[SPARK-2207][SPARK-3272][MLLib]Add minimum information gain and minimum instances per node as training parameters for decision tree.

These two parameters can act as early stop rules to do pre-pruning. When a split cause cause left or right child to have less than `minInstancesPerNode` or has less information gain than `minInfoGain`, current node will not be split by this split.

When there is no possible splits that satisfy requirements, there is no useful information gain stats, but we still need to calculate the predict value for current node. So I separated calculation of predict from calculation of information gain, which can also save computation when the number of possible splits is large. Please see [SPARK-3272](https://issues.apache.org/jira/browse/SPARK-3272) for more details.

CC: mengxr manishamde jkbradley, please help me review this, thanks.

Author: qiping.lqp <qiping.lqp@alibaba-inc.com>
Author: chouqin <liqiping1991@gmail.com>

Closes #2332 from chouqin/dt-preprune and squashes the following commits:

f1d11d1 [chouqin] fix typo
c7ebaf1 [chouqin] fix typo
39f9b60 [chouqin] change edge `minInstancesPerNode` to 2 and add one more test
0278a11 [chouqin] remove `noSplit` and set `Predict` private to tree
d593ec7 [chouqin] fix docs and change minInstancesPerNode to 1
efcc736 [qiping.lqp] fix bug
10b8012 [qiping.lqp] fix style
6728fad [qiping.lqp] minor fix: remove empty lines
bb465ca [qiping.lqp] Merge branch 'master' of https://github.com/apache/spark into dt-preprune
cadd569 [qiping.lqp] add api docs
46b891f [qiping.lqp] fix bug
e72c7e4 [qiping.lqp] add comments
845c6fa [qiping.lqp] fix style
f195e83 [qiping.lqp] fix style
987cbf4 [qiping.lqp] fix bug
ff34845 [qiping.lqp] separate calculation of predict of node from calculation of info gain
ac42378 [qiping.lqp] add min info gain and min instances per node parameters in decision tree
[SQL] Add test case with workaround for reading partitioned Avro files

In order to read from partitioned Avro files we need to also set the `SERDEPROPERTIES` since `TBLPROPERTIES` are not passed to the initialization.  This PR simply adds a test to make sure we don't break this workaround.

Author: Michael Armbrust <michael@databricks.com>

Closes #2340 from marmbrus/avroPartitioned and squashes the following commits:

6b969d6 [Michael Armbrust] fix style
fea2124 [Michael Armbrust] Add test case with workaround for reading partitioned avro files.
[SPARK-3447][SQL] Remove explicit conversion with JListWrapper to avoid NPE

Author: Michael Armbrust <michael@databricks.com>

Closes #2323 from marmbrus/kryoJListNPE and squashes the following commits:

9634f11 [Michael Armbrust] Rollback JSON RDD changes
4d4d93c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into kryoJListNPE
646976b [Michael Armbrust] Fix JSON RDD Conversion too
59065bc [Michael Armbrust] Remove explicit conversion to avoid NPE
[SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.

LogicalPlan contains a ‘resolved’ attribute indicating that all of its execution requirements have been resolved. This attribute is not checked before query execution. The analyzer contains a step to check that all Expressions are resolved, but this is not equivalent to checking all LogicalPlans. In particular, the Union plan’s implementation of ‘resolved’ verifies that the types of its children’s columns are compatible. Because the analyzer does not check that a Union plan is resolved, it is possible to execute a Union plan that outputs different types in the same column.  See SPARK-2781 for an example.

This patch adds two checks to the analyzer’s CheckResolution rule. First, each logical plan is checked to see if it is not resolved despite its children being resolved. This allows the ‘problem’ unresolved plan to be included in the TreeNodeException for reporting. Then as a backstop the root plan is checked to see if it is resolved, which recursively checks that the entire plan tree is resolved. Note that the resolved attribute is implemented recursively, and this patch also explicitly checks the resolved attribute on each logical plan in the tree. I assume the query plan trees will not be large enough for this redundant checking to meaningfully impact performance.

Because this patch starts validating that LogicalPlans are resolved before execution, I had to fix some cases where unresolved plans were passing through the analyzer as part of the implementation of the hive query system. In particular, HiveContext applies the CreateTables and PreInsertionCasts, and ExtractPythonUdfs rules manually after the analyzer runs. I moved these rules to the analyzer stage (for hive queries only), in the process completing a code TODO indicating the rules should be moved to the analyzer.

It’s worth noting that moving the CreateTables rule means introducing an analyzer rule with a significant side effect - in this case the side effect is creating a hive table. The rule will only attempt to create a table once even if its batch is executed multiple times, because it converts the InsertIntoCreatedTable plan it matches against into an InsertIntoTable. Additionally, these hive rules must be added to the Resolution batch rather than as a separate batch because hive rules rules may be needed to resolve non-root nodes, leaving the root to be resolved on a subsequent batch iteration. For example, the hive compatibility test auto_smb_mapjoin_14, and others, make use of a query plan where the root is a Union and its children are each a hive InsertIntoTable.

Mixing the custom hive rules with standard analyzer rules initially resulted in an additional failure because of policy differences between spark sql and hive when casting a boolean to a string. Hive casts booleans to strings as “true” / “false” while spark sql casts booleans to strings as “1” / “0” (causing the cast1.q test to fail). This behavior is a result of the BooleanCasts rule in HiveTypeCoercion.scala, and from looking at the implementation of BooleanCasts I think converting to to “1”/“0” is potentially a programming mistake. (If the BooleanCasts rule is disabled, casting produces “true”/“false” instead.) I believe “true” / “false” should be the behavior for spark sql - I changed the behavior so bools are converted to “true”/“false” to be consistent with hive, and none of the existing spark tests failed.

Finally, in some initial testing with hive it appears that an implicit type coercion of boolean to string results in a lowercase string, e.g. CONCAT( TRUE, “” ) -> “true” while an explicit cast produces an all caps string, e.g. CAST( TRUE AS STRING ) -> “TRUE”.  The change I’ve made just converts to lowercase strings in all cases.  I believe it is at least more correct than the existing spark sql implementation where all Cast expressions become “1” / “0”.

Author: Aaron Staple <aaron.staple@gmail.com>

Closes #1706 from staple/SPARK-2781 and squashes the following commits:

32683c4 [Aaron Staple] Fix compilation failure due to merge.
7c77fda [Aaron Staple] Move ExtractPythonUdfs to Analyzer's extendedRules in HiveContext.
d49bfb3 [Aaron Staple] Address review comments.
915b690 [Aaron Staple] Fix merge issue causing compilation failure.
701dcd2 [Aaron Staple] [SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.
[SPARK-2140] Updating heap memory calculation for YARN stable and alpha.

Updated pull request, reflecting YARN stable and alpha states. I am getting intermittent test failures on my own test infrastructure. Is that tracked anywhere yet?

Author: Chris Cope <ccope@resilientscience.com>

Closes #2253 from copester/master and squashes the following commits:

5ad89da [Chris Cope] [SPARK-2140] Removing calculateAMMemory functions since they are no longer needed.
52b4e45 [Chris Cope] [SPARK-2140] Updating heap memory calculation for YARN stable and alpha.
[SPARK-3047] [PySpark] add an option to use str in textFileRDD

str is much efficient than unicode (both CPU and memory), it'e better to use str in textFileRDD. In order to keep compatibility, use unicode by default. (Maybe change it in the future).

use_unicode=True:

daviesliudm:~/work/spark$ time python wc.py
(u'./universe/spark/sql/core/target/java/org/apache/spark/sql/execution/ExplainCommand$.java', 7776)

real	2m8.298s
user	0m0.185s
sys	0m0.064s

use_unicode=False

daviesliudm:~/work/spark$ time python wc.py
('./universe/spark/sql/core/target/java/org/apache/spark/sql/execution/ExplainCommand$.java', 7776)

real	1m26.402s
user	0m0.182s
sys	0m0.062s

We can see that it got 32% improvement!

Author: Davies Liu <davies.liu@gmail.com>

Closes #1951 from davies/unicode and squashes the following commits:

8352d57 [Davies Liu] update version number
a286f2f [Davies Liu] rollback loads()
85246e5 [Davies Liu] add docs for use_unicode
a0295e1 [Davies Liu] add an option to use str in textFile()
[SPARK-2917] [SQL] Avoid table creation in logical plan analyzing for CTAS

Author: Cheng Hao <hao.cheng@intel.com>

Closes #1846 from chenghao-intel/ctas and squashes the following commits:

56a0578 [Cheng Hao] remove the unused imports
9a57abc [Cheng Hao] Avoid table creation in logical plan analyzing
[SPARK-3390][SQL] sqlContext.jsonRDD fails on a complex structure of JSON array and JSON object nesting

This PR aims to correctly handle JSON arrays in the type of `ArrayType(...(ArrayType(StructType)))`.

JIRA: https://issues.apache.org/jira/browse/SPARK-3390.

Author: Yin Huai <huai@cse.ohio-state.edu>

Closes #2364 from yhuai/SPARK-3390 and squashes the following commits:

46db418 [Yin Huai] Handle JSON arrays in the type of ArrayType(...(ArrayType(StructType))).
[Spark-3490] Disable SparkUI for tests

We currently open many ephemeral ports during the tests, and as a result we occasionally can't bind to new ones. This has caused the `DriverSuite` and the `SparkSubmitSuite` to fail intermittently.

By disabling the `SparkUI` when it's not needed, we already cut down on the number of ports opened significantly, on the order of the number of `SparkContexts` ever created. We must keep it enabled for a few tests for the UI itself, however.

Author: Andrew Or <andrewor14@gmail.com>

Closes #2363 from andrewor14/disable-ui-for-tests and squashes the following commits:

332a7d5 [Andrew Or] No need to set spark.ui.port to 0 anymore
30c93a2 [Andrew Or] Simplify streaming UISuite
a431b84 [Andrew Or] Fix streaming test failures
8f5ae53 [Andrew Or] Fix no new line at the end
29c9b5b [Andrew Or] Disable SparkUI for tests
[SPARK-3429] Don't include the empty string "" as a defaultAclUser

Changes logging from

```
14/09/05 02:01:08 INFO SecurityManager: Changing view acls to: aash,
14/09/05 02:01:08 INFO SecurityManager: Changing modify acls to: aash,
14/09/05 02:01:08 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(aash, ); users with modify permissions: Set(aash, )
```
to
```
14/09/05 02:28:28 INFO SecurityManager: Changing view acls to: aash
14/09/05 02:28:28 INFO SecurityManager: Changing modify acls to: aash
14/09/05 02:28:28 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(aash); users with modify permissions: Set(aash)
```

Note that the first set of logs have a Set of size 2 containing "aash" and the empty string ""

cc tgravescs

Author: Andrew Ash <andrew@andrewash.com>

Closes #2286 from ash211/empty-default-acl and squashes the following commits:

18cc612 [Andrew Ash] Use .isEmpty instead of ==""
cf973a1 [Andrew Ash] Don't include the empty string "" as a defaultAclUser
SPARK-3462 push down filters and projections into Unions

Author: Cody Koeninger <cody.koeninger@mediacrossing.com>

Closes #2345 from koeninger/SPARK-3462 and squashes the following commits:

5c8d24d [Cody Koeninger] SPARK-3462 remove now-unused parameter
0788691 [Cody Koeninger] SPARK-3462 add tests, handle compatible schema with different aliases, per marmbrus feedback
ef47b3b [Cody Koeninger] SPARK-3462 push down filters and projections into Unions
SPARK-2482: Resolve sbt warnings during build

At the same time, import the `scala.language.postfixOps` and ` org.scalatest.time.SpanSugar._` cause `scala.language.postfixOps` doesn't work

Author: witgo <witgo@qq.com>

Closes #1330 from witgo/sbt_warnings3 and squashes the following commits:

179ba61 [witgo] Resolve sbt warnings during build
[SPARK-3465] fix task metrics aggregation in local mode

Before overwrite t.taskMetrics, take a deepcopy of it.

Author: Davies Liu <davies.liu@gmail.com>

Closes #2338 from davies/fix_metric and squashes the following commits:

a5cdb63 [Davies Liu] Merge branch 'master' into fix_metric
7c879e0 [Davies Liu] add more comments
754b5b8 [Davies Liu] copy taskMetrics only when isLocal is true
5ca26dc [Davies Liu] fix task metrics aggregation in local mode
[SPARK-3160] [SPARK-3494] [mllib]  DecisionTree: eliminate pre-allocated nodes, parentImpurities arrays. Memory calc bug fix.

This PR includes some code simplifications and re-organization which will be helpful for implementing random forests.  The main changes are that the nodes and parentImpurities arrays are no longer pre-allocated in the main train() method.

Also added 2 bug fixes:
* maxMemoryUsage calculation
* over-allocation of space for bins in DTStatsAggregator for unordered features.

Relation to RFs:
* Since RFs will be deeper and will therefore be more likely sparse (not full trees), it could be a cost savings to avoid pre-allocating a full tree.
* The associated re-organization also reduces bookkeeping, which will make RFs easier to implement.
* The return code doneTraining may be generalized to include cases such as nodes ready for local training.

Details:

No longer pre-allocate parentImpurities array in main train() method.
* parentImpurities values are now stored in individual nodes (in Node.stats.impurity).
* These were not really needed.  They were used in calculateGainForSplit(), but they can be calculated anyways using parentNodeAgg.

No longer using Node.build since tree structure is constructed on-the-fly.
* Did not eliminate since it is public (Developer) API.  Marked as deprecated.

Eliminated pre-allocated nodes array in main train() method.
* Nodes are constructed and added to the tree structure as needed during training.
* Moved tree construction from main train() method into findBestSplitsPerGroup() since there is no need to keep the (split, gain) array for an entire level of nodes.  Only one element of that array is needed at a time, so we do not the array.

findBestSplits() now returns 2 items:
* rootNode (newly created root node on first iteration, same root node on later iterations)
* doneTraining (indicating if all nodes at that level were leafs)

Updated DecisionTreeSuite.  Notes:
* Improved test "Second level node building with vs. without groups"
** generateOrderedLabeledPoints() modified so that it really does require 2 levels of internal nodes.
* Related update: Added Node.deepCopy (private[tree]), used for test suite

CC: mengxr

Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com>

Closes #2341 from jkbradley/dt-spark-3160 and squashes the following commits:

07dd1ee [Joseph K. Bradley] Fixed overflow bug with computing maxMemoryUsage in DecisionTree.  Also fixed bug with over-allocating space in DTStatsAggregator for unordered features.
debe072 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
5c4ac33 [Joseph K. Bradley] Added check in Strategy to make sure minInstancesPerNode >= 1
0dd4d87 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
306120f [Joseph K. Bradley] Fixed typo in DecisionTreeModel.scala doc
eaa1dcf [Joseph K. Bradley] Added topNode doc in DecisionTree and scalastyle fix
d4d7864 [Joseph K. Bradley] Marked Node.build as deprecated
d4dbb99 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into dt-spark-3160
1a8f0ad [Joseph K. Bradley] Eliminated pre-allocated nodes array in main train() method. * Nodes are constructed and added to the tree structure as needed during training.
2ab763b [Joseph K. Bradley] Simplifications to DecisionTree code:
[SPARK-2558][DOCS] Add --queue example to YARN doc

Put original YARN queue spark-submit arg description in
running-on-yarn html table and example command line

Author: Mark G. Whitney <mark@whitneyindustries.com>

Closes #2218 from kramimus/2258-yarndoc and squashes the following commits:

4b5d808 [Mark G. Whitney] remove yarn queue config
f8cda0d [Mark G. Whitney] [SPARK-2558][DOCS] Add spark.yarn.queue description to YARN doc
[PySpark] Add blank line so that Python RDD.top() docstring renders correctly

Author: RJ Nowling <rnowling@gmail.com>

Closes #2370 from rnowling/python_rdd_docstrings and squashes the following commits:

5230574 [RJ Nowling] Add blank line so that Python RDD.top() docstring renders correctly
[SPARK-3481] [SQL] Eliminate the error log in local Hive comparison test

Logically, we should remove the Hive Table/Database first and then reset the Hive configuration, repoint to the new data warehouse directory etc.
Otherwise it raised exceptions like "Database doesn't not exists: default" in the local testing.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #2352 from chenghao-intel/test_hive and squashes the following commits:

74fd76b [Cheng Hao] eliminate the error log
MAINTENANCE: Automated closing of pull requests.

This commit exists to close the following pull requests on Github:

Closes #930 (close requested by 'andrewor14')
Closes #867 (close requested by 'marmbrus')
Closes #1829 (close requested by 'marmbrus')
Closes #1131 (close requested by 'JoshRosen')
Closes #1571 (close requested by 'andrewor14')
Closes #2359 (close requested by 'andrewor14')
[SPARK-3427] [GraphX] Avoid active vertex tracking in static PageRank

GraphX's current implementation of static (fixed iteration count) PageRank uses the Pregel API. This unnecessarily tracks active vertices, even though in static PageRank all vertices are always active. Active vertex tracking incurs the following costs:

1. A shuffle per iteration to ship the active sets to the edge partitions.
2. A hash table creation per iteration at each partition to index the active sets for lookup.
3. A hash lookup per edge to check whether the source vertex is active.

I reimplemented static PageRank using the lower-level GraphX API instead of the Pregel API. In benchmarks on a 16-node m2.4xlarge cluster, this provided a 23% speedup (from 514 s to 397 s, mean over 3 trials) for 10 iterations of PageRank on a synthetic graph with 10M vertices and 1.27B edges.

Author: Ankur Dave <ankurdave@gmail.com>

Closes #2308 from ankurdave/SPARK-3427 and squashes the following commits:

449996a [Ankur Dave] Avoid unnecessary active vertex tracking in static PageRank
SPARK-3014. Log a more informative messages in a couple failure scenario...

...s

Author: Sandy Ryza <sandy@cloudera.com>

Closes #1934 from sryza/sandy-spark-3014 and squashes the following commits:

ae19cc1 [Sandy Ryza] SPARK-3014. Log a more informative messages in a couple failure scenarios