## What changes were proposed in this pull request?

```DStreams
         class FileInputDStream

 [line 162]   protected[streaming] override def clearMetadata(time: Time) {
    batchTimeToSelectedFiles.synchronized {
      val oldFiles = batchTimeToSelectedFiles.filter(_._1 < (time - rememberDuration))
      batchTimeToSelectedFiles --= oldFiles.keys

```
The above code does not remove the old generatedRDDs. "super.clearMetadata(time)" was added to the beginning of clearMetadata to remove the old generatedRDDs.

## How was this patch tested?

At the end of clearMetadata, the testing code (print the number of generatedRDDs) was added to check the old RDDS were removed manually.

Author: shaofei007 <1427357147@qq.com>
Author: Fei Shao <1427357147@qq.com>

Closes #18718 from shaofei007/master.

## What changes were proposed in this pull request?

Address scapegoat warnings for:
- BigDecimal double constructor
- Catching NPE
- Finalizer without super
- List.size is O(n)
- Prefer Seq.empty
- Prefer Set.empty
- reverse.map instead of reverseMap
- Type shadowing
- Unnecessary if condition.
- Use .log1p
- Var could be val

In some instances like Seq.empty, I avoided making the change even where valid in test code to keep the scope of the change smaller. Those issues are concerned with performance and it won't matter for tests.

## How was this patch tested?

Existing tests

Author: Sean Owen <sowen@cloudera.com>

Closes #18635 from srowen/Scapegoat1.

## What changes were proposed in this pull request?

Reload the `spark.yarn.credentials.file` property when restarting a streaming application from checkpoint.

## How was this patch tested?

Manual tested with 1.6.3 and 2.1.1.
I didn't test this with master because of some compile problems, but I think it will be the same result.

## Notice

This should be merged into maintenance branches too.

jira: [SPARK-21008](https://issues.apache.org/jira/browse/SPARK-21008)

Author: saturday_s <shi.indetail@gmail.com>

Closes #18230 from saturday-shi/SPARK-21008.

## What changes were proposed in this pull request?

This PR proposes to stop `ReceiverTracker` to close `WriteAheadLog` whenever it is and make `WriteAheadLog` and its implementations idempotent.

## How was this patch tested?

Added a test in `WriteAheadLogSuite`. Note that  the added test looks passing even if it closes twice (namely even without the changes in `FileBasedWriteAheadLog` and `BatchedWriteAheadLog`. It looks both are already idempotent but this is a rather sanity check.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #18224 from HyukjinKwon/streaming-closing.

## What changes were proposed in this pull request?

This patch adds Coda Hale metrics for instrumenting the `LiveListenerBus` in order to track the number of events received, dropped, and processed. In addition, it adds per-SparkListener-subclass timers to track message processing time. This is useful for identifying when slow third-party SparkListeners cause performance bottlenecks.

See the new `LiveListenerBusMetrics` for a complete description of the new metrics.

## How was this patch tested?

New tests in SparkListenerSuite, including a test to ensure proper counting of dropped listener events.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #18083 from JoshRosen/listener-bus-metrics.

## What changes were proposed in this pull request?

Include documentation of the fact that the updateFunc is sometimes called with no new values. This is documented in the main documentation here: https://spark.apache.org/docs/latest/streaming-programming-guide.html#updatestatebykey-operation however from the docs included with the code it is not clear that this is the case.

## How was this patch tested?

PR only changes comments. Confirmed code still builds.

Author: Wil Selwood <wil.selwood@sa.catapult.org.uk>

Closes #18088 from wselwood/note-edge-case-in-docs.

## What changes were proposed in this pull request?

Add `ThreadUtils.awaitReady` similar to `ThreadUtils.awaitResult` and disallow `Await.ready`.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #17763 from zsxwing/awaitready.

## What changes were proposed in this pull request?

Remove uses of scala.language.reflectiveCalls that are either unnecessary or probably resulting in more complex code. This turned out to be less significant than I thought, but, still worth a touch-up.

## How was this patch tested?

Existing tests.

Author: Sean Owen <sowen@cloudera.com>

Closes #17949 from srowen/SPARK-20554.

## What changes were proposed in this pull request?

Add stripXSS and stripXSSMap to Spark Core's UIUtils. Calling these functions at any point that getParameter is called against a HttpServletRequest.

## How was this patch tested?

Unit tests, IBM Security AppScan Standard no longer showing vulnerabilities, manual verification of WebUI pages.

Author: NICHOLAS T. MARION <nmarion@us.ibm.com>

Closes #17686 from n-marion/xss-fix.

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?

This PR proposes to run Spark unidoc to test Javadoc 8 build as Javadoc 8 is easily re-breakable.

There are several problems with it:

- It introduces little extra bit of time to run the tests. In my case, it took 1.5 mins more (`Elapsed :[94.8746569157]`). How it was tested is described in "How was this patch tested?".

- > One problem that I noticed was that Unidoc appeared to be processing test sources: if we can find a way to exclude those from being processed in the first place then that might significantly speed things up.

  (see  joshrosen's [comment](https://issues.apache.org/jira/browse/SPARK-18692?focusedCommentId=15947627&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15947627))

To complete this automated build, It also suggests to fix existing Javadoc breaks / ones introduced by test codes as described above.

There fixes are similar instances that previously fixed. Please refer https://github.com/apache/spark/pull/15999 and https://github.com/apache/spark/pull/16013

Note that this only fixes **errors** not **warnings**. Please see my observation https://github.com/apache/spark/pull/17389#issuecomment-288438704 for spurious errors by warnings.

## How was this patch tested?

Manually via `jekyll build` for building tests. Also, tested via running `./dev/run-tests`.

This was tested via manually adding `time.time()` as below:

```diff
     profiles_and_goals = build_profiles + sbt_goals

     print("[info] Building Spark unidoc (w/Hive 1.2.1) using SBT with these arguments: ",
           " ".join(profiles_and_goals))

+    import time
+    st = time.time()
     exec_sbt(profiles_and_goals)
+    print("Elapsed :[%s]" % str(time.time() - st))
```

produces

```
...
========================================================================
Building Unidoc API Documentation
========================================================================
...
[info] Main Java API documentation successful.
...
Elapsed :[94.8746569157]
...

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #17477 from HyukjinKwon/SPARK-18692.

[SPARK-20156][CORE][SQL][STREAMING][MLLIB] Java String toLowerCase "Turkish locale bug" causes Spark problems

## What changes were proposed in this pull request?

Add Locale.ROOT to internal calls to String `toLowerCase`, `toUpperCase`, to avoid inadvertent locale-sensitive variation in behavior (aka the "Turkish locale problem").

The change looks large but it is just adding `Locale.ROOT` (the locale with no country or language specified) to every call to these methods.

## How was this patch tested?

Existing tests.

Author: Sean Owen <sowen@cloudera.com>

Closes #17527 from srowen/SPARK-20156.

…adoc

## What changes were proposed in this pull request?

Use recommended values for row boundaries in Window's scaladoc, i.e. `Window.unboundedPreceding`, `Window.unboundedFollowing`, and `Window.currentRow` (that were introduced in 2.1.0).

## How was this patch tested?

Local build

Author: Jacek Laskowski <jacek@japila.pl>

Closes #17417 from jaceklaskowski/window-expression-scaladoc.

This change modifies the way block data is encrypted to make the more
common cases faster, while penalizing an edge case. As a side effect
of the change, all data that goes through the block manager is now
encrypted only when needed, including the previous path (broadcast
variables) where that did not happen.

The way the change works is by not encrypting data that is stored in
memory; so if a serialized block is in memory, it will only be encrypted
once it is evicted to disk.

The penalty comes when transferring that encrypted data from disk. If the
data ends up in memory again, it is as efficient as before; but if the
evicted block needs to be transferred directly to a remote executor, then
there's now a performance penalty, since the code now uses a custom
FileRegion implementation to decrypt the data before transferring.

This also means that block data transferred between executors now is
not encrypted (and thus relies on the network library encryption support
for secrecy). Shuffle blocks are still transferred in encrypted form,
since they're handled in a slightly different way by the code. This also
keeps compatibility with existing external shuffle services, which transfer
encrypted shuffle blocks, and avoids having to make the external service
aware of encryption at all.

The serialization and deserialization APIs in the SerializerManager now
do not do encryption automatically; callers need to explicitly wrap their
streams with an appropriate crypto stream before using those.

As a result of these changes, some of the workarounds added in SPARK-19520
are removed here.

Testing: a new trait ("EncryptionFunSuite") was added that provides an easy
way to run a test twice, with encryption on and off; broadcast, block manager
and caching tests were modified to use this new trait so that the existing
tests exercise both encrypted and non-encrypted paths. I also ran some
applications with encryption turned on to verify that they still work,
including streaming tests that failed without the fix for SPARK-19520.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #17295 from vanzin/SPARK-19556.

This commit adds a killTaskAttempt method to SparkContext, to allow users to
kill tasks so that they can be re-scheduled elsewhere.

This also refactors the task kill path to allow specifying a reason for the task kill. The reason is propagated opaquely through events, and will show up in the UI automatically as `(N killed: $reason)` and `TaskKilled: $reason`. Without this change, there is no way to provide the user feedback through the UI.

Currently used reasons are "stage cancelled", "another attempt succeeded", and "killed via SparkContext.killTask". The user can also specify a custom reason through `SparkContext.killTask`.

cc rxin

In the stage overview UI the reasons are summarized:
![1](https://cloud.githubusercontent.com/assets/14922/23929209/a83b2862-08e1-11e7-8b3e-ae1967bbe2e5.png)

Within the stage UI you can see individual task kill reasons:
![2](https://cloud.githubusercontent.com/assets/14922/23929200/9a798692-08e1-11e7-8697-72b27ad8a287.png)

Existing tests, tried killing some stages in the UI and verified the messages are as expected.

Author: Eric Liang <ekl@databricks.com>
Author: Eric Liang <ekl@google.com>

Closes #17166 from ericl/kill-reason.

## What changes were proposed in this pull request?

- SS python example: `TypeError: 'xxx' object is not callable`
- some other doc issue.

## How was this patch tested?

Jenkins.

Author: uncleGen <hustyugm@gmail.com>

Closes #17257 from uncleGen/docs-ss-python.

[SPARK-19822][TEST] CheckpointSuite.testCheckpointedOperation: should not filter checkpointFilesOfLatestTime with the PATH string.

## What changes were proposed in this pull request?

https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/73800/testReport/

```
sbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedDueToTimeoutException: The code
passed to eventually never returned normally. Attempted 617 times over 10.003740484 seconds.
Last failure message: 8 did not equal 2.
	at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:420)
	at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438)
	at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
	at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:336)
	at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
	at org.apache.spark.streaming.DStreamCheckpointTester$class.generateOutput(CheckpointSuite
.scala:172)
	at org.apache.spark.streaming.CheckpointSuite.generateOutput(CheckpointSuite.scala:211)
```

the check condition is:

```
val checkpointFilesOfLatestTime = Checkpoint.getCheckpointFiles(checkpointDir).filter {
     _.toString.contains(clock.getTimeMillis.toString)
}
// Checkpoint files are written twice for every batch interval. So assert that both
// are written to make sure that both of them have been written.
assert(checkpointFilesOfLatestTime.size === 2)
```

the path string may contain the `clock.getTimeMillis.toString`, like `3500` :

```
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-1000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-1500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-2000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-2500
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3000
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3500.bk
file:/root/dev/spark/assembly/CheckpointSuite/spark-20035007-9891-4fb6-91c1-cc15b7ccaf15/checkpoint-3500
                                                       ▲▲▲▲
```

so we should only check the filename, but not the whole path.

## How was this patch tested?

Jenkins.

Author: uncleGen <hustyugm@gmail.com>

Closes #17167 from uncleGen/flaky-CheckpointSuite.

## What changes were proposed in this pull request?

This PR proposes to fix the lint-breaks as below:

```
[ERROR] src/test/java/org/apache/spark/network/TransportResponseHandlerSuite.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.network.buffer.ManagedBuffer.
[ERROR] src/main/java/org/apache/spark/unsafe/types/UTF8String.java:[156,10] (modifier) ModifierOrder: 'Nonnull' annotation modifier does not precede non-annotation modifiers.
[ERROR] src/main/java/org/apache/spark/SparkFirehoseListener.java:[122] (sizes) LineLength: Line is longer than 100 characters (found 105).
[ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeExternalSorter.java:[164,78] (coding) OneStatementPerLine: Only one statement per line allowed.
[ERROR] src/test/java/test/org/apache/spark/JavaAPISuite.java:[1157] (sizes) LineLength: Line is longer than 100 characters (found 121).
[ERROR] src/test/java/org/apache/spark/streaming/JavaMapWithStateSuite.java:[149] (sizes) LineLength: Line is longer than 100 characters (found 113).
[ERROR] src/test/java/test/org/apache/spark/streaming/Java8APISuite.java:[146] (sizes) LineLength: Line is longer than 100 characters (found 122).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[32,8] (imports) UnusedImports: Unused import - org.apache.spark.streaming.Time.
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[611] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[1317] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetAggregatorSuite.java:[91] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[113] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[164] (sizes) LineLength: Line is longer than 100 characters (found 110).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[212] (sizes) LineLength: Line is longer than 100 characters (found 114).
[ERROR] src/test/java/org/apache/spark/mllib/tree/JavaDecisionTreeSuite.java:[36] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java:[26,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[20,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[94] (sizes) LineLength: Line is longer than 100 characters (found 103).
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[30,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.api.java.UDF1.
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[72] (sizes) LineLength: Line is longer than 100 characters (found 104).
[ERROR] src/main/java/org/apache/spark/examples/mllib/JavaRankingMetricsExample.java:[121] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[28,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaRDD.
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaSparkContext.
```

## How was this patch tested?

Manually via

```bash
./dev/lint-java
```

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #17072 from HyukjinKwon/java-lint.

The REST API has a security filter that performs auth checks
based on the UI root's security manager. That works fine when
the UI root is the app's UI, but not when it's the history server.

In the SHS case, all users would be allowed to see all applications
through the REST API, even if the UI itself wouldn't be available
to them.

This change adds auth checks for each app access through the API
too, so that only authorized users can see the app's data.

The change also modifies the existing security filter to use
`HttpServletRequest.getRemoteUser()`, which is used in other
places. That is not necessarily the same as the principal's
name; for example, when using Hadoop's SPNEGO auth filter,
the remote user strips the realm information, which then matches
the user name registered as the owner of the application.

I also renamed the UIRootFromServletContext trait to a more generic
name since I'm using it to store more context information now.

Tested manually with an authentication filter enabled.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #16978 from vanzin/SPARK-19652.

## What changes were proposed in this pull request?

Use `BytesWritable.copyBytes`, not `getBytes`, because `getBytes` returns the underlying array, which may be reused when repeated reads don't need a different size, as is the case with binaryRecords APIs

## How was this patch tested?

Existing tests

Author: Sean Owen <sowen@cloudera.com>

Closes #16974 from srowen/SPARK-19646.

## What changes were proposed in this pull request?

Convert tests to use Java 8 lambdas, and modest related fixes to surrounding code.

## How was this patch tested?

Jenkins tests

Author: Sean Owen <sowen@cloudera.com>

Closes #16964 from srowen/SPARK-19534.

## What changes were proposed in this pull request?

`askSync` is already added in `RpcEndpointRef` (see SPARK-19347 and https://github.com/apache/spark/pull/16690#issuecomment-276850068) and `askWithRetry` is marked as deprecated.
As mentioned SPARK-18113(https://github.com/apache/spark/pull/16503#event-927953218):

>askWithRetry is basically an unneeded API, and a leftover from the akka days that doesn't make sense anymore. It's prone to cause deadlocks (exactly because it's blocking), it imposes restrictions on the caller (e.g. idempotency) and other things that people generally don't pay that much attention to when using it.

Since `askWithRetry` is just used inside spark and not in user logic. It might make sense to replace all of them with `askSync`.

## How was this patch tested?
This PR doesn't change code logic, existing unit test can cover.

Author: jinxing <jinxing@meituan.com>

Closes #16790 from jinxing64/SPARK-19450.

- Move external/java8-tests tests into core, streaming, sql and remove
- Remove MaxPermGen and related options
- Fix some reflection / TODOs around Java 8+ methods
- Update doc references to 1.7/1.8 differences
- Remove Java 7/8 related build profiles
- Update some plugins for better Java 8 compatibility
- Fix a few Java-related warnings

For the future:

- Update Java 8 examples to fully use Java 8
- Update Java tests to use lambdas for simplicity
- Update Java internal implementations to use lambdas

## How was this patch tested?

Existing tests

Author: Sean Owen <sowen@cloudera.com>

Closes #16871 from srowen/SPARK-19493.

Spark's I/O encryption uses an ephemeral key for each driver instance.
So driver B cannot decrypt data written by driver A since it doesn't
have the correct key.

The write ahead log is used for recovery, thus needs to be readable by
a different driver. So it cannot be encrypted by Spark's I/O encryption
code.

The BlockManager APIs used by the WAL code to write the data automatically
encrypt data, so changes are needed so that callers can to opt out of
encryption.

Aside from that, the "putBytes" API in the BlockManager does not do
encryption, so a separate situation arised where the WAL would write
unencrypted data to the BM and, when those blocks were read, decryption
would fail. So the WAL code needs to ask the BM to encrypt that data
when encryption is enabled; this code is not optimal since it results
in a (temporary) second copy of the data block in memory, but should be
OK for now until a more performant solution is added. The non-encryption
case should not be affected.

Tested with new unit tests, and by running streaming apps that do
recovery using the WAL data with I/O encryption turned on.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #16862 from vanzin/SPARK-19520.

[SPARK-19347] ReceiverSupervisorImpl can add block to ReceiverTracker multiple times because of askWithRetry.

## What changes were proposed in this pull request?

`ReceiverSupervisorImpl` on executor side reports block's meta back to `ReceiverTracker` on driver side. In current code, `askWithRetry` is used. However, for `AddBlock`, `ReceiverTracker` is not idempotent, which may result in messages are processed multiple times.

**To reproduce**:

1. Check if it is the first time receiving `AddBlock` in `ReceiverTracker`, if so sleep long enough(say 200 seconds), thus the first RPC call will be timeout in `askWithRetry`, then `AddBlock` will be resent.
2. Rebuild Spark and run following job:
```
  def streamProcessing(): Unit = {
    val conf = new SparkConf()
      .setAppName("StreamingTest")
      .setMaster(masterUrl)
    val ssc = new StreamingContext(conf, Seconds(200))
    val stream = ssc.socketTextStream("localhost", 1234)
    stream.print()
    ssc.start()
    ssc.awaitTermination()
  }
```
**To fix**:

It makes sense to provide a blocking version `ask` in RpcEndpointRef, as mentioned in SPARK-18113 (https://github.com/apache/spark/pull/16503#event-927953218). Because Netty RPC layer will not drop messages. `askWithRetry` is a leftover from akka days. It imposes restrictions on the caller(e.g. idempotency) and other things that people generally don't pay that much attention to when using it.

## How was this patch tested?
Test manually. The scenario described above doesn't happen with this patch.

Author: jinxing <jinxing@meituan.com>

Closes #16690 from jinxing64/SPARK-19347.

[SPARK-19402][DOCS] Support LaTex inline formula correctly and fix warnings in Scala/Java APIs generation

## What changes were proposed in this pull request?

This PR proposes three things as below:

- Support LaTex inline-formula, `\( ... \)` in Scala API documentation
  It seems currently,

  ```
  \( ... \)
  ```

  are rendered as they are, for example,

  <img width="345" alt="2017-01-30 10 01 13" src="https://cloud.githubusercontent.com/assets/6477701/22423960/ab37d54a-e737-11e6-9196-4f6229c0189c.png">

  It seems mistakenly more backslashes were added.

- Fix warnings Scaladoc/Javadoc generation
  This PR fixes t two types of warnings as below:

  ```
  [warn] .../spark/sql/catalyst/src/main/scala/org/apache/spark/sql/Row.scala:335: Could not find any member to link for "UnsupportedOperationException".
  [warn]   /**
  [warn]   ^
  ```

  ```
  [warn] .../spark/sql/core/src/main/scala/org/apache/spark/sql/internal/VariableSubstitution.scala:24: Variable var undefined in comment for class VariableSubstitution in class VariableSubstitution
  [warn]  * `${var}`, `${system:var}` and `${env:var}`.
  [warn]      ^
  ```

- Fix Javadoc8 break
  ```
  [error] .../spark/mllib/target/java/org/apache/spark/ml/PredictionModel.java:7: error: reference not found
  [error]  *                       E.g., {link VectorUDT} for vector features.
  [error]                                       ^
  [error] .../spark/mllib/target/java/org/apache/spark/ml/PredictorParams.java:12: error: reference not found
  [error]    *                          E.g., {link VectorUDT} for vector features.
  [error]                                            ^
  [error] .../spark/mllib/target/java/org/apache/spark/ml/Predictor.java:10: error: reference not found
  [error]  *                       E.g., {link VectorUDT} for vector features.
  [error]                                       ^
  [error] .../spark/sql/hive/target/java/org/apache/spark/sql/hive/HiveAnalysis.java:5: error: reference not found
  [error]  * Note that, this rule must be run after {link PreprocessTableInsertion}.
  [error]                                                  ^
  ```

## How was this patch tested?

Manually via `sbt unidoc` and `jeykil build`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16741 from HyukjinKwon/warn-and-break.

## What changes were proposed in this pull request?

### Before
![_streaming_before](https://cloud.githubusercontent.com/assets/15843379/22181462/1e45c20c-e0c8-11e6-831c-8bf69722a4ee.png)

### After
![_streaming_after](https://cloud.githubusercontent.com/assets/15843379/22181464/23f38a40-e0c8-11e6-9a87-e27b1ffb1935.png)

## How was this patch tested?

Manually

Author: Liwei Lin <lwlin7@gmail.com>

Closes #16673 from lw-lin/streaming.

[SPARK-19182][DSTREAM] Optimize the lock in StreamingJobProgressListener to not block UI when generating Streaming jobs

## What changes were proposed in this pull request?

When DStreamGraph is generating a job, it will hold a lock and block other APIs. Because StreamingJobProgressListener (numInactiveReceivers, streamName(streamId: Int), streamIds) needs to call DStreamGraph's methods to access some information, the UI may hang if generating a job is very slow (e.g., talking to the slow Kafka cluster to fetch metadata).
It's better to optimize the locks in DStreamGraph and StreamingJobProgressListener to make the UI not block by job generation.

## How was this patch tested?
existing ut

cc zsxwing

Author: uncleGen <hustyugm@gmail.com>

Closes #16601 from uncleGen/SPARK-19182.

## What changes were proposed in this pull request?

the current implementation of Spark streaming considers a batch is completed no matter the results of the jobs (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L203)
Let's consider the following case:
A micro batch contains 2 jobs and they read from two different kafka topics respectively. One of these jobs is failed due to some problem in the user defined logic, after the other one is finished successfully.
1. The main thread in the Spark streaming application will execute the line mentioned above,
2. and another thread (checkpoint writer) will make a checkpoint file immediately after this line is executed.
3. Then due to the current error handling mechanism in Spark Streaming, StreamingContext will be closed (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L214)
the user recovers from the checkpoint file, and because the JobSet containing the failed job has been removed (taken as completed) before the checkpoint is constructed, the data being processed by the failed job would never be reprocessed

This PR fix it by removing jobset from JobScheduler.jobSets only when all jobs in a jobset are successfully finished

## How was this patch tested?

existing tests

Author: CodingCat <zhunansjtu@gmail.com>
Author: Nan Zhu <zhunansjtu@gmail.com>

Closes #16542 from CodingCat/SPARK-18905.

[SPARK-18922][SQL][CORE][STREAMING][TESTS] Fix all identified tests failed due to path and resource-not-closed problems on Windows

## What changes were proposed in this pull request?

This PR proposes to fix all the test failures identified by testing with AppVeyor.

**Scala - aborted tests**

```
WindowQuerySuite:
  Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.execution.WindowQuerySuite *** ABORTED *** (156 milliseconds)
   org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive   argetscala-2.11   est-classesdatafilespart_tiny.txt;

OrcSourceSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.orc.OrcSourceSuite *** ABORTED *** (62 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

ParquetMetastoreSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetMetastoreSuite *** ABORTED *** (4 seconds, 703 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

ParquetSourceSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetSourceSuite *** ABORTED *** (3 seconds, 907 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark  arget mpspark-581a6575-454f-4f21-a516-a07f95266143;

KafkaRDDSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaRDDSuite *** ABORTED *** (5 seconds, 212 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-4722304d-213e-4296-b556-951df1a46807

DirectKafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.DirectKafkaStreamSuite *** ABORTED *** (7 seconds, 127 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d0d3eba7-4215-4e10-b40e-bb797e89338e
   at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010)

ReliableKafkaStreamSuite
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.ReliableKafkaStreamSuite *** ABORTED *** (5 seconds, 498 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d33e45a0-287e-4bed-acae-ca809a89d888

KafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaStreamSuite *** ABORTED *** (2 seconds, 892 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-59c9d169-5a56-4519-9ef0-cefdbd3f2e6c

KafkaClusterSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaClusterSuite *** ABORTED *** (1 second, 690 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-3ef402b0-8689-4a60-85ae-e41e274f179d

DirectKafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.DirectKafkaStreamSuite *** ABORTED *** (59 seconds, 626 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-426107da-68cf-4d94-b0d6-1f428f1c53f6

KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.KafkaRDDSuite *** ABORTED *** (2 minutes, 6 seconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-b9ce7929-5dae-46ab-a0c4-9ef6f58fbc2
```

**Java - failed tests**

```
Test org.apache.spark.streaming.kafka.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-1cee32f4-4390-4321-82c9-e8616b3f0fb0, took 9.61 sec

Test org.apache.spark.streaming.kafka.JavaKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-f42695dd-242e-4b07-847c-f299b8e4676e, took 11.797 sec

Test org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-85c0d062-78cf-459c-a2dd-7973572101ce, took 1.581 sec

Test org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-49eb6b5c-8366-47a6-83f2-80c443c48280, took 17.895 sec

org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-898cf826-d636-4b1c-a61a-c12a364c02e7, took 8.858 sec
```

**Scala - failed tests**

```
PartitionProviderCompatibilitySuite:
 - insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (828 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-bb6337b9-4f99-45ab-ad2c-a787ab965c09

 - SPARK-18635 special chars in partition values - partition management true *** FAILED *** (5 seconds, 360 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - SPARK-18635 special chars in partition values - partition management false *** FAILED *** (141 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
UtilsSuite:
 - reading offset bytes of a file (compressed) *** FAILED *** (0 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-ecb2b7d5-db8b-43a7-b268-1bf242b5a491

 - reading offset bytes across multiple files (compressed) *** FAILED *** (0 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-25cc47a8-1faa-4da5-8862-cf174df63ce0
```

```
StatisticsSuite:
 - MetastoreRelations fallback to HDFS for size estimation *** FAILED *** (110 milliseconds)
   org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'csv_table' not found in database 'default';
```

```
SQLQuerySuite:
 - permanent UDTF *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count_temp'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 24

 - describe functions - user defined functions *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 7

 - CTAS without serde with location *** FAILED *** (16 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-ed673d73-edfc-404e-829e-2e2b9725d94e/c1

 - derived from Hive query file: drop_database_removes_partition_dirs.q *** FAILED *** (47 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_database_removes_partition_dirs_table

 - derived from Hive query file: drop_table_removes_partition_dirs.q *** FAILED *** (0 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_table_removes_partition_dirs_table2

 - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH *** FAILED *** (109 milliseconds)
   java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/sql/hive/projectsspark	arget	mpspark-1a122f8c-dfb3-46c4-bab1-f30764baee0e/*part-r*
```

```
HiveDDLSuite:
 - drop external tables in default database *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - add/drop partitions - external table *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - create/drop database - location without pre-created directory *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - create/drop database - location with pre-created directory *** FAILED *** (32 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - drop database containing tables - CASCADE *** FAILED *** (94 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop an empty database - CASCADE *** FAILED *** (63 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop database containing tables - RESTRICT *** FAILED *** (47 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop an empty database - RESTRICT *** FAILED *** (47 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - CREATE TABLE LIKE an external data source table *** FAILED *** (140 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-c5eba16d-07ae-4186-95bb-21c5811cf888;

 - CREATE TABLE LIKE an external Hive serde table *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - desc table for data source table - no user-defined schema *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-e8bf5bf5-721a-4cbe-9d6	at scala.collection.immutable.List.foreach(List.scala:381)d-5543a8301c1d;
```

```
MetastoreDataSourcesSuite
 - CTAS: persisted bucketed data source table *** FAILED *** (16 milliseconds)
   java.lang.IllegalArgumentException: Can not create a Path from an empty string
```

```
ShowCreateTableSuite:
 - simple external hive table *** FAILED *** (0 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
PartitionedTablePerfStatsSuite:
 - hive table: partitioned pruned table reports only selected files *** FAILED *** (313 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: partitioned pruned table reports only selected files *** FAILED *** (219 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-311f45f8-d064-4023-a4bb-e28235bff64d;

 - hive table: lazy partition pruning reads only necessary partition data *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: lazy partition pruning reads only necessary partition data *** FAILED *** (187 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-fde874ca-66bd-4d0b-a40f-a043b65bf957;

 - hive table: lazy partition pruning with file status caching enabled *** FAILED *** (188 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: lazy partition pruning with file status caching enabled *** FAILED *** (187 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-e6d20183-dd68-4145-acbe-4a509849accd;

 - hive table: file status caching respects refresh table and refreshByPath *** FAILED *** (172 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: file status caching respects refresh table and refreshByPath *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-8b2c9651-2adf-4d58-874f-659007e21463;

 - hive table: file status cache respects size limit *** FAILED *** (219 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: file status cache respects size limit *** FAILED *** (171 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-7835ab57-cb48-4d2c-bb1d-b46d5a4c47e4;

 - datasource table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-20598d76-c004-42a7-8061-6c56f0eda5e2;

 - hive table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - hive table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 281 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 422 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-4cfed321-4d1d-4b48-8d34-5c169afff383;

 - hive table: files read and cached when filesource partition management is off *** FAILED *** (234 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: all partition data cached in memory when partition management is off *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-4bcc0398-15c9-4f6a-811e-12d40f3eec12;

 - SPARK-18700: table loaded only once even when resolved concurrently *** FAILED *** (1 second, 266 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
HiveSparkSubmitSuite:
 - temporary Hive UDF: define a UDF and use it *** FAILED *** (2 seconds, 94 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - permanent Hive UDF: define a UDF and use it *** FAILED *** (281 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - permanent Hive UDF: use a already defined permanent function *** FAILED *** (718 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8368: includes jars passed in through --jars *** FAILED *** (3 seconds, 521 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8020: set sql conf in spark conf *** FAILED *** (0 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8489: MissingRequirementError during reflection *** FAILED *** (94 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-9757 Persist Parquet relation with decimal column *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-11009 fix wrong result of Window function in cluster mode *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-14244 fix window partition size attribute binding failure *** FAILED *** (78 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - set spark.sql.warehouse.dir *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - set hive.metastore.warehouse.dir *** FAILED *** (15 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-16901: set javax.jdo.option.ConnectionURL *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-18360: default table path of tables in default database should depend on the location of default database *** FAILED *** (15 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
```

```
UtilsSuite:
 - resolveURIs with multiple paths *** FAILED *** (0 milliseconds)
   ".../jar3,file:/C:/pi.py[%23]py.pi,file:/C:/path%..." did not equal ".../jar3,file:/C:/pi.py[#]py.pi,file:/C:/path%..." (UtilsSuite.scala:468)
```

```
CheckpointSuite:
 - recovery with file input stream *** FAILED *** (10 seconds, 205 milliseconds)
   The code passed to eventually never returned normally. Attempted 660 times over 10.014272499999999 seconds. Last failure message: Unexpected internal error near index 1
   \
    ^. (CheckpointSuite.scala:680)
```

## How was this patch tested?

Manually via AppVeyor as below:

**Scala - aborted tests**

```
WindowQuerySuite - all passed
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
  org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
  at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
ParquetMetastoreSuite - all passed
ParquetSourceSuite - all passed
KafkaRDDSuite - all passed
DirectKafkaStreamSuite - all passed
ReliableKafkaStreamSuite - all passed
KafkaStreamSuite - all passed
KafkaClusterSuite - all passed
DirectKafkaStreamSuite - all passed
KafkaRDDSuite - all passed
```

**Java - failed tests**

```
org.apache.spark.streaming.kafka.JavaKafkaRDDSuite - all passed
org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka.JavaKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite - all passed
```

**Scala - failed tests**

```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition (1 second, 953 milliseconds)
- SPARK-18635 special chars in partition values - partition management true (6 seconds, 31 milliseconds)
- SPARK-18635 special chars in partition values - partition management false (4 seconds, 578 milliseconds)
```

```
UtilsSuite:
- reading offset bytes of a file (compressed) (203 milliseconds)
- reading offset bytes across multiple files (compressed) (0 milliseconds)
```

```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation (94 milliseconds)
```

```
SQLQuerySuite:
 - permanent UDTF (407 milliseconds)
 - describe functions - user defined functions (441 milliseconds)
 - CTAS without serde with location (2 seconds, 831 milliseconds)
 - derived from Hive query file: drop_database_removes_partition_dirs.q (734 milliseconds)
 - derived from Hive query file: drop_table_removes_partition_dirs.q (563 milliseconds)
 - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH (453 milliseconds)
```

```
HiveDDLSuite:
 - drop external tables in default database (3 seconds, 5 milliseconds)
 - add/drop partitions - external table (2 seconds, 750 milliseconds)
 - create/drop database - location without pre-created directory (500 milliseconds)
 - create/drop database - location with pre-created directory (407 milliseconds)
 - drop database containing tables - CASCADE (453 milliseconds)
 - drop an empty database - CASCADE (375 milliseconds)
 - drop database containing tables - RESTRICT (328 milliseconds)
 - drop an empty database - RESTRICT (391 milliseconds)
 - CREATE TABLE LIKE an external data source table (953 milliseconds)
 - CREATE TABLE LIKE an external Hive serde table (3 seconds, 782 milliseconds)
 - desc table for data source table - no user-defined schema (1 second, 150 milliseconds)
```

```
MetastoreDataSourcesSuite
 - CTAS: persisted bucketed data source table (875 milliseconds)
```

```
ShowCreateTableSuite:
 - simple external hive table (78 milliseconds)
```

```
PartitionedTablePerfStatsSuite:
 - hive table: partitioned pruned table reports only selected files (1 second, 109 milliseconds)
- datasource table: partitioned pruned table reports only selected files (860 milliseconds)
 - hive table: lazy partition pruning reads only necessary partition data (859 milliseconds)
 - datasource table: lazy partition pruning reads only necessary partition data (1 second, 219 milliseconds)
 - hive table: lazy partition pruning with file status caching enabled (875 milliseconds)
 - datasource table: lazy partition pruning with file status caching enabled (890 milliseconds)
 - hive table: file status caching respects refresh table and refreshByPath (922 milliseconds)
 - datasource table: file status caching respects refresh table and refreshByPath (640 milliseconds)
 - hive table: file status cache respects size limit (469 milliseconds)
 - datasource table: file status cache respects size limit (453 milliseconds)
 - datasource table: table setup does not scan filesystem (328 milliseconds)
 - hive table: table setup does not scan filesystem (313 milliseconds)
 - hive table: num hive client calls does not scale with partition count (5 seconds, 431 milliseconds)
 - datasource table: num hive client calls does not scale with partition count (4 seconds, 79 milliseconds)
 - hive table: files read and cached when filesource partition management is off (656 milliseconds)
 - datasource table: all partition data cached in memory when partition management is off (484 milliseconds)
 - SPARK-18700: table loaded only once even when resolved concurrently (2 seconds, 578 milliseconds)
```

```
HiveSparkSubmitSuite:
 - temporary Hive UDF: define a UDF and use it (1 second, 745 milliseconds)
 - permanent Hive UDF: define a UDF and use it (406 milliseconds)
 - permanent Hive UDF: use a already defined permanent function (375 milliseconds)
 - SPARK-8368: includes jars passed in through --jars (391 milliseconds)
 - SPARK-8020: set sql conf in spark conf (156 milliseconds)
 - SPARK-8489: MissingRequirementError during reflection (187 milliseconds)
 - SPARK-9757 Persist Parquet relation with decimal column (157 milliseconds)
 - SPARK-11009 fix wrong result of Window function in cluster mode (156 milliseconds)
 - SPARK-14244 fix window partition size attribute binding failure (156 milliseconds)
 - set spark.sql.warehouse.dir (172 milliseconds)
 - set hive.metastore.warehouse.dir (156 milliseconds)
 - SPARK-16901: set javax.jdo.option.ConnectionURL (157 milliseconds)
 - SPARK-18360: default table path of tables in default database should depend on the location of default database (172 milliseconds)
```

```
UtilsSuite:
 - resolveURIs with multiple paths (0 milliseconds)
```

```
CheckpointSuite:
 - recovery with file input stream (4 seconds, 452 milliseconds)
```

Note: after resolving the aborted tests, there is a test failure identified as below:

```
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
  org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
  at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
```

This does not look due to this problem so this PR does not fix it here.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16451 from HyukjinKwon/all-path-resource-fixes.

## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.

## How was this patch tested?
N/A since only docs or comments were updated.

Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>

Closes #16455 from neurons/np.structure_streaming_doc.

## What changes were proposed in this pull request?

This PR is an inheritance from #16000, and is a completion of #15904.

**Description**

- Augment the `org.apache.spark.status.api.v1` package for serving streaming information.
- Retrieve the streaming information through StreamingJobProgressListener.

> this api should cover exceptly the same amount of information as you can get from the web interface
> the implementation is base on the current REST implementation of spark-core
> and will be available for running applications only
>
> https://issues.apache.org/jira/browse/SPARK-18537

## How was this patch tested?

Local test.

Author: saturday_s <shi.indetail@gmail.com>
Author: Chan Chor Pang <ChorPang.Chan@access-company.com>
Author: peterCPChan <universknight@gmail.com>

Closes #16253 from saturday-shi/SPARK-18537.

## What changes were proposed in this pull request?

https://spark-tests.appspot.com/test-details?suite_name=org.apache.spark.streaming.InputStreamsSuite&test_name=socket+input+stream

## How was this patch tested?

Tested 2,000 times.

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #16343 from brkyvz/sock.

Remove spark-tag's compile-scope dependency (and, indirectly, spark-core's compile-scope transitive-dependency) on scalatest by splitting test-oriented tags into spark-tags' test JAR.

Alternative to #16303.

Author: Ryan Williams <ryan.blake.williams@gmail.com>

Closes #16311 from ryan-williams/tt.

[SPARK-18954][TESTS] Fix flaky test: o.a.s.streaming.BasicOperationsSuite rdd cleanup - map and window

## What changes were proposed in this pull request?

The issue in this test is the cleanup of RDDs may not be able to finish before stopping StreamingContext. This PR basically just puts the assertions into `eventually` and runs it before stopping StreamingContext.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16362 from zsxwing/SPARK-18954.

## What changes were proposed in this pull request?

The failure is because in `test("basic functionality")`, it doesn't block until `ExecutorAllocationManager.manageAllocation` is called. This PR just adds StreamManualClock to allow the tests to block on expected wait time to make the test deterministic.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16321 from zsxwing/SPARK-18031.

## What changes were proposed in this pull request?
This patch bumps master branch version to 2.2.0-SNAPSHOT.

## How was this patch tested?
N/A

Author: Reynold Xin <rxin@databricks.com>

Closes #16126 from rxin/SPARK-18695.

[SPARK-18617][SPARK-18560][TESTS] Fix flaky test: StreamingContextSuite. Receiver data should be deserialized properly

## What changes were proposed in this pull request?

Avoid to create multiple threads to stop StreamingContext. Otherwise, the latch added in #16091 can be passed too early.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16105 from zsxwing/SPARK-18617-2.

[SPARK-18617][SPARK-18560][TEST] Fix flaky test: StreamingContextSuite. Receiver data should be deserialized properly

## What changes were proposed in this pull request?

Fixed the potential SparkContext leak in `StreamingContextSuite.SPARK-18560 Receiver data should be deserialized properly` which was added in #16052. I also removed FakeByteArrayReceiver and used TestReceiver directly.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16091 from zsxwing/SPARK-18617-follow-up.

## What changes were proposed in this pull request?

#15992 provided a solution to fix the bug, i.e. **receiver data can not be deserialized properly**. As zsxwing said, it is a critical bug, but we should not break APIs between maintenance releases. It may be a rational choice to close auto pick kryo serializer for Spark Streaming in the first step. I will continue #15992 to optimize the solution.

## How was this patch tested?

existing ut

Author: uncleGen <hustyugm@gmail.com>

Closes #16052 from uncleGen/SPARK-18617.