Include the following changes:

1. Close `java.sql.Statement`
2. Fix incorrect `asInstanceOf`.
3. Remove unnecessary `synchronized` and `ReentrantLock`.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10440 from zsxwing/findbugs.

The Scala 2.11 SBT build currently fails for Spark 1.6.0 and master due to warnings about the `transient` annotation:

```
[error] [warn] /Users/joshrosen/Documents/spark/extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDD.scala:73: no valid targets for annotation on value sc - it is discarded unused. You may specify targets with meta-annotations, e.g. (transient param)
[error] [warn]     transient sc: SparkContext,
```

This fix implemented here is the same as what we did in #8433: remove the `transient` annotations when they are not necessary and replace use  `transient private val` in the remaining cases.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #10479 from JoshRosen/fix-sbt-2.11.

[SPARK-12222][CORE] Deserialize RoaringBitmap using Kryo serializer throw Buffer underflow exception

Since we only need to implement `def skipBytes(n: Int)`,
code in #10213 could be simplified.
davies scwf

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #10253 from adrian-wang/kryo.

When explain any plan with Generate, we will see an exclamation mark in the plan. Normally, when we see this mark, it means the plan has an error. This PR is to correct the `missingInput` in `Generate`.

For example,
```scala
val df = Seq((1, "a b c"), (2, "a b"), (3, "a")).toDF("number", "letters")
val df2 =
  df.explode('letters) {
    case Row(letters: String) => letters.split(" ").map(Tuple1(_)).toSeq
  }

df2.explain(true)
```
Before the fix, the plan is like
```
== Parsed Logical Plan ==
'Generate UserDefinedGenerator('letters), true, false, None
+- Project [_1#0 AS number#2,_2#1 AS letters#3]
   +- LocalRelation [_1#0,_2#1], [[1,a b c],[2,a b],[3,a]]

== Analyzed Logical Plan ==
number: int, letters: string, _1: string
Generate UserDefinedGenerator(letters#3), true, false, None, [_1#8]
+- Project [_1#0 AS number#2,_2#1 AS letters#3]
   +- LocalRelation [_1#0,_2#1], [[1,a b c],[2,a b],[3,a]]

== Optimized Logical Plan ==
Generate UserDefinedGenerator(letters#3), true, false, None, [_1#8]
+- LocalRelation [number#2,letters#3], [[1,a b c],[2,a b],[3,a]]

== Physical Plan ==
!Generate UserDefinedGenerator(letters#3), true, false, [number#2,letters#3,_1#8]
+- LocalTableScan [number#2,letters#3], [[1,a b c],[2,a b],[3,a]]
```

**Updates**: The same issues are also found in the other four Dataset operators: `MapPartitions`/`AppendColumns`/`MapGroups`/`CoGroup`. Fixed all these four.

Author: gatorsmile <gatorsmile@gmail.com>
Author: xiaoli <lixiao1983@gmail.com>
Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local>

Closes #10393 from gatorsmile/generateExplain.

Moved (case) classes Strategy, Once, FixedPoint and Batch to the companion object. This is necessary if we want to have the Optimizer easily extendable in the following sense: Usually a user wants to add additional rules, and just take the ones that are already there. However, inner classes made that impossible since the code did not compile

This allows easy extension of existing Optimizers see the DefaultOptimizerExtendableSuite for a corresponding test case.

Author: Stephan Kessler <stephan.kessler@sap.com>

Closes #10174 from stephankessler/SPARK-7727.

ParamMap#filter uses `mutable.Map#filterKeys`. The return type of `filterKey` is collection.Map, not mutable.Map but the result is casted to mutable.Map using `asInstanceOf` so we get `ClassCastException`.
Also, the return type of Map#filterKeys is not Serializable. It's the issue of Scala (https://issues.scala-lang.org/browse/SI-6654).

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #10381 from sarutak/SPARK-12424.

Support Unsafe Row in MapPartitions/MapGroups/CoGroup.

Added a test case for MapPartitions. Since MapGroups and CoGroup are built on AppendColumns, all the related dataset test cases already can verify the correctness when MapGroups and CoGroup processing unsafe rows.

davies cloud-fan Not sure if my understanding is right, please correct me. Thank you!

Author: gatorsmile <gatorsmile@gmail.com>

Closes #10398 from gatorsmile/unsafeRowMapGroup.

The feature was first added at commit: 7b877b27 but was later removed (probably by mistake) at commit: fc8b5819.
This change sets the default path of RDDs created via sc.textFile(...) to the path argument.

Here is the symptom:

* Using spark-1.5.2-bin-hadoop2.6:

scala> sc.textFile("/home/root/.bashrc").name
res5: String = null

scala> sc.binaryFiles("/home/root/.bashrc").name
res6: String = /home/root/.bashrc

* while using Spark 1.3.1:

scala> sc.textFile("/home/root/.bashrc").name
res0: String = /home/root/.bashrc

scala> sc.binaryFiles("/home/root/.bashrc").name
res1: String = /home/root/.bashrc

Author: Yaron Weinsberg <wyaron@gmail.com>
Author: yaron <yaron@il.ibm.com>

Closes #10456 from wyaron/master.

Hello Michael & All:

We have some issues to submit the new codes in the other PR(#10299), so we closed that PR and open this one with the fix.

The reason for the previous failure is that the projection for the scan when there is a filter that is not pushed down (the "left-over" filter) could be different, in elements or ordering, from the original projection.

With this new codes, the approach to solve this problem is:

Insert a new Project if the "left-over" filter is nonempty and (the original projection is not empty and the projection for the scan has more than one elements which could otherwise cause different ordering in projection).

We create 3 test cases to cover the otherwise failure cases.

Author: Kevin Yu <qyu@us.ibm.com>

Closes #10388 from kevinyu98/spark-12231.

https://github.com/apache/spark/pull/10311 introduces some rare, non-deterministic flakiness for hive udf tests, see https://github.com/apache/spark/pull/10311#issuecomment-166548851

I can't reproduce it locally, and may need more time to investigate, a quick solution is: bypass hive tests for json serialization.

Author: Wenchen Fan <wenchen@databricks.com>

Closes #10430 from cloud-fan/hot-fix.

This patch fixes a handful of minor bugs in the `dev/tests/pr_public_classes.sh` script, which is used by the `run_tests_jenkins` script to detect the addition of new public classes:

- Account for differences between BSD and GNU `sed` in order to allow the script to run on OS X.
- Diff `$ghprbActualCommit^...$ghprbActualCommit ` instead of `master...$ghprbActualCommit`: since `ghprbActualCommit` is a merge commit which results from merging the PR into the target branch, this will give us the desired diff and will avoid certain race-conditions which could lead to false-positives.
- Use `echo -e` instead of `echo` so that newline characters are handled correctly in output. This should fix a formatting glitch which caused the output to appear on a single line in the GitHub comment (see [the SC2028 page](https://github.com/koalaman/shellcheck/wiki/SC2028) on the Shellcheck wiki for more details).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #10455 from JoshRosen/fix-pr-public-classes-test.

This PR is a follow-up of PR #10362.

Two major changes:

1.  The fix introduced in #10362 is OK for Parquet, but may disable ORC PPD in many cases

    PR #10362 stops converting an `AND` predicate if any branch is inconvertible.  On the other hand, `OrcFilters` combines all filters into a single big conjunction first and then tries to convert it into ORC `SearchArgument`.  This means, if any filter is inconvertible, no filters can be pushed down.  This PR fixes this issue by finding out all convertible filters first before doing the actual conversion.

    The reason behind the current implementation is mostly due to the limitation of ORC `SearchArgument` builder, which is documented in this PR in detail.

1.  Copied the `AND` predicate fix for ORC from #10362 to avoid merge conflict.

Same as #10362, this PR targets master (2.0.0-SNAPSHOT), branch-1.6, and branch-1.5.

Author: Cheng Lian <lian@databricks.com>

Closes #10377 from liancheng/spark-12218.fix-orc-conjunction-ppd.

The semantics of Python countByValue is different from Scala API, it is more like countDistinctValue, so here change to make it consistent with Scala/Java API.

Author: jerryshao <sshao@hortonworks.com>

Closes #10350 from jerryshao/SPARK-12353.

Author: felixcheung <felixcheung_m@hotmail.com>

Closes #10465 from felixcheung/dfreaderjdbcdoc.

After reading the JIRA https://issues.apache.org/jira/browse/SPARK-12520, I double checked the code.

For example, users can do the Equi-Join like
  ```df.join(df2, 'name', 'outer').select('name', 'height').collect()```
- There exists a bug in 1.5 and 1.4. The code just ignores the third parameter (join type) users pass. However, the join type we called is `Inner`, even if the user-specified type is the other type (e.g., `Outer`).
- After a PR: https://github.com/apache/spark/pull/8600, the 1.6 does not have such an issue, but the description has not been updated.

Plan to submit another PR to fix 1.5 and issue an error message if users specify a non-inner join type when using Equi-Join.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #10477 from gatorsmile/pyOuterJoin.

Instead of just cancel the registrationRetryTimer to avoid driver retry connect to master, change the function to schedule.
It is no need to register to master iteratively.

Author: echo2mei <534384876@qq.com>

Closes #10447 from echoTomei/master.

In SparkContext method `setCheckpointDir`, a warning is issued when spark master is not local and the passed directory for the checkpoint dir appears to be local.

In practice, when relying on HDFS configuration file and using a relative path for the checkpoint directory (using an incomplete URI without HDFS scheme, ...), this warning should not be issued and might be confusing.
In fact, in this case, the checkpoint directory is successfully created, and the checkpointing mechanism works as expected.

This PR uses the `FileSystem` instance created with the given directory, and checks whether it is local or not.
(The rationale is that since this same `FileSystem` instance is used to create the checkpoint dir anyway and can therefore be reliably used to determine if it is local or not).

The warning is only issued if the directory is not local, on top of the existing conditions.

Author: pierre-borckmans <pierre.borckmans@realimpactanalytics.com>

Closes #10392 from pierre-borckmans/SPARK-12440_CheckpointDir_Warning_NonLocal.

In the past Spark JDBC write only worked with technologies which support the following INSERT statement syntax (JdbcUtils.scala: insertStatement()):

INSERT INTO $table VALUES ( ?, ?, ..., ? )

But some technologies require a list of column names:

INSERT INTO $table ( $colNameList ) VALUES ( ?, ?, ..., ? )

This was blocking the use of e.g. the Progress JDBC Driver for Cassandra.

Another limitation is that syntax 1 relies no the dataframe field ordering match that of the target table. This works fine, as long as the target table has been created by writer.jdbc().

If the target table contains more columns (not created by writer.jdbc()), then the insert fails due mismatch of number of columns or their data types.

This PR switches to the recommended second INSERT syntax. Column names are taken from datafram field names.

Author: CK50 <christian.kurz@oracle.com>

Closes #10380 from CK50/master-SPARK-12010-2.

[SPARK-12311][CORE] Restore previous value of "os.arch" property in test suites after forcing to set specific value to "os.arch" property

Restore the original value of os.arch property after each test

Since some of tests forced to set the specific value to os.arch property, we need to set the original value.

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

Closes #10289 from kiszk/SPARK-12311.

fix an exception with IBM JDK by removing update field from a JavaVersion tuple. This is because IBM JDK does not have information on update '_xx'

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

Closes #10463 from kiszk/SPARK-12502.

allow the user to override MAVEN_OPTS (2GB wasn't sufficient for me)

Author: Adrian Bridgett <adrian@smop.co.uk>

Closes #10448 from abridgett/feature/do_not_force_maven_opts.

Fix Tachyon deprecations; pull Tachyon dependency into `TachyonBlockManager` only

CC calvinjia as I probably need a double-check that the usage of the new API is correct.

Author: Sean Owen <sowen@cloudera.com>

Closes #10449 from srowen/SPARK-12500.

Accessing null elements in an array field fails when tungsten is enabled.
It works in Spark 1.3.1, and in Spark > 1.5 with Tungsten disabled.

This PR solves this by checking if the accessed element in the array field is null, in the generated code.

Example:
```
// Array of String
case class AS( as: Seq[String] )
val dfAS = sc.parallelize( Seq( AS ( Seq("a",null,"b") ) ) ).toDF
dfAS.registerTempTable("T_AS")
for (i <- 0 to 2) { println(i + " = " + sqlContext.sql(s"select as[$i] from T_AS").collect.mkString(","))}
```

With Tungsten disabled:
```
0 = [a]
1 = [null]
2 = [b]
```

With Tungsten enabled:
```
0 = [a]
15/12/22 09:32:50 ERROR Executor: Exception in task 7.0 in stage 1.0 (TID 15)
java.lang.NullPointerException
	at org.apache.spark.sql.catalyst.expressions.UnsafeRowWriters$UTF8StringWriter.getSize(UnsafeRowWriters.java:90)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown Source)
	at org.apache.spark.sql.execution.TungstenProject$$anonfun$3$$anonfun$apply$3.apply(basicOperators.scala:90)
	at org.apache.spark.sql.execution.TungstenProject$$anonfun$3$$anonfun$apply$3.apply(basicOperators.scala:88)
	at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
	at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
	at scala.collection.Iterator$class.foreach(Iterator.scala:727)
	at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
```

Author: pierre-borckmans <pierre.borckmans@realimpactanalytics.com>

Closes #10429 from pierre-borckmans/SPARK-12477_Tungsten-Projection-Null-Element-In-Array.

When the filter is ```"b in ('1', '2')"```, the filter is not pushed down to Parquet. Thanks!

Author: gatorsmile <gatorsmile@gmail.com>
Author: xiaoli <lixiao1983@gmail.com>
Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local>

Closes #10278 from gatorsmile/parquetFilterNot.

When creating extractors for product types (i.e. case classes and tuples), a null check is missing, thus we always assume input product values are non-null.

This PR adds a null check in the extractor expression for product types. The null check is stripped off for top level product fields, which are mapped to the outermost `Row`s, since they can't be null.

Thanks cloud-fan for helping investigating this issue!

Author: Cheng Lian <lian@databricks.com>

Closes #10431 from liancheng/spark-12478.top-level-null-field.

This PR adds Scala, Java and Python examples to show how to use Accumulator and Broadcast in Spark Streaming to support checkpointing.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10385 from zsxwing/accumulator-broadcast-example.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10439 from zsxwing/kafka-message-handler-doc.

Compare both left and right side of the case expression ignoring nullablity when checking for type equality.

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

Closes #10156 from dilipbiswal/spark-12102.

Author: Nong Li <nong@databricks.com>

Closes #10422 from nongli/12471-pids.

Author: Jacek Laskowski <jacek@japila.pl>

Closes #10432 from jaceklaskowski/minor-corrections.

First try, not sure how much information we need to provide in the usage part.

Author: Xiu Guo <xguo27@gmail.com>

Closes #10423 from xguo27/SPARK-12456.

We should update to the latest version of Zinc in order to match our SBT version.

Author: Josh Rosen <joshrosen@databricks.com>

Closes #10426 from JoshRosen/update-zinc.

[SPARK-11677][SQL][FOLLOW-UP] Add tests for checking the ORC filter creation against pushed down filters.

https://issues.apache.org/jira/browse/SPARK-11677
Although it checks correctly the filters by the number of results if ORC filter-push-down is enabled, the filters themselves are not being tested.
So, this PR includes the test similarly with `ParquetFilterSuite`.
Since the results are checked by `OrcQuerySuite`, this `OrcFilterSuite` only checks if the appropriate filters are created.

One thing different with `ParquetFilterSuite` here is, it does not check the results because that is checked in `OrcQuerySuite`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #10341 from HyukjinKwon/SPARK-11677-followup.

This PR adds a new expression `AssertNotNull` to ensure non-nullable fields of products and case classes don't receive null values at runtime.

Author: Cheng Lian <lian@databricks.com>

Closes #10331 from liancheng/dataset-nullability-check.

No tests done for JDBCRDD#compileFilter.

Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>

Closes #10409 from maropu/AddTestsInJdbcRdd.

Some methods are missing, such as ways to access the std, mean, etc. This PR is for feature parity for pyspark.mllib.feature.StandardScaler & StandardScalerModel.

Author: Holden Karau <holden@us.ibm.com>

Closes #10298 from holdenk/SPARK-12296-feature-parity-pyspark-mllib-StandardScalerModel.

This patch fixes a flaky "test jdbc cancel" test in HiveThriftBinaryServerSuite. This test is prone to a race-condition which causes it to block indefinitely with while waiting for an extremely slow query to complete, which caused many Jenkins builds to time out.

For more background, see my comments on #6207 (the PR which introduced this test).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #10425 from JoshRosen/SPARK-11823.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10424 from zsxwing/typo.

i.e. Hadoop 1 and Hadoop 2.0

Author: Reynold Xin <rxin@databricks.com>

Closes #10404 from rxin/SPARK-11807.

According the benchmark [1], LZ4-java could be 80% (or 30%) faster than Snappy.

After changing the compressor to LZ4, I saw 20% improvement on end-to-end time for a TPCDS query (Q4).

[1] https://github.com/ning/jvm-compressor-benchmark/wiki

cc rxin

Author: Davies Liu <davies@databricks.com>

Closes #10342 from davies/lz4.