### What changes were proposed in this pull request?
Currently, we have a bug when we specify `IF NOT EXISTS` in `INSERT OVERWRITE` data source tables. For example, given a query:
```SQL
INSERT OVERWRITE TABLE $tableName partition (b=2, c=3) IF NOT EXISTS SELECT 9, 10
```
we will get the following error:
```
unresolved operator 'InsertIntoTable Relation[a#425,d#426,b#427,c#428] parquet, Map(b -> Some(2), c -> Some(3)), true, true;;
'InsertIntoTable Relation[a#425,d#426,b#427,c#428] parquet, Map(b -> Some(2), c -> Some(3)), true, true
+- Project [cast(9#423 as int) AS a#429, cast(10#424 as int) AS d#430]
   +- Project [9 AS 9#423, 10 AS 10#424]
      +- OneRowRelation$
```

This PR is to fix the issue to follow the behavior of Hive serde tables
> INSERT OVERWRITE will overwrite any existing data in the table or partition unless IF NOT EXISTS is provided for a partition

### How was this patch tested?
Modified an existing test case

Author: gatorsmile <gatorsmile@gmail.com>

Closes #18050 from gatorsmile/insertPartitionIfNotExists.

## What changes were proposed in this pull request?

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

## How was this patch tested?

Added test in MapStatusSuite.

Author: jinxing <jinxing6042@126.com>

Closes #18031 from jinxing64/SPARK-20801.

## What changes were proposed in this pull request?
On status column of the table, I removed the condition  that forced only the display value to take on values Active, Blacklisted and Dead.

Before the removal, values used for sort and filter for that particular column was True and False.
## How was this patch tested?

Tested with Active, Blacklisted and Dead present as current status.

Author: John Lee <jlee2@yahoo-inc.com>

Closes #18036 from yoonlee95/SPARK-20813.

## What changes were proposed in this pull request?
This PR solution to run the SortShuffleSuite unit tests have residual spark_* system directory
For example:
OS:Windows 7
After the running SortShuffleSuite unit tests,
the system of TMP directory have '..\AppData\Local\Temp\spark-f64121f9-11b4-4ffd-a4f0-cfca66643503' not deleted

## How was this patch tested?
Run SortShuffleSuite unit test.

Author: caoxuewen <cao.xuewen@zte.com.cn>

Closes #17869 from heary-cao/SortShuffleSuite.

[SPARK-20591][WEB UI] Succeeded tasks num not equal in all jobs page and job detail page on spark web ui when speculative task(s) exist.

## What changes were proposed in this pull request?

Modified succeeded num in job detail page from "completed = stageData.completedIndices.size" to "completed = stageData.numCompleteTasks",which making succeeded tasks num in all jobs page and job detail page look more consistent, and more easily to find which stages the speculative task(s) were in.

## How was this patch tested?

manual tests

Author: fjh100456 <fu.jinhua6@zte.com.cn>

Closes #17923 from fjh100456/master.

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

## How was this patch tested?

Built docs locally and tested links.

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

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

## What changes were proposed in this pull request?

When two Breeze SparseMatrices are operated, the result matrix may contain provisional 0 values extra in rowIndices and data arrays. This causes an incoherence with the colPtrs data, but Breeze get away with this incoherence by keeping a counter of the valid data.

In spark, when this matrices are converted to SparseMatrices, Sparks relies solely on rowIndices, data, and colPtrs, but these might be incorrect because of breeze internal hacks. Therefore, we need to slice both rowIndices and data, using their counter of active data

This method is at least called by BlockMatrix when performing distributed block operations, causing exceptions on valid operations.

See http://stackoverflow.com/questions/33528555/error-thrown-when-using-blockmatrix-add

## How was this patch tested?

Added a test to MatricesSuite that verifies that the conversions are valid and that code doesn't crash. Originally the same code would crash on Spark.

Bugfix for https://issues.apache.org/jira/browse/SPARK-20687

Author: Ignacio Bermudez <ignaciobermudez@gmail.com>
Author: Ignacio Bermudez Corrales <icorrales@splunk.com>

Closes #17940 from ghoto/bug-fix/SPARK-20687.

## What changes were proposed in this pull request?

Replaced specific sequence encoders with generic sequence encoder to enable nesting of sequences.

Does not add support for nested arrays as that cannot be solved in this way.

## How was this patch tested?

```bash
build/mvn -DskipTests clean package && dev/run-tests
```

Additionally in Spark shell:

```
scala> Seq(Seq(Seq(1))).toDS.collect()
res0: Array[Seq[Seq[Int]]] = Array(List(List(1)))
```

Author: Michal Senkyr <mike.senkyr@gmail.com>

Closes #18011 from michalsenkyr/dataset-seq-nested.

## What changes were proposed in this pull request?

This PR improves the implementation of `ColumnStats` by using the following appoaches.

1. Declare subclasses of `ColumnStats` as `final`
2. Remove unnecessary call of `row.isNullAt(ordinal)`
3. Remove the dependency on `GenericInternalRow`

For 1., this declaration encourages method inlining and other optimizations of JIT compiler
For 2., in `gatherStats()`, while previous code in subclasses of `ColumnStats` always calls `row.isNullAt()` twice, the PR just calls `row.isNullAt()` only once.
For 3., `collectedStatistics()` returns `Array[Any]` instead of `GenericInternalRow`. This removes the dependency of unnecessary package and reduces the number of allocations of `GenericInternalRow`.

In addition to that, in the future, `gatherValueStats()`, which is specialized for each data type, can be effectively called from the generated code without using generic data structure `InternalRow`.

## How was this patch tested?

Tested by existing test suite

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

Closes #18002 from kiszk/SPARK-20770.

## What changes were proposed in this pull request?

spark-sql>SELECT ceil(1234567890123456);
1234567890123456

spark-sql>SELECT ceil(12345678901234567);
12345678901234568

spark-sql>SELECT ceil(123456789012345678);
123456789012345680

when the length of the getText is greater than 16. long to double will be precision loss.

but mysql handle the value is ok.

mysql> SELECT ceil(1234567890123456);
+------------------------+
| ceil(1234567890123456) |
+------------------------+
|       1234567890123456 |
+------------------------+
1 row in set (0.00 sec)

mysql> SELECT ceil(12345678901234567);
+-------------------------+
| ceil(12345678901234567) |
+-------------------------+
|       12345678901234567 |
+-------------------------+
1 row in set (0.00 sec)

mysql> SELECT ceil(123456789012345678);
+--------------------------+
| ceil(123456789012345678) |
+--------------------------+
|       123456789012345678 |
+--------------------------+
1 row in set (0.00 sec)

## How was this patch tested?

Supplement the unit test.

Author: caoxuewen <cao.xuewen@zte.com.cn>

Closes #18016 from heary-cao/ceil_long.

## What changes were proposed in this pull request?
PySpark StringIndexer supports StringOrderType added in #17879.

Author: Wayne Zhang <actuaryzhang@uber.com>

Closes #17978 from actuaryzhang/PythonStringIndexer.

[SPARK-20792][SS] Support same timeout operations in mapGroupsWithState function in batch queries as in streaming queries

## What changes were proposed in this pull request?

Currently, in the batch queries, timeout is disabled (i.e. GroupStateTimeout.NoTimeout) which means any GroupState.setTimeout*** operation would throw UnsupportedOperationException. This makes it weird when converting a streaming query into a batch query by changing the input DF from streaming to a batch DF. If the timeout was enabled and used, then the batch query will start throwing UnsupportedOperationException.

This PR creates the dummy state in batch queries with the provided timeoutConf so that it behaves in the same way. The code has been refactored to make it obvious when the state is being created for a batch query or a streaming query.

## How was this patch tested?
Additional tests

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #18024 from tdas/SPARK-20792.

## What changes were proposed in this pull request?

Remove redundant check for libdir in CommandBuilderUtils

## How was this patch tested?

Existing tests

Author: Sean Owen <sowen@cloudera.com>

Closes #18032 from srowen/SPARK-20806.

[https://issues.apache.org/jira/browse/SPARK-20781](https://issues.apache.org/jira/browse/SPARK-20781)
the location of Dockerfile in docker.properties.template should be "../external/docker/spark-mesos/Dockerfile"

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

Closes #18013 from liu-zhaokun/dockerfile_location.

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

## How was this patch tested?

Build doc locally.

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

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

## What changes were proposed in this pull request?
Some examples in the DataFrame methods are syntactically wrong, even though they are pseudo code. Fix these and some style issues.

Author: Wayne Zhang <actuaryzhang@uber.com>

Closes #18003 from actuaryzhang/sparkRDoc3.

## What changes were proposed in this pull request?

Rename `carsDF` to `df` in SparkR `rollup` and `cube` examples.

## How was this patch tested?

Manual tests.

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

Closes #17988 from zero323/cube-docs.

## What changes were proposed in this pull request?
spark-sql>select month("1582-09-28");
spark-sql>10
For this case, the expected result is 9, but it is 10.

spark-sql>select day("1582-04-18");
spark-sql>28
For this case, the expected result is 18, but it is 28.

when the date  before "1582-10-04", the function of `month` and `day` return the value which is not we expected.

## How was this patch tested?
unit tests

Author: liuxian <liu.xian3@zte.com.cn>

Closes #17997 from 10110346/wip_lx_0516.

## What changes were proposed in this pull request?

Add built-in SQL Function - COT.

## How was this patch tested?

unit tests

Author: Yuming Wang <wgyumg@gmail.com>

Closes #17999 from wangyum/SPARK-20751.

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

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

Closes #17992 from liu-zhaokun/new.

## What changes were proposed in this pull request?

This PR update to two:
1.adds the new unit tests.
  testing would be performed when there is no shuffle stage,
  shuffle will not generate the data file and the index files.
2.Modify the '[SPARK-4085] rerun map stage if reduce stage cannot find its local shuffle file' unit test,
  parallelize is 1 but not is 2, Check the index file and delete.

## How was this patch tested?
The new unit test.

Author: caoxuewen <cao.xuewen@zte.com.cn>

Closes #17868 from heary-cao/ShuffleSuite.

Fix quadratic List indexing in ParquetWriteSupport.

I noticed this function while profiling some code with today. It showed up as a significant factor in a table with twenty columns; with hundreds of columns, it could dominate any other function call.

## What changes were proposed in this pull request?

The writeFields method iterates from 0 until number of fields, indexing into rootFieldWriters for each element. rootFieldWriters is a List, so indexing is a linear operation. The complexity of the writeFields method is thus quadratic in the number of fields.

Solution: explicitly convert rootFieldWriters to Array (implicitly converted to WrappedArray) for constant-time indexing.

## How was this patch tested?

This is a one-line change for performance reasons.

Author: tpoterba <tpoterba@broadinstitute.org>
Author: Tim Poterba <tpoterba@gmail.com>

Closes #18005 from tpoterba/tpoterba-patch-1.

## What changes were proposed in this pull request?

GenerateUnsafeProjection.writeStructToBuffer() did not honor the assumption that the caller must make sure that a value is not null before using the getter. This could lead to various errors. This change fixes that behavior.

Example of code generated before:
```scala
/* 059 */         final UTF8String fieldName = value.getUTF8String(0);
/* 060 */         if (value.isNullAt(0)) {
/* 061 */           rowWriter1.setNullAt(0);
/* 062 */         } else {
/* 063 */           rowWriter1.write(0, fieldName);
/* 064 */         }
```

Example of code generated now:
```scala
/* 060 */         boolean isNull1 = value.isNullAt(0);
/* 061 */         UTF8String value1 = isNull1 ? null : value.getUTF8String(0);
/* 062 */         if (isNull1) {
/* 063 */           rowWriter1.setNullAt(0);
/* 064 */         } else {
/* 065 */           rowWriter1.write(0, value1);
/* 066 */         }
```

## How was this patch tested?

Adds GenerateUnsafeProjectionSuite.

Author: Ala Luszczak <ala@databricks.com>

Closes #18030 from ala/fix-generate-unsafe-projection.

## What changes were proposed in this pull request?

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

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

cc budde , brkyvz

Author: Yash Sharma <ysharma@atlassian.com>

Closes #18028 from yssharma/ysharma/kinesis_retry_docs.

## What changes were proposed in this pull request?

This is an alternative workaround by simply avoiding the predicate pushdown for columns having dots in the names. This is an approach different with https://github.com/apache/spark/pull/17680.

The downside of this PR is, literally it does not push down filters on the column having dots in Parquet files at all (both no record level and no rowgroup level) whereas the downside of the approach in that PR, it does not use the Parquet's API properly but in a hacky way to support this case.

I assume we prefer a safe way here by using the Parquet API properly but this does close that PR as we are basically just avoiding here.

This way looks a simple workaround and probably it is fine given the problem looks arguably rather corner cases (although it might end up with reading whole row groups under the hood but either looks not the best).

Currently, if there are dots in the column name, predicate pushdown seems being failed in Parquet.

**With dots**

```scala
val path = "/tmp/abcde"
Seq(Some(1), None).toDF("col.dots").write.parquet(path)
spark.read.parquet(path).where("`col.dots` IS NOT NULL").show()
```

```
+--------+
|col.dots|
+--------+
+--------+
```

**Without dots**

```scala
val path = "/tmp/abcde"
Seq(Some(1), None).toDF("coldots").write.parquet(path)
spark.read.parquet(path).where("`coldots` IS NOT NULL").show()
```

```
+-------+
|coldots|
+-------+
|      1|
+-------+
```

**After**

```scala
val path = "/tmp/abcde"
Seq(Some(1), None).toDF("col.dots").write.parquet(path)
spark.read.parquet(path).where("`col.dots` IS NOT NULL").show()
```

```
+--------+
|col.dots|
+--------+
|       1|
+--------+
```

## How was this patch tested?

Unit tests added in `ParquetFilterSuite`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #18000 from HyukjinKwon/SPARK-20364-workaround.

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

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

Closes #18027 from liu-zhaokun/sbin.

## What changes were proposed in this pull request?

The license is not at the top in some files. and it will be best if we update these places of the ASF header to be consistent with other files.

## How was this patch tested?

manual tests

Author: zuotingbing <zuo.tingbing9@zte.com.cn>

Closes #18012 from zuotingbing/spark-license.

## What changes were proposed in this pull request?

This PR proposes to close PRs ...

  - inactive to the review comments more than a month
  - WIP and inactive more than a month
  - with Jenkins build failure but inactive more than a month
  - suggested to be closed and no comment against that
  - obviously looking inappropriate (e.g., Branch 0.5)

To make sure, I left a comment for each PR about a week ago and I could not have a response back from the author in these PRs below:

Closes #11129
Closes #12085
Closes #12162
Closes #12419
Closes #12420
Closes #12491
Closes #13762
Closes #13837
Closes #13851
Closes #13881
Closes #13891
Closes #13959
Closes #14091
Closes #14481
Closes #14547
Closes #14557
Closes #14686
Closes #15594
Closes #15652
Closes #15850
Closes #15914
Closes #15918
Closes #16285
Closes #16389
Closes #16652
Closes #16743
Closes #16893
Closes #16975
Closes #17001
Closes #17088
Closes #17119
Closes #17272
Closes #17971

Added:
Closes #17778
Closes #17303
Closes #17872

## How was this patch tested?

N/A

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #18017 from HyukjinKwon/close-inactive-prs.

## What changes were proposed in this pull request?

In the previous approach we used `aliasMap` to link an `Attribute` to the expression with potentially the form `f(a, b)`, but we only searched the `expressions` and `children.expressions` for this, which is not enough when an `Alias` may lies deep in the logical plan. In that case, we can't generate the valid equivalent constraint classes and thus we fail at preventing the recursive deductions.

We fix this problem by collecting all `Alias`s from the logical plan.

## How was this patch tested?

No additional test case is added, but do modified one test case to cover this situation.

Author: Xingbo Jiang <xingbo.jiang@databricks.com>

Closes #18020 from jiangxb1987/inferConstrants.

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

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

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #17994 from yanboliang/spark-20505.

## What changes were proposed in this pull request?

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?

Executor task reaper may fail to detect if a task is finished or not when a task is finishing but being killed at the same time.

The fix is pretty easy, just flip the "finished" flag when a task is successful.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #18021 from zsxwing/SPARK-20788.

## What changes were proposed in this pull request?

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

## How was this patch tested?

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

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

Closes #18001 from aray/patch-1.

## What changes were proposed in this pull request?

In

```
./bin/spark-shell --master=local[64]
```

I ran

```
sc.parallelize(1 to 100000, 100000).count()
```
and profiled the time spend in the LiveListenerBus event processing thread. I discovered that the majority of the time was being spent in `TaskMetrics.empty` calls in `JobProgressListener.onTaskStart`. It turns out that we can slightly refactor to remove the need to construct one empty instance per call, greatly improving the performance of this code.

The performance gains here help to avoid an issue where listener events would be dropped because the JobProgressListener couldn't keep up with the throughput.

**Before:**

![image](https://cloud.githubusercontent.com/assets/50748/26133095/95bcd42a-3a59-11e7-8051-a50550e447b8.png)

**After:**

![image](https://cloud.githubusercontent.com/assets/50748/26133070/7935e148-3a59-11e7-8c2d-73d5aa5a2397.png)

## How was this patch tested?

Benchmarks described above.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #18008 from JoshRosen/nametoaccums-improvements.

## What changes were proposed in this pull request?

We add missing attributes into Filter in Analyzer. But we shouldn't do it through subqueries like this:

    select 1 from  (select 1 from onerow t1 LIMIT 1) where  t1.c1=1

This query works in current codebase. However, the outside where clause shouldn't be able to refer `t1.c1` attribute.

The root cause is we allow subqueries in FROM have no alias names previously, it is confusing and isn't supported by various databases such as MySQL, Postgres, Oracle. We shouldn't support it too.

## 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 #17935 from viirya/SPARK-20690.

## What changes were proposed in this pull request?
Currently the parser logs the query it is parsing at `info` level. This is too high, this PR lowers the log level to `debug`.

## How was this patch tested?
Existing tests.

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

Closes #18006 from hvanhovell/lower_parser_log_level.

## What changes were proposed in this pull request?

The pull requests proposes to remove the hardcoded values for Amazon Kinesis - MIN_RETRY_WAIT_TIME_MS, MAX_RETRIES.

This change is critical for kinesis checkpoint recovery when the kinesis backed rdd is huge.
Following happens in a typical kinesis recovery :
- kinesis throttles large number of requests while recovering
- retries in case of throttling are not able to recover due to the small wait period
- kinesis throttles per second, the wait period should be configurable for recovery

The patch picks the spark kinesis configs from:
- spark.streaming.kinesis.retry.wait.time
- spark.streaming.kinesis.retry.max.attempts

Jira : https://issues.apache.org/jira/browse/SPARK-20140

## How was this patch tested?

Modified the KinesisBackedBlockRDDSuite.scala to run kinesis tests with the modified configurations. Wasn't able to test the patch with actual throttling.

Author: Yash Sharma <ysharma@atlassian.com>

Closes #17467 from yssharma/ysharma/spark-kinesis-retries.

## What changes were proposed in this pull request?

When an expression for `df.filter()` has many nodes (e.g. 400), the size of Java bytecode for the generated Java code is more than 64KB. It produces an Java exception. As a result, the execution fails.
This PR continues to execute by calling `Expression.eval()` disabling code generation if an exception has been caught.

## How was this patch tested?

Add a test suite into `DataFrameSuite`

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

Closes #17087 from kiszk/SPARK-19372.

## What changes were proposed in this pull request?

In the current codes, when worker connects to master, master will send its address to the worker. Then worker will save this address and use it to reconnect in case of failure. However, sometimes, this address is not correct. If there is a proxy between master and worker, the address master sent is not the address of proxy.

In this PR, the master address used by the worker will be sent to the master, then master just replies this address back, worker will use this address to reconnect in case of failure. In other words, the worker will use the config master address set in the worker side if possible rather than the master address set in the master side.

There is still one potential issue though. When a master is restarted or takes over leadership, the work will use the address sent from the master to connect. If there is still a proxy between  master and worker, the address may be wrong. However, there is no way to figure it out just in the worker.

## How was this patch tested?

The new added unit test.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #17821 from zsxwing/SPARK-20529.

Small clean ups from #17742 and #17845.

## How was this patch tested?

Existing unit tests.

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

Closes #17919 from MLnick/SPARK-20677-als-perf-followup.