

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-19820 adds a reason field for why tasks were killed. However, for backwards compatibility it left the old TaskKilledException constructor which defaults to "unknown reason".
The range() operator should use the constructor that fills in the reason rather than dropping it on task kill.

## How was this patch tested?

Existing tests, and I tested this manually.

Author: Eric Liang <ekl@databricks.com>

Closes #17692 from ericl/fix-kill-reason-in-range.

## What changes were proposed in this pull request?

Also went through the same file to ensure other string concatenation are correct.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #17691 from zsxwing/fix-error-message.

## What changes were proposed in this pull request?

Apply Complementation Laws during boolean expression simplification.

## How was this patch tested?

Tested using unit tests, integration tests, and manual tests.

Author: ptkool <michael.styles@shopify.com>
Author: Michael Styles <michael.styles@shopify.com>

Closes #17650 from ptkool/apply_complementation_laws.

## What changes were proposed in this pull request?

Checking a source parameter is asynchronous. When the query is created, it's not guaranteed that source has been created. This PR just increases the timeout of awaitTermination to ensure the parsing error is thrown.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #17687 from zsxwing/SPARK-20397.

## What changes were proposed in this pull request?

Note that you shouldn't manually add dependencies on org.apache.kafka artifacts

## How was this patch tested?

Doc only change, did jekyll build and looked at the page.

Author: cody koeninger <cody@koeninger.org>

Closes #17675 from koeninger/SPARK-20036.

## What changes were proposed in this pull request?

This PR proposes two things as below:

- Avoid Unidoc build only if Hadoop 2.6 is explicitly set in SBT build

  Due to a different dependency resolution in SBT & Unidoc by an unknown reason, the documentation build fails on a specific machine & environment in Jenkins but it was unable to reproduce.

  So, this PR just checks an environment variable `AMPLAB_JENKINS_BUILD_PROFILE` that is set in Hadoop 2.6 SBT build against branches on Jenkins, and then disables Unidoc build. **Note that PR builder will still build it with Hadoop 2.6 & SBT.**

  ```
  ========================================================================
  Building Unidoc API Documentation
  ========================================================================
  [info] Building Spark unidoc (w/Hive 1.2.1) using SBT with these arguments:  -Phadoop-2.6 -Pmesos -Pkinesis-asl -Pyarn -Phive-thriftserver -Phive unidoc
  Using /usr/java/jdk1.8.0_60 as default JAVA_HOME.
  ...
  ```

  I checked the environment variables from the logs (first bit) as below:

  - **spark-master-test-sbt-hadoop-2.6** (this one is being failed) - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-sbt-hadoop-2.6/lastBuild/consoleFull

  ```
  JAVA_HOME=/usr/java/jdk1.8.0_60
  JAVA_7_HOME=/usr/java/jdk1.7.0_79
  SPARK_BRANCH=master
  AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.6   <- I use this variable
  AMPLAB_JENKINS="true"
  ```
  - spark-master-test-sbt-hadoop-2.7 - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-sbt-hadoop-2.7/lastBuild/consoleFull

  ```
  JAVA_HOME=/usr/java/jdk1.8.0_60
  JAVA_7_HOME=/usr/java/jdk1.7.0_79
  SPARK_BRANCH=master
  AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.7
  AMPLAB_JENKINS="true"
  ```

  - spark-master-test-maven-hadoop-2.6 - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-2.6/lastBuild/consoleFull

  ```
  JAVA_HOME=/usr/java/jdk1.8.0_60
  JAVA_7_HOME=/usr/java/jdk1.7.0_79
  HADOOP_PROFILE=hadoop-2.6
  HADOOP_VERSION=
  SPARK_BRANCH=master
  AMPLAB_JENKINS="true"
  ```

  - spark-master-test-maven-hadoop-2.7 - https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-master-test-maven-hadoop-2.7/lastBuild/consoleFull

  ```
  JAVA_HOME=/usr/java/jdk1.8.0_60
  JAVA_7_HOME=/usr/java/jdk1.7.0_79
  HADOOP_PROFILE=hadoop-2.7
  HADOOP_VERSION=
  SPARK_BRANCH=master
  AMPLAB_JENKINS="true"
  ```

  - PR builder - https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/75843/consoleFull

  ```
  JENKINS_MASTER_HOSTNAME=amp-jenkins-master
  JAVA_HOME=/usr/java/jdk1.8.0_60
  JAVA_7_HOME=/usr/java/jdk1.7.0_79
  ```

  Assuming from other logs in branch-2.1

    - SBT & Hadoop 2.6 against branch-2.1 https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-branch-2.1-test-sbt-hadoop-2.6/lastBuild/consoleFull

      ```
      JAVA_HOME=/usr/java/jdk1.8.0_60
      JAVA_7_HOME=/usr/java/jdk1.7.0_79
      SPARK_BRANCH=branch-2.1
      AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.6
      AMPLAB_JENKINS="true"
      ```

    - Maven & Hadoop 2.6 against branch-2.1 https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test%20(Dashboard)/job/spark-branch-2.1-test-maven-hadoop-2.6/lastBuild/consoleFull

      ```
      JAVA_HOME=/usr/java/jdk1.8.0_60
      JAVA_7_HOME=/usr/java/jdk1.7.0_79
      HADOOP_PROFILE=hadoop-2.6
      HADOOP_VERSION=
      SPARK_BRANCH=branch-2.1
      AMPLAB_JENKINS="true"
      ```

  We have been using the same convention for those variables. These are actually being used in `run-tests.py` script - here https://github.com/apache/spark/blob/master/dev/run-tests.py#L519-L520

- Revert the previous try

  After https://github.com/apache/spark/pull/17651, it seems the build still fails on SBT Hadoop 2.6 master.

  I am unable to reproduce this - https://github.com/apache/spark/pull/17477#issuecomment-294094092 and the reviewer was too. So, this got merged as it looks the only way to verify this is to merge it currently (as no one seems able to reproduce this).

## How was this patch tested?

I only checked `is_hadoop_version_2_6 = os.environ.get("AMPLAB_JENKINS_BUILD_PROFILE") == "hadoop2.6"` is working fine as expected as below:

```python
>>> import collections
>>> os = collections.namedtuple('os', 'environ')(environ={"AMPLAB_JENKINS_BUILD_PROFILE": "hadoop2.6"})
>>> print(not os.environ.get("AMPLAB_JENKINS_BUILD_PROFILE") == "hadoop2.6")
False
>>> os = collections.namedtuple('os', 'environ')(environ={"AMPLAB_JENKINS_BUILD_PROFILE": "hadoop2.7"})
>>> print(not os.environ.get("AMPLAB_JENKINS_BUILD_PROFILE") == "hadoop2.6")
True
>>> os = collections.namedtuple('os', 'environ')(environ={})
>>> print(not os.environ.get("AMPLAB_JENKINS_BUILD_PROFILE") == "hadoop2.6")
True
```

I tried many ways but I was unable to reproduce this in my local. Sean also tried the way I did but he was also unable to reproduce this.

Please refer the comments in https://github.com/apache/spark/pull/17477#issuecomment-294094092

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #17669 from HyukjinKwon/revert-SPARK-20343.

[SPARK-20356][SQL] Pruned InMemoryTableScanExec should have correct output partitioning and ordering

## What changes were proposed in this pull request?

The output of `InMemoryTableScanExec` can be pruned and mismatch with `InMemoryRelation` and its child plan's output. This causes wrong output partitioning and ordering.

## How was this patch tested?

Jenkins tests.

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

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #17679 from viirya/SPARK-20356.

[SPARK-20359][SQL] Avoid unnecessary execution in EliminateOuterJoin optimization that can lead to NPE

Avoid necessary execution that can lead to NPE in EliminateOuterJoin and add test in DataFrameSuite to confirm NPE is no longer thrown

## What changes were proposed in this pull request?
Change leftHasNonNullPredicate and rightHasNonNullPredicate to lazy so they are only executed when needed.

## How was this patch tested?

Added test in DataFrameSuite that failed before this fix and now succeeds. Note that a test in catalyst project would be better but i am unsure how to do this.

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

Author: Koert Kuipers <koert@tresata.com>

Closes #17660 from koertkuipers/feat-catch-npe-in-eliminate-outer-join.