[SPARK-18291][SPARKR][ML] Revert "[SPARK-18291][SPARKR][ML] SparkR glm predict should output original label when family = binomial."

## What changes were proposed in this pull request?
It's better we can fix this issue by providing an option ```type``` for users to change the ```predict``` output schema, then they could output probabilities, log-space predictions, or original labels. In order to not involve breaking API change for 2.1, so revert this change firstly and will add it back after [SPARK-18618](https://issues.apache.org/jira/browse/SPARK-18618

) resolved.

## How was this patch tested?
Existing unit tests.

This reverts commit daa975f4.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #16118 from yanboliang/spark-18291-revert.

(cherry picked from commit a985dd8e)
Signed-off-by: Joseph K. Bradley <joseph@databricks.com>

## What changes were proposed in this pull request?

Similar to SPARK-18401, as a classification algorithm, logistic regression should support output original label instead of supporting index label.

In this PR, original label output is supported and test cases are modified and added. Document is also modified.

## How was this patch tested?

Unit tests.

Author: wm624@hotmail.com <wm624@hotmail.com>

Closes #15910 from wangmiao1981/audit.

(cherry picked from commit 2eb6764f)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?

### The Issue

If I specify my schema when doing
```scala
spark.read
  .schema(someSchemaWherePartitionColumnsAreStrings)
```
but if the partition inference can infer it as IntegerType or I assume LongType or DoubleType (basically fixed size types), then once UnsafeRows are generated, your data will be corrupted.

### Proposed solution

The partition handling code path is kind of a mess. In my fix I'm probably adding to the mess, but at least trying to standardize the code path.

The real issue is that a user that uses the `spark.read` code path can never clearly specify what the partition columns are. If you try to specify the fields in `schema`, we practically ignore what the user provides, and fall back to our inferred data types. What happens in the end is data corruption.

My solution tries to fix this by always trying to infer partition columns the first time you specify the table. Once we find what the partition columns are, we try to find them in the user specified schema and use the dataType provided there, or fall back to the smallest common data type.

We will ALWAYS append partition columns to the user's schema, even if they didn't ask for it. We will only use the data type they provided if they specified it. While this is confusing, this has been the behavior since Spark 1.6, and I didn't want to change this behavior in the QA period of Spark 2.1. We may revisit this decision later.

A side effect of this PR is that we won't need https://github.com/apache/spark/pull/15942

 if this PR goes in.

## How was this patch tested?

Regression tests

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #15951 from brkyvz/partition-corruption.

(cherry picked from commit 0d1bf2b6)
Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>

## What changes were proposed in this pull request?

Updates links to the wiki to links to the new location of content on spark.apache.org.

## How was this patch tested?

Doc builds

Author: Sean Owen <sowen@cloudera.com>

Closes #15967 from srowen/SPARK-18073.1.

(cherry picked from commit 7e0cd1d9)
Signed-off-by: Sean Owen <sowen@cloudera.com>

## What changes were proposed in this pull request?
* Fix SparkR ```spark.glm``` errors when fitting on collinear data, since ```standard error of coefficients, t value and p value``` are not available in this condition.
* Scala/Python GLM summary should throw exception if users get ```standard error of coefficients, t value and p value``` but the underlying WLS was solved by local "l-bfgs".

## How was this patch tested?
Add unit tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15930 from yanboliang/spark-18501.

(cherry picked from commit 982b82e3)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?

It seems in R, there are

- `Note:`
- `NOTE:`
- `Note that`

This PR proposes to fix those to `Note:` to be consistent.

**Before**

![2016-11-21 11 30 07](https://cloud.githubusercontent.com/assets/6477701/20468848/2f27b0fa-afde-11e6-89e3-993701269dbe.png)

**After**

![2016-11-21 11 29 44](https://cloud.githubusercontent.com/assets/6477701/20468851/39469664-afde-11e6-9929-ad80be7fc405.png

)

## How was this patch tested?

The notes were found via

```bash
grep -r "NOTE: " .
grep -r "Note that " .
```

And then fixed one by one comparing with API documentation.

After that, manually tested via `sh create-docs.sh` under `./R`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15952 from HyukjinKwon/SPARK-18514.

(cherry picked from commit 4922f9cd)
Signed-off-by: Sean Owen <sowen@cloudera.com>

## What changes were proposed in this pull request?
When running SparkR job in yarn-cluster mode, it will download Spark package from apache website which is not necessary.
```
./bin/spark-submit --master yarn-cluster ./examples/src/main/r/dataframe.R
```
The following is output:
```
Attaching package: ‘SparkR’

The following objects are masked from ‘package:stats’:

    cov, filter, lag, na.omit, predict, sd, var, window

The following objects are masked from ‘package:base’:

    as.data.frame, colnames, colnames<-, drop, endsWith, intersect,
    rank, rbind, sample, startsWith, subset, summary, transform, union

Spark not found in SPARK_HOME:
Spark not found in the cache directory. Installation will start.
MirrorUrl not provided.
Looking for preferred site from apache website...
......
```
There's no ```SPARK_HOME``` in yarn-cluster mode since the R process is in a remote host of the yarn cluster rather than in the client host. The JVM comes up first and the R process then connects to it. So in such cases we should never have to download Spark as Spark is already running.

## How was this patch tested?
Offline test.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15888 from yanboliang/spark-18444.

(cherry picked from commit acb97157)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?

I found the documentation for the sample method to be confusing, this adds more clarification across all languages.

- [x] Scala
- [x] Python
- [x] R
- [x] RDD Scala
- [ ] RDD Python with SEED
- [X] RDD Java
- [x] RDD Java with SEED
- [x] RDD Python

## How was this patch tested?

NA

Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark

 before opening a pull request.

Author: anabranch <wac.chambers@gmail.com>
Author: Bill Chambers <bill@databricks.com>

Closes #15815 from anabranch/SPARK-18365.

(cherry picked from commit 49b6f456)
Signed-off-by: Sean Owen <sowen@cloudera.com>

## What changes were proposed in this pull request?
```spark.mlp``` should support ```RFormula``` like other ML algorithm wrappers.
BTW, I did some cleanup and improvement for ```spark.mlp```.

## How was this patch tested?
Unit tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15883 from yanboliang/spark-18438.

(cherry picked from commit 95eb06bd)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?
* Fix the following exceptions which throws when ```spark.randomForest```(classification), ```spark.gbt```(classification), ```spark.naiveBayes``` and ```spark.glm```(binomial family) were fitted on libsvm data.
```
java.lang.IllegalArgumentException: requirement failed: If label column already exists, forceIndexLabel can not be set with true.
```
See [SPARK-18412](https://issues.apache.org/jira/browse/SPARK-18412

) for more detail about how to reproduce this bug.
* Refactor out ```getFeaturesAndLabels``` to RWrapperUtils, since lots of ML algorithm wrappers use this function.
* Drop some unwanted columns when making prediction.

## How was this patch tested?
Add unit test.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15851 from yanboliang/spark-18412.

(cherry picked from commit 07be232e)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

[SPARK-18264][SPARKR] build vignettes with package, update vignettes for CRAN release build and add info on release

## What changes were proposed in this pull request?

Changes to DESCRIPTION to build vignettes.
Changes the metadata for vignettes to generate the recommended format (which is about <10% of size before). Unfortunately it does not look as nice
(before - left, after - right)

![image](https://cloud.githubusercontent.com/assets/8969467/20040492/b75883e6-a40d-11e6-9534-25cdd5d59a8b.png)

![image](https://cloud.githubusercontent.com/assets/8969467/20040490/a40f4d42-a40d-11e6-8c91-af00ddcbdad9.png

)

Also add information on how to run build/release to CRAN later.

## How was this patch tested?

manually, unit tests

shivaram

We need this for branch-2.1

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15790 from felixcheung/rpkgvignettes.

(cherry picked from commit ba23f768)
Signed-off-by: Shivaram Venkataraman <shivaram@cs.berkeley.edu>

## What changes were proposed in this pull request?
SparkR ```spark.randomForest``` classification prediction should output original label rather than the indexed label. This issue is very similar with [SPARK-18291](https://issues.apache.org/jira/browse/SPARK-18291

).

## How was this patch tested?
Add unit tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15842 from yanboliang/spark-18401.

(cherry picked from commit 5ddf6947)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?

Gradient Boosted Tree in R.
With a few minor improvements to RandomForest in R.

Since this is relatively isolated I'd like to target this for branch-2.1

## How was this patch tested?

manual tests, unit tests

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15746 from felixcheung/rgbt.

(cherry picked from commit 55964c15)
Signed-off-by: Felix Cheung <felixcheung@apache.org>

## What changes were proposed in this pull request?
SparkR ```spark.glm``` predict should output original label when family = "binomial".

## How was this patch tested?
Add unit test.
You can also run the following code to test:
```R
training <- suppressWarnings(createDataFrame(iris))
training <- training[training$Species %in% c("versicolor", "virginica"), ]
model <- spark.glm(training, Species ~ Sepal_Length + Sepal_Width,family = binomial(link = "logit"))
showDF(predict(model, training))
```
Before this change:
```
+------------+-----------+------------+-----------+----------+-----+-------------------+
|Sepal_Length|Sepal_Width|Petal_Length|Petal_Width|   Species|label|         prediction|
+------------+-----------+------------+-----------+----------+-----+-------------------+
|         7.0|        3.2|         4.7|        1.4|versicolor|  0.0| 0.8271421517601544|
|         6.4|        3.2|         4.5|        1.5|versicolor|  0.0| 0.6044595910413112|
|         6.9|        3.1|         4.9|        1.5|versicolor|  0.0| 0.7916340858281998|
|         5.5|        2.3|         4.0|        1.3|versicolor|  0.0|0.16080518180591158|
|         6.5|        2.8|         4.6|        1.5|versicolor|  0.0| 0.6112229217050189|
|         5.7|        2.8|         4.5|        1.3|versicolor|  0.0| 0.2555087295500885|
|         6.3|        3.3|         4.7|        1.6|versicolor|  0.0| 0.5681507664364834|
|         4.9|        2.4|         3.3|        1.0|versicolor|  0.0|0.05990570219972002|
|         6.6|        2.9|         4.6|        1.3|versicolor|  0.0| 0.6644434078306246|
|         5.2|        2.7|         3.9|        1.4|versicolor|  0.0|0.11293577405862379|
|         5.0|        2.0|         3.5|        1.0|versicolor|  0.0|0.06152372321585971|
|         5.9|        3.0|         4.2|        1.5|versicolor|  0.0|0.35250697207602555|
|         6.0|        2.2|         4.0|        1.0|versicolor|  0.0|0.32267018290814303|
|         6.1|        2.9|         4.7|        1.4|versicolor|  0.0|  0.433391153814592|
|         5.6|        2.9|         3.6|        1.3|versicolor|  0.0| 0.2280744262436993|
|         6.7|        3.1|         4.4|        1.4|versicolor|  0.0| 0.7219848389339459|
|         5.6|        3.0|         4.5|        1.5|versicolor|  0.0|0.23527698971404695|
|         5.8|        2.7|         4.1|        1.0|versicolor|  0.0|  0.285024533520016|
|         6.2|        2.2|         4.5|        1.5|versicolor|  0.0| 0.4107047877447493|
|         5.6|        2.5|         3.9|        1.1|versicolor|  0.0|0.20083561961645083|
+------------+-----------+------------+-----------+----------+-----+-------------------+
```
After this change:
```
+------------+-----------+------------+-----------+----------+-----+----------+
|Sepal_Length|Sepal_Width|Petal_Length|Petal_Width|   Species|label|prediction|
+------------+-----------+------------+-----------+----------+-----+----------+
|         7.0|        3.2|         4.7|        1.4|versicolor|  0.0| virginica|
|         6.4|        3.2|         4.5|        1.5|versicolor|  0.0| virginica|
|         6.9|        3.1|         4.9|        1.5|versicolor|  0.0| virginica|
|         5.5|        2.3|         4.0|        1.3|versicolor|  0.0|versicolor|
|         6.5|        2.8|         4.6|        1.5|versicolor|  0.0| virginica|
|         5.7|        2.8|         4.5|        1.3|versicolor|  0.0|versicolor|
|         6.3|        3.3|         4.7|        1.6|versicolor|  0.0| virginica|
|         4.9|        2.4|         3.3|        1.0|versicolor|  0.0|versicolor|
|         6.6|        2.9|         4.6|        1.3|versicolor|  0.0| virginica|
|         5.2|        2.7|         3.9|        1.4|versicolor|  0.0|versicolor|
|         5.0|        2.0|         3.5|        1.0|versicolor|  0.0|versicolor|
|         5.9|        3.0|         4.2|        1.5|versicolor|  0.0|versicolor|
|         6.0|        2.2|         4.0|        1.0|versicolor|  0.0|versicolor|
|         6.1|        2.9|         4.7|        1.4|versicolor|  0.0|versicolor|
|         5.6|        2.9|         3.6|        1.3|versicolor|  0.0|versicolor|
|         6.7|        3.1|         4.4|        1.4|versicolor|  0.0| virginica|
|         5.6|        3.0|         4.5|        1.5|versicolor|  0.0|versicolor|
|         5.8|        2.7|         4.1|        1.0|versicolor|  0.0|versicolor|
|         6.2|        2.2|         4.5|        1.5|versicolor|  0.0|versicolor|
|         5.6|        2.5|         3.9|        1.1|versicolor|  0.0|versicolor|
+------------+-----------+------------+-----------+----------+-----+----------+
```

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15788 from yanboliang/spark-18291.

(cherry picked from commit daa975f4)
Signed-off-by: Yanbo Liang <ybliang8@gmail.com>

## What changes were proposed in this pull request?

This PR proposes to improve documentation and fix some descriptions equivalent to several minor fixes identified in https://github.com/apache/spark/pull/15677

Also, this suggests to change `Note:` and `NOTE:` to `.. note::` consistently with the others which marks up pretty.

## How was this patch tested?

Jenkins tests and manually.

For PySpark, `Note:` and `NOTE:` to `.. note::` make the document as below:

**From**

![2016-11-04 6 53 35](https://cloud.githubusercontent.com/assets/6477701/20002648/42989922-a2c5-11e6-8a32-b73eda49e8c3.png)
![2016-11-04 6 53 45](https://cloud.githubusercontent.com/assets/6477701/20002650/429fb310-a2c5-11e6-926b-e030d7eb0185.png)
![2016-11-04 6 54 11](https://cloud.githubusercontent.com/assets/6477701/20002649/429d570a-a2c5-11e6-9e7e-44090f337e32.png)
![2016-11-04 6 53 51](https://cloud.githubusercontent.com/assets/6477701/20002647/4297fc74-a2c5-11e6-801a-b89fbcbfca44.png)
![2016-11-04 6 53 51](https://cloud.githubusercontent.com/assets/6477701/20002697/749f5780-a2c5-11e6-835f-022e1f2f82e3.png)

**To**

![2016-11-04 7 03 48](https://cloud.githubusercontent.com/assets/6477701/20002659/4961b504-a2c5-11e6-9ee0-ef0751482f47.png)
![2016-11-04 7 04 03](https://cloud.githubusercontent.com/assets/6477701/20002660/49871d3a-a2c5-11e6-85ea-d9a5d11efeff.png)
![2016-11-04 7 04 28](https://cloud.githubusercontent.com/assets/6477701/20002662/498e0f14-a2c5-11e6-803d-c0c5aeda4153.png)
![2016-11-04 7 33 39](https://cloud.githubusercontent.com/assets/6477701/20002731/a76e30d2-a2c5-11e6-993b-0481b8342d6b.png)
![2016-11-04 7 33 39](https://cloud.githubusercontent.com/assets/6477701/20002731/a76e30d2-a2c5-11e6-993b-0481b8342d6b.png

)

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15765 from HyukjinKwon/minor-function-doc.

(cherry picked from commit 15d39268)
Signed-off-by: Felix Cheung <felixcheung@apache.org>

## What changes were proposed in this pull request?

minor doc update that should go to master & branch-2.1

## How was this patch tested?

manual

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15747 from felixcheung/pySPARK-14393.

(cherry picked from commit a08463b1)
Signed-off-by: Felix Cheung <felixcheung@apache.org>

## What changes were proposed in this pull request?

Due to a limitation of hive metastore(table location must be directory path, not file path), we always store `path` for data source table in storage properties, instead of the `locationUri` field. However, we should not expose this difference to `CatalogTable` level, but just treat it as a hack in `HiveExternalCatalog`, like we store table schema of data source table in table properties.

This PR unifies `path` and `locationUri` outside of `HiveExternalCatalog`, both data source table and hive serde table should use the `locationUri` field.

This PR also unifies the way we handle default table location for managed table. Previously, the default table location of hive serde managed table is set by external catalog, but the one of data source table is set by command. After this PR, we follow the hive way and the default table location is always set by external catalog.

For managed non-file-based tables, we will assign a default table location and create an empty directory for it, the table location will be removed when the table is dropped. This is reasonable as metastore doesn't care about whether a table is file-based or not, and an empty table directory has no harm.
For external non-file-based tables, ideally we can omit the table location, but due to a hive metastore issue, we will assign a random location to it, and remove it right after the table is created. See SPARK-15269 for more details. This is fine as it's well isolated in `HiveExternalCatalog`.

To keep the existing behaviour of the `path` option, in this PR we always add the `locationUri` to storage properties using key `path`, before passing storage properties to `DataSource` as data source options.
## How was this patch tested?

existing tests.

Author: Wenchen Fan <wenchen@databricks.com>

Closes #15024 from cloud-fan/path.

(cherry picked from commit 3a1bc6f4)
Signed-off-by: Yin Huai <yhuai@databricks.com>

## What changes were proposed in this pull request?

Simplify struct creation, especially the aspect of `CleanupAliases` which missed some aliases when handling trees created by `CreateStruct`.

This PR includes:

1. A failing test (create struct with nested aliases, some of the aliases survive `CleanupAliases`).
2. A fix that transforms `CreateStruct` into a `CreateNamedStruct` constructor, effectively eliminating `CreateStruct` from all expression trees.
3. A `NamePlaceHolder` used by `CreateStruct` when column names cannot be extracted from unresolved `NamedExpression`.
4. A new Analyzer rule that resolves `NamePlaceHolder` into a string literal once the `NamedExpression` is resolved.
5. `CleanupAliases` code was simplified as it no longer has to deal with `CreateStruct`'s top level columns.

## How was this patch tested?
Running all tests-suits in package org.apache.spark.sql, especially including the analysis suite, making sure added test initially fails, after applying suggested fix rerun the entire analysis package successfully.

Modified few tests that expected `CreateStruct` which is now transformed into `CreateNamedStruct`.

Author: eyal farago <eyal farago>
Author: Herman van Hovell <hvanhovell@databricks.com>
Author: eyal farago <eyal.farago@gmail.com>
Author: Eyal Farago <eyal.farago@actimize.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Author: eyalfa <eyal.farago@gmail.com>

Closes #15718 from hvanhovell/SPARK-16839-2.

(cherry picked from commit f151bd1a)
Signed-off-by: Herman van Hovell <hvanhovell@databricks.com>

[SPARK-17838][SPARKR] Check named arguments for options and use formatted R friendly message from JVM exception message

## What changes were proposed in this pull request?

This PR proposes to
- improve the R-friendly error messages rather than raw JVM exception one.

  As `read.json`, `read.text`, `read.orc`, `read.parquet` and `read.jdbc` are executed in the same  path with `read.df`, and `write.json`, `write.text`, `write.orc`, `write.parquet` and `write.jdbc` shares the same path with `write.df`, it seems it is safe to call `handledCallJMethod` to handle
  JVM messages.
-  prevent `zero-length variable name` and prints the ignored options as an warning message.

**Before**

``` r
> read.json("path", a = 1, 2, 3, "a")
Error in env[[name]] <- value :
  zero-length variable name
```

``` r
> read.json("arbitrary_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/...;
  at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$12.apply(DataSource.scala:398)
  ...

> read.orc("arbitrary_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/...;
  at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$12.apply(DataSource.scala:398)
  ...

> read.text("arbitrary_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/...;
  at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$12.apply(DataSource.scala:398)
  ...

> read.parquet("arbitrary_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/...;
  at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$12.apply(DataSource.scala:398)
  ...
```

``` r
> write.json(df, "existing_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: path file:/... already exists.;
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:68)

> write.orc(df, "existing_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: path file:/... already exists.;
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:68)

> write.text(df, "existing_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: path file:/... already exists.;
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:68)

> write.parquet(df, "existing_path")
Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) :
  org.apache.spark.sql.AnalysisException: path file:/... already exists.;
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:68)
```

**After**

``` r
read.json("arbitrary_path", a = 1, 2, 3, "a")
Unnamed arguments ignored: 2, 3, a.
```

``` r
> read.json("arbitrary_path")
Error in json : analysis error - Path does not exist: file:/...

> read.orc("arbitrary_path")
Error in orc : analysis error - Path does not exist: file:/...

> read.text("arbitrary_path")
Error in text : analysis error - Path does not exist: file:/...

> read.parquet("arbitrary_path")
Error in parquet : analysis error - Path does not exist: file:/...
```

``` r
> write.json(df, "existing_path")
Error in json : analysis error - path file:/... already exists.;

> write.orc(df, "existing_path")
Error in orc : analysis error - path file:/... already exists.;

> write.text(df, "existing_path")
Error in text : analysis error - path file:/... already exists.;

> write.parquet(df, "existing_path")
Error in parquet : analysis error - path file:/... already exists.;
```
## How was this patch tested?

Unit tests in `test_utils.R` and `test_sparkSQL.R`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15608 from HyukjinKwon/SPARK-17838.

This reverts commit 5441a626.

## What changes were proposed in this pull request?

Simplify struct creation, especially the aspect of `CleanupAliases` which missed some aliases when handling trees created by `CreateStruct`.

This PR includes:

1. A failing test (create struct with nested aliases, some of the aliases survive `CleanupAliases`).
2. A fix that transforms `CreateStruct` into a `CreateNamedStruct` constructor, effectively eliminating `CreateStruct` from all expression trees.
3. A `NamePlaceHolder` used by `CreateStruct` when column names cannot be extracted from unresolved `NamedExpression`.
4. A new Analyzer rule that resolves `NamePlaceHolder` into a string literal once the `NamedExpression` is resolved.
5. `CleanupAliases` code was simplified as it no longer has to deal with `CreateStruct`'s top level columns.

## How was this patch tested?

running all tests-suits in package org.apache.spark.sql, especially including the analysis suite, making sure added test initially fails, after applying suggested fix rerun the entire analysis package successfully.

modified few tests that expected `CreateStruct` which is now transformed into `CreateNamedStruct`.

Credit goes to hvanhovell for assisting with this PR.

Author: eyal farago <eyal farago>
Author: eyal farago <eyal.farago@gmail.com>
Author: Herman van Hovell <hvanhovell@databricks.com>
Author: Eyal Farago <eyal.farago@actimize.com>
Author: Hyukjin Kwon <gurwls223@gmail.com>
Author: eyalfa <eyal.farago@gmail.com>

Closes #14444 from eyalfa/SPARK-16839_redundant_aliases_after_cleanupAliases.

## What changes were proposed in this pull request?

Random Forest Regression and Classification for R
Clean-up/reordering generics.R

## How was this patch tested?

manual tests, unit tests

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15607 from felixcheung/rrandomforest.

## What changes were proposed in this pull request?

This patch makes RBackend connection timeout configurable by user.

## How was this patch tested?
N/A

Author: Hossein <hossein@databricks.com>

Closes #15471 from falaki/SPARK-17919.

## What changes were proposed in this pull request?

API and programming guide doc changes for Scala, Python and R.

## How was this patch tested?

manual test

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15629 from felixcheung/jsondoc.

## What changes were proposed in this pull request?

a couple of small late finding fixes for doc

## How was this patch tested?

manually
wangmiao1981

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15650 from felixcheung/logitfix.

## What changes were proposed in this pull request?

As we discussed in #14818, I added a separate R wrapper spark.logit for logistic regression.

This single interface supports both binary and multinomial logistic regression. It also has "predict" and "summary" for binary logistic regression.

## How was this patch tested?

New unit tests are added.

Author: wm624@hotmail.com <wm624@hotmail.com>

Closes #15365 from wangmiao1981/glm.

## What changes were proposed in this pull request?

Add storageLevel to DataFrame for SparkR.
This is similar to this RP:  https://github.com/apache/spark/pull/13780

but in R I do not make a class for `StorageLevel`
but add a method `storageToString`

## How was this patch tested?

test added.

Author: WeichenXu <WeichenXu123@outlook.com>

Closes #15516 from WeichenXu123/storageLevel_df_r.

## What changes were proposed in this pull request?

update SparkR MLP, add initalWeights parameter.

## How was this patch tested?

test added.

Author: WeichenXu <WeichenXu123@outlook.com>

Closes #15552 from WeichenXu123/mlp_r_add_initialWeight_param.

## What changes were proposed in this pull request?

Fixes for R doc

## How was this patch tested?

N/A

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15589 from felixcheung/rdocmergefix.

(cherry picked from commit 0e0d83a5)
Signed-off-by: Felix Cheung <felixcheung@apache.org>

## What changes were proposed in this pull request?
NA date values are serialized as "NA" and NA time values are serialized as NaN from R. In the backend we did not have proper logic to deal with them. As a result we got an IllegalArgumentException for Date and wrong value for time. This PR adds support for deserializing NA as Date and Time.

## How was this patch tested?
* [x] TODO

Author: Hossein <hossein@databricks.com>

Closes #15421 from falaki/SPARK-17811.

## What changes were proposed in this pull request?

Add crossJoin and do not default to cross join if joinExpr is left out

## How was this patch tested?

unit test

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15559 from felixcheung/rcrossjoin.

## What changes were proposed in this pull request?

testthat library we are using for testing R is redirecting warning (and disabling `options("warn" = 2)`), we need to have a way to detect any new warning and fail

## How was this patch tested?

manual testing, Jenkins

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15576 from felixcheung/rtestwarning.

## What changes were proposed in this pull request?

Fix for a bunch of test warnings that were added recently.
We need to investigate why warnings are not turning into errors.

```
Warnings -----------------------------------------------------------------------
1. createDataFrame uses files for large objects (test_sparkSQL.R#215) - Use Sepal_Length instead of Sepal.Length  as column name

2. createDataFrame uses files for large objects (test_sparkSQL.R#215) - Use Sepal_Width instead of Sepal.Width  as column name

3. createDataFrame uses files for large objects (test_sparkSQL.R#215) - Use Petal_Length instead of Petal.Length  as column name

4. createDataFrame uses files for large objects (test_sparkSQL.R#215) - Use Petal_Width instead of Petal.Width  as column name

Consider adding
  importFrom("utils", "object.size")
to your NAMESPACE file.
```

## How was this patch tested?

unit tests

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15560 from felixcheung/rwarnings.

## What changes were proposed in this pull request?
If the R data structure that is being parallelized is larger than `INT_MAX` we use files to transfer data to JVM. The serialization protocol mimics Python pickling. This allows us to simply call `PythonRDD.readRDDFromFile` to create the RDD.

I tested this on my MacBook. Following code works with this patch:
```R
intMax <- .Machine$integer.max
largeVec <- 1:intMax
rdd <- SparkR:::parallelize(sc, largeVec, 2)
```

## How was this patch tested?
* [x] Unit tests

Author: Hossein <hossein@databricks.com>

Closes #15375 from falaki/SPARK-17790.

## What changes were proposed in this pull request?

SQLConf is session-scoped and mutable. However, we do have the requirement for a static SQL conf, which is global and immutable, e.g. the `schemaStringThreshold` in `HiveExternalCatalog`, the flag to enable/disable hive support, the global temp view database in https://github.com/apache/spark/pull/14897.

Actually we've already implemented static SQL conf implicitly via `SparkConf`, this PR just make it explicit and expose it to users, so that they can see the config value via SQL command or `SparkSession.conf`, and forbid users to set/unset static SQL conf.

## How was this patch tested?

new tests in SQLConfSuite

Author: Wenchen Fan <wenchen@databricks.com>

Closes #15295 from cloud-fan/global-conf.

## What changes were proposed in this pull request?
Fix SparkR ```spark.naiveBayes``` error when response variable of dataset is numeric type.
See details and how to reproduce this bug at [SPARK-15153](https://issues.apache.org/jira/browse/SPARK-15153).

## How was this patch tested?
Add unit test.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #15431 from yanboliang/spark-15153-2.

## What changes were proposed in this pull request?

This PR includes the changes below:

  - Support `mode`/`options` in `read.parquet`, `write.parquet`, `read.orc`, `write.orc`, `read.text`, `write.text`, `read.json` and `write.json` APIs

  - Support other types (logical, numeric and string) as options for `write.df`, `read.df`, `read.parquet`, `write.parquet`, `read.orc`, `write.orc`, `read.text`, `write.text`, `read.json` and `write.json`

## How was this patch tested?

Unit tests in `test_sparkSQL.R`/ `utils.R`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15239 from HyukjinKwon/SPARK-17665.

## What changes were proposed in this pull request?

`write.df`/`read.df` API require path which is not actually always necessary in Spark. Currently, it only affects the datasources implementing `CreatableRelationProvider`. Currently, Spark currently does not have internal data sources implementing this but it'd affect other external datasources.

In addition we'd be able to use this way in Spark's JDBC datasource after https://github.com/apache/spark/pull/12601 is merged.

**Before**

 - `read.df`

  ```r
> read.df(source = "json")
Error in dispatchFunc("read.df(path = NULL, source = NULL, schema = NULL, ...)",  :
  argument "x" is missing with no default
```

  ```r
> read.df(path = c(1, 2))
Error in dispatchFunc("read.df(path = NULL, source = NULL, schema = NULL, ...)",  :
  argument "x" is missing with no default
```

  ```r
> read.df(c(1, 2))
Error in invokeJava(isStatic = TRUE, className, methodName, ...) :
  java.lang.ClassCastException: java.lang.Double cannot be cast to java.lang.String
	at org.apache.spark.sql.execution.datasources.DataSource.hasMetadata(DataSource.scala:300)
	at
...
In if (is.na(object)) { :
...
```

 - `write.df`

  ```r
> write.df(df, source = "json")
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘write.df’ for signature ‘"function", "missing"’
```

  ```r
> write.df(df, source = c(1, 2))
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘write.df’ for signature ‘"SparkDataFrame", "missing"’
```

  ```r
> write.df(df, mode = TRUE)
Error in (function (classes, fdef, mtable)  :
  unable to find an inherited method for function ‘write.df’ for signature ‘"SparkDataFrame", "missing"’
```

**After**

- `read.df`

  ```r
> read.df(source = "json")
Error in loadDF : analysis error - Unable to infer schema for JSON at . It must be specified manually;
```

  ```r
> read.df(path = c(1, 2))
Error in f(x, ...) : path should be charactor, null or omitted.
```

  ```r
> read.df(c(1, 2))
Error in f(x, ...) : path should be charactor, null or omitted.
```

- `write.df`

  ```r
> write.df(df, source = "json")
Error in save : illegal argument - 'path' is not specified
```

  ```r
> write.df(df, source = c(1, 2))
Error in .local(df, path, ...) :
  source should be charactor, null or omitted. It is 'parquet' by default.
```

  ```r
> write.df(df, mode = TRUE)
Error in .local(df, path, ...) :
  mode should be charactor or omitted. It is 'error' by default.
```

## How was this patch tested?

Unit tests in `test_sparkSQL.R`

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15231 from HyukjinKwon/write-default-r.

## What changes were proposed in this pull request?

Clean up output, format table, truncate long example output, hide warnings

(new - Left; existing - Right)
![image](https://cloud.githubusercontent.com/assets/8969467/19064018/5dcde4d0-89bc-11e6-857b-052df3f52a4e.png)

![image](https://cloud.githubusercontent.com/assets/8969467/19064034/6db09956-89bc-11e6-8e43-232d5c3fe5e6.png)

![image](https://cloud.githubusercontent.com/assets/8969467/19064058/88f09590-89bc-11e6-9993-61639e29dfdd.png)

![image](https://cloud.githubusercontent.com/assets/8969467/19064066/95ccbf64-89bc-11e6-877f-45af03ddcadc.png)

![image](https://cloud.githubusercontent.com/assets/8969467/19064082/a8445404-89bc-11e6-8532-26d8bc9b206f.png)

## How was this patch tested?

Run create-doc.sh manually

Author: Felix Cheung <felixcheung_m@hotmail.com>

Closes #15340 from felixcheung/vignettes.