## What changes were proposed in this pull request?
This pr fixes the behaviour of `format("csv").option("quote", null)` along with one of spark-csv.
Also, it explicitly sets default values for CSV options in python.

## How was this patch tested?
Added tests in CSVSuite.

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

Closes #13372 from maropu/SPARK-15585.

## What changes were proposed in this pull request?
Currently structured streaming only supports append output mode.  This PR adds the following.

- Added support for Complete output mode in the internal state store, analyzer and planner.
- Added public API in Scala and Python for users to specify output mode
- Added checks for unsupported combinations of output mode and DF operations
  - Plans with no aggregation should support only Append mode
  - Plans with aggregation should support only Update and Complete modes
  - Default output mode is Append mode (**Question: should we change this to automatically set to Complete mode when there is aggregation?**)
- Added support for Complete output mode in Memory Sink. So Memory Sink internally supports append and complete, update. But from public API only Complete and Append output modes are supported.

## How was this patch tested?
Unit tests in various test suites
- StreamingAggregationSuite: tests for complete mode
- MemorySinkSuite: tests for checking behavior in Append and Complete modes.
- UnsupportedOperationSuite: tests for checking unsupported combinations of DF ops and output modes
- DataFrameReaderWriterSuite: tests for checking that output mode cannot be called on static DFs
- Python doc test and existing unit tests modified to call write.outputMode.

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

Closes #13286 from tdas/complete-mode.

## What changes were proposed in this pull request?

This reverts commit c24b6b67. Sent a PR to run Jenkins tests due to the revert conflicts of `dev/deps/spark-deps-hadoop*`.

## How was this patch tested?

Jenkins unit tests, integration tests, manual tests)

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #13417 from zsxwing/revert-SPARK-11753.

## What changes were proposed in this pull request?

`a` -> `an`

I use regex to generate potential error lines:
`grep -in ' a [aeiou]' mllib/src/main/scala/org/apache/spark/ml/*/*scala`
and review them line by line.

## How was this patch tested?

local build
`lint-java` checking

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #13317 from zhengruifeng/a_an.

## What changes were proposed in this pull request?

Default QuoteEscapingEnabled flag to true when writing CSV and add an escapeQuotes option to be able to change this.

See https://github.com/uniVocity/univocity-parsers/blob/f3eb2af26374940e60d91d1703bde54619f50c51/src/main/java/com/univocity/parsers/csv/CsvWriterSettings.java#L231-L247

This change is needed to be able to write RFC 4180 compatible CSV files (https://tools.ietf.org/html/rfc4180#section-2)

https://issues.apache.org/jira/browse/SPARK-15493

## How was this patch tested?

Added a test that verifies the output is quoted correctly.

Author: Jurriaan Pruis <email@jurriaanpruis.nl>

Closes #13267 from jurriaan/quote-escaping.

## What changes were proposed in this pull request?

Jackson suppprts `allowNonNumericNumbers` option to parse non-standard non-numeric numbers such as "NaN", "Infinity", "INF".  Currently used Jackson version (2.5.3) doesn't support it all. This patch upgrades the library and make the two ignored tests in `JsonParsingOptionsSuite` passed.

## How was this patch tested?

`JsonParsingOptionsSuite`.

Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Liang-Chi Hsieh <viirya@appier.com>

Closes #9759 from viirya/fix-json-nonnumric.

## What changes were proposed in this pull request?
This patch is a follow-up to https://github.com/apache/spark/pull/13104 and adds documentation to clarify the semantics of read.text with respect to partitioning.

## How was this patch tested?
N/A

Author: Reynold Xin <rxin@databricks.com>

Closes #13184 from rxin/SPARK-14463.

## What changes were proposed in this pull request?

Update the unit test code, examples, and documents to remove calls to deprecated method `dataset.registerTempTable`.

## How was this patch tested?

This PR only changes the unit test code, examples, and comments. It should be safe.
This is a follow up of PR https://github.com/apache/spark/pull/12945 which was merged.

Author: Sean Zhong <seanzhong@databricks.com>

Closes #13098 from clockfly/spark-15171-remove-deprecation.

## What changes were proposed in this pull request?
Seems https://github.com/apache/spark/commit/db573fc743d12446dd0421fb45d00c2f541eaf9a did not remove withHiveSupport from readwrite.py

Author: Yin Huai <yhuai@databricks.com>

Closes #13069 from yhuai/fixPython.

## What changes were proposed in this pull request?

When a CSV begins with:
- `,,`
OR
- `"","",`

meaning that the first column names are either empty or blank strings and `header` is specified to be `true`, then the column name is replaced with `C` + the index number of that given column. For example, if you were to read in the CSV:
```
"","second column"
"hello", "there"
```
Then column names would become `"C0", "second column"`.

This behavior aligns with what currently happens when `header` is specified to be `false` in recent versions of Spark.

### Current Behavior in Spark <=1.6
In Spark <=1.6, a CSV with a blank column name becomes a blank string, `""`, meaning that this column cannot be accessed. However the CSV reads in without issue.

### Current Behavior in Spark 2.0
Spark throws a NullPointerError and will not read in the file.

#### Reproduction in 2.0
https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/346304/2828750690305044/484361/latest.html

## How was this patch tested?
A new test was added to `CSVSuite` to account for this issue. We then have asserts that test for being able to select both the empty column names as well as the regular column names.

Author: Bill Chambers <bill@databricks.com>
Author: Bill Chambers <wchambers@ischool.berkeley.edu>

Closes #13041 from anabranch/master.

This PR:
* Corrects the documentation for the `properties` parameter, which is supposed to be a dictionary and not a list.
* Generally clarifies the Python docstring for DataFrameReader.jdbc() by pulling from the [Scala docstrings](https://github.com/apache/spark/blob/b28137764716f56fa1a923c4278624a56364a505/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala#L201-L251) and rephrasing things.
* Corrects minor Sphinx typos.

Author: Nicholas Chammas <nicholas.chammas@gmail.com>

Closes #13034 from nchammas/SPARK-15256.

## What changes were proposed in this pull request?
Use SparkSession instead of SQLContext in Python TestSuites

## How was this patch tested?
Existing tests

Author: Sandeep Singh <sandeep@techaddict.me>

Closes #13044 from techaddict/SPARK-15037-python.

## What changes were proposed in this pull request?

This PR removes the old `json(path: String)` API which is covered by the new `json(paths: String*)`.

## How was this patch tested?

Jenkins tests (existing tests should cover this)

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>

Closes #13040 from HyukjinKwon/SPARK-15250.

## What changes were proposed in this pull request?
This patch removes experimental tag from DataFrameReader and DataFrameWriter, and explicitly tags a few methods added for structured streaming as experimental.

## How was this patch tested?
N/A

Author: Reynold Xin <rxin@databricks.com>

Closes #13038 from rxin/SPARK-15261.

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-15050

This PR adds function parameters for Python API for reading and writing `csv()`.

## How was this patch tested?

This was tested by `./dev/run_tests`.

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>

Closes #12834 from HyukjinKwon/SPARK-15050.

## What changes were proposed in this pull request?

This PR adds the explanation and documentation for CSV options for reading and writing.

## How was this patch tested?

Style tests with `./dev/run_tests` for documentation style.

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>

Closes #12817 from HyukjinKwon/SPARK-13425.

## What changes were proposed in this pull request?

This PR adds Python APIs for:
 - `ContinuousQueryManager`
 - `ContinuousQueryException`

The `ContinuousQueryException` is a very basic wrapper, it doesn't provide the functionality that the Scala side provides, but it follows the same pattern for `AnalysisException`.

For `ContinuousQueryManager`, all APIs are provided except for registering listeners.

This PR also attempts to fix test flakiness by stopping all active streams just before tests.

## How was this patch tested?

Python Doc tests and unit tests

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #12673 from brkyvz/pyspark-cqm.

## What changes were proposed in this pull request?

```
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /__ / .__/\_,_/_/ /_/\_\   version 2.0.0-SNAPSHOT
      /_/

Using Python version 2.7.5 (default, Mar  9 2014 22:15:05)
SparkSession available as 'spark'.
>>> spark
<pyspark.sql.session.SparkSession object at 0x101f3bfd0>
>>> spark.sql("SHOW TABLES").show()
...
+---------+-----------+
|tableName|isTemporary|
+---------+-----------+
|      src|      false|
+---------+-----------+

>>> spark.range(1, 10, 2).show()
+---+
| id|
+---+
|  1|
|  3|
|  5|
|  7|
|  9|
+---+
```
**Note**: This API is NOT complete in its current state. In particular, for now I left out the `conf` and `catalog` APIs, which were added later in Scala. These will be added later before 2.0.

## How was this patch tested?

Python tests.

Author: Andrew Or <andrew@databricks.com>

Closes #12746 from andrewor14/python-spark-session.

## What changes were proposed in this pull request?

In Python, the `option` and `options` method of `DataFrameReader` and `DataFrameWriter` were sending the string "None" instead of `null` when passed `None`, therefore making it impossible to send an actual `null`. This fixes that problem.

This is based on #11305 from mathieulongtin.

## How was this patch tested?

Added test to readwriter.py.

Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: mathieu longtin <mathieu.longtin@nuance.com>

Closes #12494 from viirya/py-df-none-option.

## What changes were proposed in this pull request?

This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes:
 - ContinuousQuery
 - Trigger
 - ProcessingTime
in pyspark under `pyspark.sql.streaming`.

In addition, it contains the new methods added under:
 -  `DataFrameWriter`
     a) `startStream`
     b) `trigger`
     c) `queryName`

 -  `DataFrameReader`
     a) `stream`

 - `DataFrame`
    a) `isStreaming`

This PR doesn't contain all methods exposed for `ContinuousQuery`, for example:
 - `exception`
 - `sourceStatuses`
 - `sinkStatus`

They may be added in a follow up.

This PR also contains some very minor doc fixes in the Scala side.

## How was this patch tested?

Python doc tests

TODO:
 - [ ] verify Python docs look good

Author: Burak Yavuz <brkyvz@gmail.com>
Author: Burak Yavuz <burak@databricks.com>

Closes #12320 from brkyvz/stream-python.

[SPARK-14231] [SQL] JSON data source infers floating-point values as a double when they do not fit in a decimal

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-14231

Currently, JSON data source supports to infer `DecimalType` for big numbers and `floatAsBigDecimal` option which reads floating-point values as `DecimalType`.

But there are few restrictions in Spark `DecimalType` below:

1. The precision cannot be bigger than 38.
2. scale cannot be bigger than precision.

Currently, both restrictions are not being handled.

This PR handles the cases by inferring them as `DoubleType`. Also, the option name was changed from `floatAsBigDecimal` to `prefersDecimal` as suggested [here](https://issues.apache.org/jira/browse/SPARK-14231?focusedCommentId=15215579&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15215579).

So, the codes below:

```scala
def doubleRecords: RDD[String] =
  sqlContext.sparkContext.parallelize(
    s"""{"a": 1${"0" * 38}, "b": 0.01}""" ::
    s"""{"a": 2${"0" * 38}, "b": 0.02}""" :: Nil)

val jsonDF = sqlContext.read
  .option("prefersDecimal", "true")
  .json(doubleRecords)
jsonDF.printSchema()
```

produces below:

- **Before**

```scala
org.apache.spark.sql.AnalysisException: Decimal scale (2) cannot be greater than precision (1).;
	at org.apache.spark.sql.types.DecimalType.<init>(DecimalType.scala:44)
	at org.apache.spark.sql.execution.datasources.json.InferSchema$.org$apache$spark$sql$execution$datasources$json$InferSchema$$inferField(InferSchema.scala:144)
	at org.apache.spark.sql.execution.datasources.json.InferSchema$.org$apache$spark$sql$execution$datasources$json$InferSchema$$inferField(InferSchema.scala:108)
	at
...
```

- **After**

```scala
root
 |-- a: double (nullable = true)
 |-- b: double (nullable = true)
```

## How was this patch tested?

Unit tests were used and `./dev/run_tests` for coding style tests.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #12030 from HyukjinKwon/SPARK-14231.

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-13953

Currently, JSON data source creates a new field in `PERMISSIVE` mode for storing malformed string.
This field can be renamed via `spark.sql.columnNameOfCorruptRecord` option but it is a global configuration.

This PR make that option can be applied per read and can be specified via `option()`. This will overwrites `spark.sql.columnNameOfCorruptRecord` if it is set.

## How was this patch tested?

Unit tests were used and `./dev/run_tests` for coding style tests.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #11881 from HyukjinKwon/SPARK-13953.

## What changes were proposed in this pull request?

Currently, there is no way to control the behaviour when fails to parse corrupt records in JSON data source .

This PR adds the support for parse modes just like CSV data source. There are three modes below:

- `PERMISSIVE` :  When it fails to parse, this sets `null` to to field. This is a default mode when it has been this mode.
- `DROPMALFORMED`: When it fails to parse, this drops the whole record.
- `FAILFAST`: When it fails to parse, it just throws an exception.

This PR also make JSON data source share the `ParseModes` in CSV data source.

## How was this patch tested?

Unit tests were used and `./dev/run_tests` for code style tests.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #11756 from HyukjinKwon/SPARK-13764.

## What changes were proposed in this pull request?

This PR adds the support to specify compression codecs for both ORC and Parquet.

## How was this patch tested?

unittests within IDE and code style tests with `dev/run_tests`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #11464 from HyukjinKwon/SPARK-13543.

https://issues.apache.org/jira/browse/SPARK-13507
https://issues.apache.org/jira/browse/SPARK-13509

## What changes were proposed in this pull request?
This PR adds the support to write CSV data directly by a single call to the given path.

Several unitests were added for each functionality.
## How was this patch tested?

This was tested with unittests and with `dev/run_tests` for coding style

Author: hyukjinkwon <gurwls223@gmail.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>

Closes #11389 from HyukjinKwon/SPARK-13507-13509.

I tried to add this via `USE_BIG_DECIMAL_FOR_FLOATS` option from Jackson with no success.

Added test for non-complex types. Should I add a test for complex types?

Author: Brandon Bradley <bradleytastic@gmail.com>

Closes #10936 from blbradley/spark-12749.

Author: Reynold Xin <rxin@databricks.com>

Closes #10559 from rxin/remove-deprecated-sql.

We can provides the option to choose JSON parser can be enabled to accept quoting of all character or not.

Author: Cazen <Cazen@korea.com>
Author: Cazen Lee <cazen.lee@samsung.com>
Author: Cazen Lee <Cazen@korea.com>
Author: cazen.lee <cazen.lee@samsung.com>

Closes #10497 from Cazen/master.

Since we rename the column name from ```text``` to ```value``` for DataFrame load by ```SQLContext.read.text```, we need to update doc.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #10349 from yanboliang/text-value.

This patch makes it consistent to use varargs in all DataFrameReader methods, including Parquet, JSON, text, and the generic load function.

Also added a few more API tests for the Java API.

Author: Reynold Xin <rxin@databricks.com>

Closes #9945 from rxin/SPARK-11967.

…ion in PySpark

Author: Jeff Zhang <zjffdu@apache.org>

Closes #9791 from zjffdu/SPARK-11804.

This patch adds the following options to the JSON data source, for dealing with non-standard JSON files:
* `allowComments` (default `false`): ignores Java/C++ style comment in JSON records
* `allowUnquotedFieldNames` (default `false`): allows unquoted JSON field names
* `allowSingleQuotes` (default `true`): allows single quotes in addition to double quotes
* `allowNumericLeadingZeros` (default `false`): allows leading zeros in numbers (e.g. 00012)

To avoid passing a lot of options throughout the json package, I introduced a new JSONOptions case class to define all JSON config options.

Also updated documentation to explain these options.

Scala

![screen shot 2015-11-15 at 6 12 12 pm](https://cloud.githubusercontent.com/assets/323388/11172965/e3ace6ec-8bc4-11e5-805e-2d78f80d0ed6.png)

Python

![screen shot 2015-11-15 at 6 11 28 pm](https://cloud.githubusercontent.com/assets/323388/11172964/e23ed6ee-8bc4-11e5-8216-312f5983acd5.png)

Author: Reynold Xin <rxin@databricks.com>

Closes #9724 from rxin/SPARK-11745.

#9527 missed updating the python tests.

Author: Michael Armbrust <michael@databricks.com>

Closes #9533 from marmbrus/hotfixTextValue.

Adds DataFrameReader.text and DataFrameWriter.text.

Author: Reynold Xin <rxin@databricks.com>

Closes #9259 from rxin/SPARK-11292.

Make sure comma-separated paths get processed correcly in ResolvedDataSource for a HadoopFsRelationProvider

Author: Koert Kuipers <koert@tresata.com>

Closes #8416 from koertkuipers/feat-sql-comma-separated-paths.

cc mengxr

Author: Davies Liu <davies@databricks.com>

Closes #8657 from davies/move_since.

PySpark DataFrameReader should could accept an RDD of Strings (like the Scala version does) for JSON, rather than only taking a path.
If this PR is merged, it should be duplicated to cover the other input types (not just JSON).

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #8444 from yanboliang/spark-9964.

Author: MechCoder <manojkumarsivaraj334@gmail.com>

Closes #8110 from MechCoder/spark-9828.

JIRA: https://issues.apache.org/jira/browse/SPARK-6591

Author: Yijie Shen <henry.yijieshen@gmail.com>

Closes #7926 from yjshen/py_dsload_opt and squashes the following commits:

b207832 [Yijie Shen] fix style
efdf834 [Yijie Shen] resolve comment
7a8f6a2 [Yijie Shen] lowercase
822e769 [Yijie Shen] convert load opts to string

This PR adds DataFrame reader/writer shortcut methods for ORC in both Scala and Python.

Author: Cheng Lian <lian@databricks.com>

Closes #7444 from liancheng/spark-9100 and squashes the following commits:

284d043 [Cheng Lian] Fixes PySpark test cases and addresses PR comments
e0b09fb [Cheng Lian] Adds DataFrame reader/writer shortcut methods for ORC