[SPARK-20764][ML][PYSPARK][FOLLOWUP] Fix visibility discrepancy with numInstances and degreesOfFreedom in LR and GLR - Python version

## What changes were proposed in this pull request?
Add test cases for PR-18062

## How was this patch tested?
The existing UT

Author: Peng <peng.meng@intel.com>

Closes #18068 from mpjlu/moreTest.

## What changes were proposed in this pull request?

When a TaskContext is not propagated properly to all child threads for the task, just like the reported cases in this issue, we fail to get to TID from TaskContext and that causes unable to release the lock and assertion failures. To resolve this, we have to explicitly pass the TID value to the `unlock` method.

## How was this patch tested?

Add new failing regression test case in `RDDSuite`.

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

Closes #18076 from jiangxb1987/completion-iterator.

Changes:

pyspark.ml Estimators can take either a list of param maps or a dict of params. This change allows the CrossValidator and TrainValidationSplit Estimators to pass through lists of param maps to the underlying estimators so that those estimators can handle parallelization when appropriate (eg distributed hyper parameter tuning).

Testing:

Existing unit tests.

Author: Bago Amirbekian <bago@databricks.com>

Closes #18077 from MrBago/delegate_params.

The contribution is my original work and I license the work to the project under the project’s open source license.

Note: the Teradata JDBC connector limits the row size to 64K. The default string datatype equivalent I used is a 255 character/byte length varchar. This effectively limits the max number of string columns to 250 when using the Teradata jdbc connector.

## What changes were proposed in this pull request?

Added a teradataDialect for JDBC connection to Teradata. The Teradata dialect uses VARCHAR(255) in place of TEXT for string datatypes, and CHAR(1) in place of BIT(1) for boolean datatypes.

## How was this patch tested?

I added two unit tests to double check that the types get set correctly for a teradata jdbc url. I also ran a couple manual tests to make sure the jdbc connector worked with teradata and to make sure that an error was thrown if a row could potentially exceed 64K (this error comes from the teradata jdbc connector, not from the spark code). I did not check how string columns longer than 255 characters are handled.

Author: Kirby Linvill <kirby.linvill@teradata.com>
Author: klinvill <kjlinvill@gmail.com>

Closes #16746 from klinvill/master.

## What changes were proposed in this pull request?
This patch renames BroadcastHint to ResolvedHint (and Hint to UnresolvedHint) so the hint framework is more generic and would allow us to introduce other hint types in the future without introducing new hint nodes.

## How was this patch tested?
Updated test cases.

Author: Reynold Xin <rxin@databricks.com>

Closes #18072 from rxin/SPARK-20857.

## What changes were proposed in this pull request?
Joint coefficients with intercept for SparkR linear SVM summary.

## How was this patch tested?
Existing tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #18035 from yanboliang/svm-r.

[SPARK-20399][SQL][FOLLOW-UP] Add a config to fallback string literal parsing consistent with old sql parser behavior

## What changes were proposed in this pull request?

As srowen pointed in https://github.com/apache/spark/commit/609ba5f2b9fd89b1b9971d08f7cc680d202dbc7c#commitcomment-22221259, the previous tests are not proper.

This follow-up is going to fix the tests.

## 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 #18048 from viirya/SPARK-20399-follow-up.

## What changes were proposed in this pull request?

This change skips tests that use the Hadoop libraries while running
on CRAN check with Windows as the operating system. This is to handle
cases where the Hadoop winutils binaries are missing on the target
system. The skipped tests consist of
1. Tests that save, load a model in MLlib
2. Tests that save, load CSV, JSON and Parquet files in SQL
3. Hive tests

## How was this patch tested?

Tested by running on a local windows VM with HADOOP_HOME unset. Also testing with https://win-builder.r-project.org

Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>

Closes #17966 from shivaram/sparkr-windows-cran.

## What changes were proposed in this pull request?

- Add a null check to RPackageUtils#checkManifestForR so that jars w/o manifests don't NPE.

## How was this patch tested?

- Unit tests and manual tests.

Author: James Shuster <jshuster@palantir.com>

Closes #18040 from jrshust/feature/r-package-utils.

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

After we adding a new field `stats` into `CatalogTable`, we should not expose Hive-specific Stats metadata to `MetastoreRelation`. It complicates all the related codes. It also introduces a bug in `SHOW CREATE TABLE`. The statistics-related table properties should be skipped by `SHOW CREATE TABLE`, since it could be incorrect in the newly created table. See the Hive JIRA: https://issues.apache.org/jira/browse/HIVE-13792

Also fix the issue to fill Hive-generated RowCounts to our stats.

This PR is to handle Hive-specific Stats metadata in `HiveClientImpl`.
### How was this patch tested?

Added a few test cases.

Author: Xiao Li <gatorsmile@gmail.com>

Closes #14971 from gatorsmile/showCreateTableNew.

## What changes were proposed in this pull request?

Add cot test in MathExpressionsSuite as https://github.com/apache/spark/pull/17999#issuecomment-302832794.

## How was this patch tested?

unit tests

Author: Yuming Wang <wgyumg@gmail.com>

Closes #18039 from wangyum/SPARK-20751-test.

Restore code that was removed as part of SPARK-17979, but instead of
using the deprecated env variable name to propagate the class path, use
a new one.

Verified by running "./bin/spark-class o.a.s.executor.CoarseGrainedExecutorBackend"
manually.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #18037 from vanzin/SPARK-20814.

## What changes were proposed in this pull request?
support decision tree in R

## How was this patch tested?
added tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #17981 from zhengruifeng/dt_r.

and contains scala classes

## What changes were proposed in this pull request?
This change ensures that all references to guava from within the yarn shuffle jar pointed to the shaded guava class already provided in the jar.

Also, it explicitly excludes scala classes from being added to the jar.

## How was this patch tested?
Ran unit tests on the module and they passed.
javap now returns the expected result - reference to the shaded guava under `org/spark_project` (previously this was referring to `com.google...`
```
javap -cp common/network-yarn/target/scala-2.11/spark-2.3.0-SNAPSHOT-yarn-shuffle.jar -c org/apache/spark/network/yarn/YarnShuffleService | grep Lists
      57: invokestatic  #138                // Method org/spark_project/guava/collect/Lists.newArrayList:()Ljava/util/ArrayList;
```

Guava is still shaded in the jar:
```
jar -tf common/network-yarn/target/scala-2.11/spark-2.3.0-SNAPSHOT-yarn-shuffle.jar | grep guava | head
META-INF/maven/com.google.guava/
META-INF/maven/com.google.guava/guava/
META-INF/maven/com.google.guava/guava/pom.properties
META-INF/maven/com.google.guava/guava/pom.xml
org/spark_project/guava/
org/spark_project/guava/annotations/
org/spark_project/guava/annotations/Beta.class
org/spark_project/guava/annotations/GwtCompatible.class
org/spark_project/guava/annotations/GwtIncompatible.class
org/spark_project/guava/annotations/VisibleForTesting.class
```
(not sure if the above META-INF/* is a problem or not)

I took this jar, deployed it on a yarn cluster with shuffle service enabled, and made sure the YARN node managers came up. An application with a shuffle was run and it succeeded.

Author: Mark Grover <mark@apache.org>

Closes #17990 from markgrover/spark-20756.

[SPARK-20764][ML][PYSPARK] Fix visibility discrepancy with numInstances and degreesOfFreedom in LR and GLR - Python version

## What changes were proposed in this pull request?

SPARK-20097 exposed degreesOfFreedom in LinearRegressionSummary and numInstances in GeneralizedLinearRegressionSummary. Python API should be updated to reflect these changes.

## How was this patch tested?
The existing UT

Author: Peng <peng.meng@intel.com>

Closes #18062 from mpjlu/spark-20764.

### 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.