After the following patches, the main (Scala) API is now usable for Java users directly.

https://github.com/apache/spark/pull/4056
https://github.com/apache/spark/pull/4054
https://github.com/apache/spark/pull/4049
https://github.com/apache/spark/pull/4030
https://github.com/apache/spark/pull/3965
https://github.com/apache/spark/pull/3958

Author: Reynold Xin <rxin@databricks.com>

Closes #4065 from rxin/sql-java-api and squashes the following commits:

b1fd860 [Reynold Xin] Fix Mima
6d86578 [Reynold Xin] Ok one more attempt in fixing Python...
e8f1455 [Reynold Xin] Fix Python again...
3e53f91 [Reynold Xin] Fixed Python.
83735da [Reynold Xin] Fix BigDecimal test.
e9f1de3 [Reynold Xin] Use scala BigDecimal.
500d2c4 [Reynold Xin] Fix Decimal.
ba3bfa2 [Reynold Xin] Updated javadoc for RowFactory.
c4ae1c5 [Reynold Xin] [SPARK-5193][SQL] Remove Spark SQL Java-specific API.

As part of SPARK-5193:

1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf").
2. For Java UDFs, renamed dataType to returnType.
3. For Scala UDFs, added type tags.
4. Added all Java UDF registration methods to Scala's UDFRegistration.
5. Documentation

Author: Reynold Xin <rxin@databricks.com>

Closes #4056 from rxin/udf-registration and squashes the following commits:

ae9c556 [Reynold Xin] Updated example.
675a3c9 [Reynold Xin] Style fix
47c24ff [Reynold Xin] Python fix.
5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags.
032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.

When attempting to infer the schema of an RDD that contains namedtuples, pyspark fails to identify the records as namedtuples, resulting in it raising an error.

Example:

```python
from pyspark import SparkContext
from pyspark.sql import SQLContext
from collections import namedtuple
import os

sc = SparkContext()
rdd = sc.textFile(os.path.join(os.getenv('SPARK_HOME'), 'README.md'))
TextLine = namedtuple('TextLine', 'line length')
tuple_rdd = rdd.map(lambda l: TextLine(line=l, length=len(l)))
tuple_rdd.take(5)  # This works

sqlc = SQLContext(sc)

# The following line raises an error
schema_rdd = sqlc.inferSchema(tuple_rdd)
```

The error raised is:
```
  File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 107, in main
    process()
  File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 98, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/serializers.py", line 227, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/rdd.py", line 1107, in takeUpToNumLeft
    yield next(iterator)
  File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/sql.py", line 816, in convert_struct
    raise ValueError("unexpected tuple: %s" % obj)
TypeError: not all arguments converted during string formatting
```

Author: Gabe Mulley <gabe@edx.org>

Closes #3978 from mulby/inferschema-namedtuple and squashes the following commits:

98c61cc [Gabe Mulley] Ensure exception message is populated correctly
375d96b [Gabe Mulley] Ensure schema can be inferred from a namedtuple

Creates a top level directory script (as `build/mvn`) to automatically download zinc and the specific version of scala used to easily build spark. This will also download and install maven if the user doesn't already have it and all packages are hosted under the `build/` directory. Tested on both Linux and OSX OS's and both work. All commands pass through to the maven binary so it acts exactly as a traditional maven call would.

Author: Brennon York <brennon.york@capitalone.com>

Closes #3707 from brennonyork/SPARK-4501 and squashes the following commits:

0e5a0e4 [Brennon York] minor incorrect doc verbage (with -> this)
9b79e38 [Brennon York] fixed merge conflicts with dev/run-tests, properly quoted args in sbt/sbt, fixed bug where relative paths would fail if passed in from build/mvn
d2d41b6 [Brennon York] added blurb about leverging zinc with build/mvn
b979c58 [Brennon York] updated the merge conflict
c5634de [Brennon York] updated documentation to overview build/mvn, updated all points where sbt/sbt was referenced with build/sbt
b8437ba [Brennon York] set progress bars for curl and wget when not run on jenkins, no progress bar when run on jenkins, moved sbt script to build/sbt, wrote stub and warning under sbt/sbt which calls build/sbt, modified build/sbt to use the correct directory, fixed bug in build/sbt-launch-lib.bash to correctly pull the sbt version
be11317 [Brennon York] added switch to silence download progress only if AMPLAB_JENKINS is set
28d0a99 [Brennon York] updated to remove the python dependency, uses grep instead
7e785a6 [Brennon York] added silent and quiet flags to curl and wget respectively, added single echo output to denote start of a download if download is needed
14a5da0 [Brennon York] removed unnecessary zinc output on startup
1af4a94 [Brennon York] fixed bug with uppercase vs lowercase variable
3e8b9b3 [Brennon York] updated to properly only restart zinc if it was freshly installed
a680d12 [Brennon York] Added comments to functions and tested various mvn calls
bb8cc9d [Brennon York] removed package files
ef017e6 [Brennon York] removed OS complexities, setup generic install_app call, removed extra file complexities, removed help, removed forced install (defaults now), removed double-dash from cli
07bf018 [Brennon York] Updated to specifically handle pulling down the correct scala version
f914dea [Brennon York] Beginning final portions of localized scala home
69c4e44 [Brennon York] working linux and osx installers for purely local mvn build
4a1609c [Brennon York] finalizing working linux install for maven to local ./build/apache-maven folder
cbfcc68 [Brennon York] Changed the default sbt/sbt to build/sbt and added a build/mvn which will automatically download, install, and execute maven with zinc for easier build capability

This PR modifies the python `SchemaRDD` to use `sample()` and `takeSample()` from Scala instead of the slower python implementations from `rdd.py`. This is worthwhile because the `Row`'s are already serialized as Java objects.

In order to use the faster `takeSample()`, a `takeSampleToPython()` method was implemented in `SchemaRDD.scala` following the pattern of `collectToPython()`.

Author: jbencook <jbenjamincook@gmail.com>
Author: J. Benjamin Cook <jbenjamincook@gmail.com>

Closes #3764 from jbencook/master and squashes the following commits:

6fbc769 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing sloppy indentation for takeSampleToPython() arguments
5170da2 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing typo: from RDD to SchemaRDD
de22f70 [jbencook] [SPARK-4860][pyspark][sql] using sample() method from JavaSchemaRDD
b916442 [jbencook] [SPARK-4860][pyspark][sql] adding sample() to JavaSchemaRDD
020cbdf [jbencook] [SPARK-4860][pyspark][sql] using Scala implementations of `sample()` and `takeSample()`

Modify python annotations for sphinx. There is no change to build process from.
https://github.com/apache/spark/blob/master/docs/README.md

Author: lewuathe <lewuathe@me.com>

Closes #3685 from Lewuathe/sphinx-tag-for-pydoc and squashes the following commits:

88a0fd9 [lewuathe] [SPARK-4822] Fix DevelopApi and WARN tags
3d7a398 [lewuathe] [SPARK-4822] Use sphinx tags for Python doc annotations

This PR brings support of using StructType(and other hashable types) as key in MapType.

Author: Davies Liu <davies@databricks.com>

Closes #3714 from davies/fix_struct_in_map and squashes the following commits:

68585d7 [Davies Liu] fix primitive types in MapType
9601534 [Davies Liu] support StructType as key in MapType

The Row object is created on the fly once the field is accessed, so we should access them by getattr() in asDict(0

Author: Davies Liu <davies@databricks.com>

Closes #3434 from davies/fix_asDict and squashes the following commits:

b20f1e7 [Davies Liu] fix asDict() with nested Row()

Here's a simple fix for SchemaRDD to JSON.

Author: Dan McClary <dan.mcclary@gmail.com>

Closes #3213 from dwmclary/SPARK-4228 and squashes the following commits:

d714e1d [Dan McClary] fixed PEP 8 error
cac2879 [Dan McClary] move pyspark comment and doctest to correct location
f9471d3 [Dan McClary] added pyspark doc and doctest
6598cee [Dan McClary] adding complex type queries
1a5fd30 [Dan McClary] removing SPARK-4228 from SQLQuerySuite
4a651f0 [Dan McClary] cleaned PEP and Scala style failures.  Moved tests to JsonSuite
47ceff6 [Dan McClary] cleaned up scala style issues
2ee1e70 [Dan McClary] moved rowToJSON to JsonRDD
4387dd5 [Dan McClary] Added UserDefinedType, cleaned up case formatting
8f7bfb6 [Dan McClary] Map type added to SchemaRDD.toJSON
1b11980 [Dan McClary] Map and UserDefinedTypes partially done
11d2016 [Dan McClary] formatting and unicode deserialization default fixed
6af72d1 [Dan McClary] deleted extaneous comment
4d11c0c [Dan McClary] JsonFactory rewrite of toJSON for SchemaRDD
149dafd [Dan McClary] wrapped scala toJSON in sql.py
5e5eb1b [Dan McClary] switched to Jackson for JSON processing
6c94a54 [Dan McClary] added toJSON to pyspark SchemaRDD
aaeba58 [Dan McClary] added toJSON to pyspark SchemaRDD
1d171aa [Dan McClary] upated missing brace on if statement
319e3ba [Dan McClary] updated to upstream master with merged SPARK-4228
424f130 [Dan McClary] tests pass, ready for pull and PR
626a5b1 [Dan McClary] added toJSON to SchemaRDD
f7d166a [Dan McClary] added toJSON method
5d34e37 [Dan McClary] merge resolved
d6d19e9 [Dan McClary] pr example

This PR simplify serializer, always use batched serializer (AutoBatchedSerializer as default), even batch size is 1.

Author: Davies Liu <davies@databricks.com>

This patch had conflicts when merged, resolved by
Committer: Josh Rosen <joshrosen@databricks.com>

Closes #2920 from davies/fix_autobatch and squashes the following commits:

e544ef9 [Davies Liu] revert unrelated change
6880b14 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
1d557fc [Davies Liu] fix tests
8180907 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
76abdce [Davies Liu] clean up
53fa60b [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
d7ac751 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
2cc2497 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch
b4292ce [Davies Liu] fix bug in master
d79744c [Davies Liu] recover hive tests
be37ece [Davies Liu] refactor
eb3938d [Davies Liu] refactor serializer in scala
8d77ef2 [Davies Liu] simplify serializer, use AutoBatchedSerializer by default.

Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python.

marmbrus jkbradley davies

Author: Xiangrui Meng <meng@databricks.com>

Closes #3068 from mengxr/SPARK-4192-sql and squashes the following commits:

acff637 [Xiangrui Meng] merge master
dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well
2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion
7c4a6a9 [Xiangrui Meng] address comments
75223db [Xiangrui Meng] minor update
f740379 [Xiangrui Meng] remove UDT from default imports
e98d9d0 [Xiangrui Meng] fix py style
4e84fce [Xiangrui Meng] remove local hive tests and add more tests
39f19e0 [Xiangrui Meng] add tests
b7f666d [Xiangrui Meng] add Python UDT

This patch will try to infer schema for RDD which has empty value (None, [], {}) in the first row. It will try first 100 rows and merge the types into schema, also merge fields of StructType together. If there is still NullType in schema, then it will show an warning, tell user to try with sampling.

If sampling is presented, it will infer schema from all the rows after sampling.

Also, add samplingRatio for jsonFile() and jsonRDD()

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

Closes #2716 from davies/infer and squashes the following commits:

e678f6d [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
34b5c63 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
567dc60 [Davies Liu] update docs
9767b27 [Davies Liu] Merge branch 'master' into infer
e48d7fb [Davies Liu] fix tests
29e94d5 [Davies Liu] let NullType inherit from PrimitiveType
ee5d524 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
540d1d5 [Davies Liu] merge fields for StructType
f93fd84 [Davies Liu] add more tests
3603e00 [Davies Liu] take more rows to infer schema, or infer the schema by sampling the RDD

- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf)
- Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs

This is still marked WIP because there are a few TODOs, but I'll remove that tag when done.

Author: Matei Zaharia <matei@databricks.com>

Closes #2983 from mateiz/decimal-1 and squashes the following commits:

35e6b02 [Matei Zaharia] Fix issues after merge
227f24a [Matei Zaharia] Review comments
31f915e [Matei Zaharia] Implement Davies's suggestions in Python
eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet
4dc6bae [Matei Zaharia] Fix decimal support in PySpark
d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase
b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore
2118c0d [Matei Zaharia] Some test and bug fixes
81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions
7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now
ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double

Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON.

Metadata is preserved through simple operations like `SELECT`.

marmbrus liancheng

Author: Xiangrui Meng <meng@databricks.com>
Author: Michael Armbrust <michael@databricks.com>

Closes #2701 from mengxr/structfield-metadata and squashes the following commits:

dedda56 [Xiangrui Meng] merge remote
5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701
886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages.
589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
1e2abcf [Xiangrui Meng] change default value of metadata to None in python
611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr
ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility
3f49aab [Xiangrui Meng] remove StructField.toString
24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
473a7c5 [Xiangrui Meng] merge master
c9d7301 [Xiangrui Meng] organize imports
1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java
60cc131 [Xiangrui Meng] add doc and header
60614c7 [Xiangrui Meng] add metadata
e42c452 [Xiangrui Meng] merge master
93518fb [Xiangrui Meng] support metadata in python
905bb89 [Xiangrui Meng] java conversions
618e349 [Xiangrui Meng] make tests work in scala
61b8e0f [Xiangrui Meng] merge master
7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString
c41a664 [Xiangrui Meng] merge master
d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite
67fdebb [Xiangrui Meng] add test on join
d65072e [Xiangrui Meng] remove Map.empty
367d237 [Xiangrui Meng] add test
c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute

 In #2241 hive-thriftserver is not enabled. This patch enable hive-thriftserver to support hive-0.13.1 by using a shim layer refer to #2241.

 1 A light shim layer(code in sql/hive-thriftserver/hive-version) for each different hive version to handle api compatibility

 2 New pom profiles "hive-default" and "hive-versions"(copy from #2241) to activate different hive version

 3 SBT cmd for different version as follows:
   hive-0.12.0 --- sbt/sbt -Phive,hadoop-2.3 -Phive-0.12.0 assembly
   hive-0.13.1 --- sbt/sbt -Phive,hadoop-2.3 -Phive-0.13.1 assembly

 4 Since hive-thriftserver depend on hive subproject, this patch should be merged with #2241 to enable hive-0.13.1 for hive-thriftserver

Author: wangfei <wangfei1@huawei.com>
Author: scwf <wangfei1@huawei.com>

Closes #2685 from scwf/shim-thriftserver1 and squashes the following commits:

f26f3be [wangfei] remove clean to save time
f5cac74 [wangfei] remove local hivecontext test
578234d [wangfei] use new shaded hive
18fb1ff [wangfei] exclude kryo in hive pom
fa21d09 [wangfei] clean package assembly/assembly
8a4daf2 [wangfei] minor fix
0d7f6cf [wangfei] address comments
f7c93ae [wangfei] adding build with hive 0.13 before running tests
bcf943f [wangfei] Merge branch 'master' of https://github.com/apache/spark into shim-thriftserver1
c359822 [wangfei] reuse getCommandProcessor in hiveshim
52674a4 [scwf] sql/hive included since examples depend on it
3529e98 [scwf] move hive module to hive profile
f51ff4e [wangfei] update and fix conflicts
f48d3a5 [scwf] Merge branch 'master' of https://github.com/apache/spark into shim-thriftserver1
41f727b [scwf] revert pom changes
13afde0 [scwf] fix small bug
4b681f4 [scwf] enable thriftserver in profile hive-0.13.1
0bc53aa [scwf] fixed when result filed is null
dfd1c63 [scwf] update run-tests to run hive-0.12.0 default now
c6da3ce [scwf] Merge branch 'master' of https://github.com/apache/spark into shim-thriftserver
7c66b8e [scwf] update pom according spark-2706
ae47489 [scwf] update and fix conflicts

Add json and python api for date type.
By using Pickle, `java.sql.Date` was serialized as calendar, and recognized in python as `datetime.datetime`.

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

Closes #2901 from adrian-wang/spark3988 and squashes the following commits:

c51a24d [Daoyuan Wang] convert datetime to date
5670626 [Daoyuan Wang] minor line combine
f760d8e [Daoyuan Wang] fix indent
444f100 [Daoyuan Wang] fix a typo
1d74448 [Daoyuan Wang] fix scala style
8d7dd22 [Daoyuan Wang] add json and python api for date type

Added a method to Row to turn row into dict:

```
>>> row = Row(a=1)
>>> row.asDict()
{'a': 1}
```

Author: Davies Liu <davies@databricks.com>

Closes #2896 from davies/dict and squashes the following commits:

8d97366 [Davies Liu] convert Row into dict

Sphinx documents contains a corrupted ReST format and have some warnings.

The purpose of this issue is same as https://issues.apache.org/jira/browse/SPARK-3773.

commit: 0e8203f4

output
```
$ cd ./python/docs
$ make clean html
rm -rf _build/*
sphinx-build -b html -d _build/doctrees   . _build/html
Making output directory...
Running Sphinx v1.2.3
loading pickled environment... not yet created
building [html]: targets for 4 source files that are out of date
updating environment: 4 added, 0 changed, 0 removed
reading sources... [100%] pyspark.sql
/Users/<user>/MyRepos/Scala/spark/python/pyspark/mllib/feature.py:docstring of pyspark.mllib.feature.Word2VecModel.findSynonyms:4: WARNING: Field list ends without a blank line; unexpected unindent.
/Users/<user>/MyRepos/Scala/spark/python/pyspark/mllib/feature.py:docstring of pyspark.mllib.feature.Word2VecModel.transform:3: WARNING: Field list ends without a blank line; unexpected unindent.
/Users/<user>/MyRepos/Scala/spark/python/pyspark/sql.py:docstring of pyspark.sql:4: WARNING: Bullet list ends without a blank line; unexpected unindent.
looking for now-outdated files... none found
pickling environment... done
checking consistency... done
preparing documents... done
writing output... [100%] pyspark.sql
writing additional files... (12 module code pages) _modules/index search
copying static files... WARNING: html_static_path entry u'/Users/<user>/MyRepos/Scala/spark/python/docs/_static' does not exist
done
copying extra files... done
dumping search index... done
dumping object inventory... done
build succeeded, 4 warnings.

Build finished. The HTML pages are in _build/html.
```

Author: cocoatomo <cocoatomo77@gmail.com>

Closes #2766 from cocoatomo/issues/3909-sphinx-build-warnings and squashes the following commits:

2c7faa8 [cocoatomo] [SPARK-3909][PySpark][Doc] A corrupted format in Sphinx documents and building warnings

This PR uses JSON instead of `toString` to serialize `DataType`s. The latter is not only hard to parse but also flaky in many cases.

Since we already write schema information to Parquet metadata in the old style, we have to reserve the old `DataType` parser and ensure downward compatibility. The old parser is now renamed to `CaseClassStringParser` and moved into `object DataType`.

JoshRosen davies Please help review PySpark related changes, thanks!

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #2563 from liancheng/datatype-to-json and squashes the following commits:

fc92eb3 [Cheng Lian] Reverts debugging code, simplifies primitive type JSON representation
438c75f [Cheng Lian] Refactors PySpark DataType JSON SerDe per comments
6b6387b [Cheng Lian] Removes debugging code
6a3ee3a [Cheng Lian] Addresses per review comments
dc158b5 [Cheng Lian] Addresses PEP8 issues
99ab4ee [Cheng Lian] Adds compatibility est case for Parquet type conversion
a983a6c [Cheng Lian] Adds PySpark support
f608c6e [Cheng Lian] De/serializes DataType objects from/to JSON

Retire Epydoc, use Sphinx to generate API docs.

Refine Sphinx docs, also convert some docstrings into Sphinx style.

It looks like:
![api doc](https://cloud.githubusercontent.com/assets/40902/4538272/9e2d4f10-4dec-11e4-8d96-6e45a8fe51f9.png)

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

Closes #2689 from davies/docs and squashes the following commits:

bf4a0a5 [Davies Liu] fix links
3fb1572 [Davies Liu] fix _static in jekyll
65a287e [Davies Liu] fix scripts and logo
8524042 [Davies Liu] Merge branch 'master' of github.com:apache/spark into docs
d5b874a [Davies Liu] Merge branch 'master' of github.com:apache/spark into docs
4bc1c3c [Davies Liu] refactor
746d0b6 [Davies Liu] @param -> :param
240b393 [Davies Liu] replace epydoc with sphinx doc

Add a toString method to GeneralizedLinearModel, also change `__str__` to `__repr__` for some classes, to provide better message in repr.

This PR is based on #1388, thanks to sryza!

closes #1388

Author: Sandy Ryza <sandy@cloudera.com>
Author: Davies Liu <davies.liu@gmail.com>

Closes #2625 from davies/string and squashes the following commits:

3544aad [Davies Liu] fix LinearModel
0bcd642 [Davies Liu] Merge branch 'sandy-spark-2461' of github.com:sryza/spark
1ce5c2d [Sandy Ryza] __repr__ back to __str__ in a couple places
aa9e962 [Sandy Ryza] Switch __str__ to __repr__
a0c5041 [Sandy Ryza] Add labels back in
1aa17f5 [Sandy Ryza] Match existing conventions
fac1bc4 [Sandy Ryza] Fix PEP8 error
f7b58ed [Sandy Ryza] SPARK-2461. Add a toString method to GeneralizedLinearModel

1. broadcast is triggle unexpected
2. fd is leaked in JVM (also leak in parallelize())
3. broadcast is not unpersisted in JVM after RDD is not be used any more.

cc JoshRosen , sorry for these stupid bugs.

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

Closes #2603 from davies/fix_broadcast and squashes the following commits:

080a743 [Davies Liu] fix bugs in broadcast large closure of RDD

This patch add profiling support for PySpark, it will show the profiling results
before the driver exits, here is one example:

```
============================================================
Profile of RDD<id=3>
============================================================
         5146507 function calls (5146487 primitive calls) in 71.094 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
  5144576   68.331    0.000   68.331    0.000 statcounter.py:44(merge)
       20    2.735    0.137   71.071    3.554 statcounter.py:33(__init__)
       20    0.017    0.001    0.017    0.001 {cPickle.dumps}
     1024    0.003    0.000    0.003    0.000 t.py:16(<lambda>)
       20    0.001    0.000    0.001    0.000 {reduce}
       21    0.001    0.000    0.001    0.000 {cPickle.loads}
       20    0.001    0.000    0.001    0.000 copy_reg.py:95(_slotnames)
       41    0.001    0.000    0.001    0.000 serializers.py:461(read_int)
       40    0.001    0.000    0.002    0.000 serializers.py:179(_batched)
       62    0.000    0.000    0.000    0.000 {method 'read' of 'file' objects}
       20    0.000    0.000   71.072    3.554 rdd.py:863(<lambda>)
       20    0.000    0.000    0.001    0.000 serializers.py:198(load_stream)
    40/20    0.000    0.000   71.072    3.554 rdd.py:2093(pipeline_func)
       41    0.000    0.000    0.002    0.000 serializers.py:130(load_stream)
       40    0.000    0.000   71.072    1.777 rdd.py:304(func)
       20    0.000    0.000   71.094    3.555 worker.py:82(process)
```

Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk
by `sc.dump_profiles(path)`, such as

```python
>>> sc._conf.set("spark.python.profile", "true")
>>> rdd = sc.parallelize(range(100)).map(str)
>>> rdd.count()
100
>>> sc.show_profiles()
============================================================
Profile of RDD<id=1>
============================================================
         284 function calls (276 primitive calls) in 0.001 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4    0.000    0.000    0.000    0.000 serializers.py:198(load_stream)
        4    0.000    0.000    0.000    0.000 {reduce}
     12/4    0.000    0.000    0.001    0.000 rdd.py:2092(pipeline_func)
        4    0.000    0.000    0.000    0.000 {cPickle.loads}
        4    0.000    0.000    0.000    0.000 {cPickle.dumps}
      104    0.000    0.000    0.000    0.000 rdd.py:852(<genexpr>)
        8    0.000    0.000    0.000    0.000 serializers.py:461(read_int)
       12    0.000    0.000    0.000    0.000 rdd.py:303(func)
```
The profiling is disabled by default, can be enabled by "spark.python.profile=true".

Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump"

This is bugfix of #2351 cc JoshRosen

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

Closes #2556 from davies/profiler and squashes the following commits:

e68df5a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
858e74c [Davies Liu] compatitable with python 2.6
7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles()
2b0daf2 [Davies Liu] fix docs
7a56c24 [Davies Liu] bugfix
cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext
fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
09d02c3 [Davies Liu] Merge branch 'master' into profiler
c23865c [Davies Liu] Merge branch 'master' into profiler
15d6f18 [Davies Liu] add docs for two configs
dadee1a [Davies Liu] add docs string and clear profiles after show or dump
4f8309d [Davies Liu] address comment, add tests
0a5b6eb [Davies Liu] fix Python UDF
4b20494 [Davies Liu] add profile for python

Currently, the schema of object in ArrayType or MapType is attached lazily, it will have better performance but introduce issues while serialization or accessing nested objects.

This patch will apply schema to the objects of ArrayType or MapType immediately when accessing them, will be a little bit slower, but much robust.

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

Closes #2526 from davies/nested and squashes the following commits:

2399ae5 [Davies Liu] fix serialization of List and Map in SchemaRDD

This reverts commit 1aa549ba.

This patch add profiling support for PySpark, it will show the profiling results
before the driver exits, here is one example:

```
============================================================
Profile of RDD<id=3>
============================================================
         5146507 function calls (5146487 primitive calls) in 71.094 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
  5144576   68.331    0.000   68.331    0.000 statcounter.py:44(merge)
       20    2.735    0.137   71.071    3.554 statcounter.py:33(__init__)
       20    0.017    0.001    0.017    0.001 {cPickle.dumps}
     1024    0.003    0.000    0.003    0.000 t.py:16(<lambda>)
       20    0.001    0.000    0.001    0.000 {reduce}
       21    0.001    0.000    0.001    0.000 {cPickle.loads}
       20    0.001    0.000    0.001    0.000 copy_reg.py:95(_slotnames)
       41    0.001    0.000    0.001    0.000 serializers.py:461(read_int)
       40    0.001    0.000    0.002    0.000 serializers.py:179(_batched)
       62    0.000    0.000    0.000    0.000 {method 'read' of 'file' objects}
       20    0.000    0.000   71.072    3.554 rdd.py:863(<lambda>)
       20    0.000    0.000    0.001    0.000 serializers.py:198(load_stream)
    40/20    0.000    0.000   71.072    3.554 rdd.py:2093(pipeline_func)
       41    0.000    0.000    0.002    0.000 serializers.py:130(load_stream)
       40    0.000    0.000   71.072    1.777 rdd.py:304(func)
       20    0.000    0.000   71.094    3.555 worker.py:82(process)
```

Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk
by `sc.dump_profiles(path)`, such as

```python
>>> sc._conf.set("spark.python.profile", "true")
>>> rdd = sc.parallelize(range(100)).map(str)
>>> rdd.count()
100
>>> sc.show_profiles()
============================================================
Profile of RDD<id=1>
============================================================
         284 function calls (276 primitive calls) in 0.001 seconds

   Ordered by: internal time, cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        4    0.000    0.000    0.000    0.000 serializers.py:198(load_stream)
        4    0.000    0.000    0.000    0.000 {reduce}
     12/4    0.000    0.000    0.001    0.000 rdd.py:2092(pipeline_func)
        4    0.000    0.000    0.000    0.000 {cPickle.loads}
        4    0.000    0.000    0.000    0.000 {cPickle.dumps}
      104    0.000    0.000    0.000    0.000 rdd.py:852(<genexpr>)
        8    0.000    0.000    0.000    0.000 serializers.py:461(read_int)
       12    0.000    0.000    0.000    0.000 rdd.py:303(func)
```
The profiling is disabled by default, can be enabled by "spark.python.profile=true".

Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump"

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

Closes #2351 from davies/profiler and squashes the following commits:

7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles()
2b0daf2 [Davies Liu] fix docs
7a56c24 [Davies Liu] bugfix
cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext
fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler
09d02c3 [Davies Liu] Merge branch 'master' into profiler
c23865c [Davies Liu] Merge branch 'master' into profiler
15d6f18 [Davies Liu] add docs for two configs
dadee1a [Davies Liu] add docs string and clear profiles after show or dump
4f8309d [Davies Liu] address comment, add tests
0a5b6eb [Davies Liu] fix Python UDF
4b20494 [Davies Liu] add profile for python

Fix the issue when applySchema() to an RDD of Row.

Also add type mapping for BinaryType.

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

Closes #2448 from davies/row and squashes the following commits:

dd220cf [Davies Liu] fix test
3f3f188 [Davies Liu] add more test
f559746 [Davies Liu] add tests, fix serialization
9688fd2 [Davies Liu] support applySchema to RDD of Row

Py4j can not handle large string efficiently, so we should use broadcast for large closure automatically. (Broadcast use local filesystem to pass through data).

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

Closes #2417 from davies/command and squashes the following commits:

fbf4e97 [Davies Liu] bugfix
aefd508 [Davies Liu] use broadcast automatically for large closure

Using Sphinx to generate API docs for PySpark.

requirement: Sphinx

```
$ cd python/docs/
$ make html
```

The generated API docs will be located at python/docs/_build/html/index.html

It can co-exists with those generated by Epydoc.

This is the first working version, after merging in, then we can continue to improve it and replace the epydoc finally.

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

Closes #2292 from davies/sphinx and squashes the following commits:

425a3b1 [Davies Liu] cleanup
1573298 [Davies Liu] move docs to python/docs/
5fe3903 [Davies Liu] Merge branch 'master' into sphinx
9468ab0 [Davies Liu] fix makefile
b408f38 [Davies Liu] address all comments
e2ccb1b [Davies Liu] update name and version
9081ead [Davies Liu] generate PySpark API docs using Sphinx

[SPARK-2314][SQL] Override collect and take in python library, and count in java library, with optimized versions.

SchemaRDD overrides RDD functions, including collect, count, and take, with optimized versions making use of the query optimizer.  The java and python interface classes wrapping SchemaRDD need to ensure the optimized versions are called as well.  This patch overrides relevant calls in the python and java interfaces with optimized versions.

Adds a new Row serialization pathway between python and java, based on JList[Array[Byte]] versus the existing RDD[Array[Byte]]. I wasn’t overjoyed about doing this, but I noticed that some QueryPlans implement optimizations in executeCollect(), which outputs an Array[Row] rather than the typical RDD[Row] that can be shipped to python using the existing serialization code. To me it made sense to ship the Array[Row] over to python directly instead of converting it back to an RDD[Row] just for the purpose of sending the Rows to python using the existing serialization code.

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

Closes #1592 from staple/SPARK-2314 and squashes the following commits:

89ff550 [Aaron Staple] Merge with master.
6bb7b6c [Aaron Staple] Fix typo.
b56d0ac [Aaron Staple] [SPARK-2314][SQL] Override count in JavaSchemaRDD, forwarding to SchemaRDD's count.
0fc9d40 [Aaron Staple] Fix comment typos.
f03cdfa [Aaron Staple] [SPARK-2314][SQL] Override collect and take in sql.py, forwarding to SchemaRDD's collect.

Added missing rdd.distinct(numPartitions) and associated tests

Author: Matthew Farrellee <matt@redhat.com>

Closes #2383 from mattf/SPARK-3519 and squashes the following commits:

30b837a [Matthew Farrellee] Combine test cases to save on JVM startups
6bc4a2c [Matthew Farrellee] [SPARK-3519] add distinct(n) to SchemaRDD in PySpark
7a17f2b [Matthew Farrellee] [SPARK-3519] add distinct(n) to PySpark

Currently, SchemaRDD._jschema_rdd is SchemaRDD, the Scala API (coalesce(), repartition()) can not been called in Python easily, there is no way to specify the implicit parameter `ord`. The _jrdd is an JavaRDD, so _jschema_rdd should also be JavaSchemaRDD.

In this patch, change _schema_rdd to JavaSchemaRDD, also added an assert for it. If some methods are missing from JavaSchemaRDD, then it's called by _schema_rdd.baseSchemaRDD().xxx().

BTW, Do we need JavaSQLContext?

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

Closes #2369 from davies/fix_schemardd and squashes the following commits:

abee159 [Davies Liu] use JavaSchemaRDD as SchemaRDD._jschema_rdd

Tiny PR making SQLContext a new-style class.  This allows various type logic to work more effectively

```Python
In [1]: import pyspark

In [2]: pyspark.sql.SQLContext.mro()
Out[2]: [pyspark.sql.SQLContext, object]
```

Author: Matthew Rocklin <mrocklin@gmail.com>

Closes #2288 from mrocklin/sqlcontext-new-style-class and squashes the following commits:

4aadab6 [Matthew Rocklin] update other old-style classes
a2dc02f [Matthew Rocklin] pyspark.sql.SQLContext is new-style class

The underline JavaRDD for PipelineRDD is created lazily, it's delayed until call _jrdd.

The id of JavaRDD is cached as `_id`, it saves a RPC call in py4j for later calls.

closes #1276

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

Closes #2296 from davies/id and squashes the following commits:

e197958 [Davies Liu] fix style
9721716 [Davies Liu] fix id of PipelineRDD

Author: Holden Karau <holden@pigscanfly.ca>

Closes #2280 from holdenk/SPARK-3406-Python-RDD-persist-api-does-not-have-default-storage-level and squashes the following commits:

33eaade [Holden Karau] As Josh pointed out, sql also override persist. Make persist behave the same as in the underlying RDD as well
e658227 [Holden Karau] Fix the test I added
e95a6c5 [Holden Karau] The Python persist function did not have a default storageLevel unlike the Scala API. Noticed this issue because we got a bug report back from the book where we had documented it as if it was the same as the Scala API

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

Closes #2251 from sarutak/SPARK-3378 and squashes the following commits:

0bfe234 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3378
bb5938f [Kousuke Saruta] Replaced rest of "SparkSQL" with "Spark SQL"
6df66de [Kousuke Saruta] Replaced "SparkSQL" with "Spark SQL"

After this patch, broadcast can be used in Python UDF.

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

Closes #2243 from davies/udf_broadcast and squashes the following commits:

7b88861 [Davies Liu] support broadcast in UDF

Put all public API in __all__, also put them all in pyspark.__init__.py, then we can got all the documents for public API by `pydoc pyspark`. It also can be used by other programs (such as Sphinx or Epydoc) to generate only documents for public APIs.

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

Closes #2205 from davies/public and squashes the following commits:

c6c5567 [Davies Liu] fix message
f7b35be [Davies Liu] put SchemeRDD, Row in pyspark.sql module
7e3016a [Davies Liu] add __all__ in mllib
6281b48 [Davies Liu] fix doc for SchemaRDD
6caab21 [Davies Liu] add public interfaces into pyspark.__init__.py

[SPARK-2969][SQL] Make ScalaReflection be able to handle ArrayType.containsNull and MapType.valueContainsNull.

Make `ScalaReflection` be able to handle like:

- `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)`
- `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)`
- `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)`
- `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)`

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #1889 from ueshin/issues/SPARK-2969 and squashes the following commits:

24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API.
79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API.
7cd1a7a [Takuya UESHIN] Fix json test failures.
2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true.
2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull.
9fa02f5 [Takuya UESHIN] Fix a test failure.
1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.

Test code in `sql.py` tries to compare two floating-point numbers directly, and cased [build failure(s)](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18365/consoleFull).

[Doctest documentation](https://docs.python.org/3/library/doctest.html#warnings) recommends using numbers in the form of `I/2**J` to avoid the precision issue.

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #1925 from liancheng/fix-pysql-fp-test and squashes the following commits:

0fbf584 [Cheng Lian] Removed unnecessary `...' from inferSchema doctest
e8059d4 [Cheng Lian] Using safe floating-point numbers in doctest