## What changes were proposed in this pull request?
In previous work SPARK-21513, we has allowed `MapType` and `ArrayType` of `MapType`s convert to a json string but only for Scala API. In this follow-up PR, we will make SparkSQL support it for PySpark and SparkR, too. We also fix some little bugs and comments of the previous work in this follow-up PR.
### For PySpark
```
>>> data = [(1, {"name": "Alice"})]
>>> df = spark.createDataFrame(data, ("key", "value"))
>>> df.select(to_json(df.value).alias("json")).collect()
[Row(json=u'{"name":"Alice")']
>>> data = [(1, [{"name": "Alice"}, {"name": "Bob"}])]
>>> df = spark.createDataFrame(data, ("key", "value"))
>>> df.select(to_json(df.value).alias("json")).collect()
[Row(json=u'[{"name":"Alice"},{"name":"Bob"}]')]
```
### For SparkR
```
# Converts a map into a JSON object
df2 <- sql("SELECT map('name', 'Bob')) as people")
df2 <- mutate(df2, people_json = to_json(df2$people))
# Converts an array of maps into a JSON array
df2 <- sql("SELECT array(map('name', 'Bob'), map('name', 'Alice')) as people")
df2 <- mutate(df2, people_json = to_json(df2$people))
```
## How was this patch tested?
Add unit test cases.
cc viirya HyukjinKwon
Author: goldmedal <liugs963@gmail.com>
Closes#19223 from goldmedal/SPARK-21513-fp-PySaprkAndSparkR.
## What changes were proposed in this pull request?
This PR proposes to add a wrapper for `unionByName` API to R and Python as well.
**Python**
```python
df1 = spark.createDataFrame([[1, 2, 3]], ["col0", "col1", "col2"])
df2 = spark.createDataFrame([[4, 5, 6]], ["col1", "col2", "col0"])
df1.unionByName(df2).show()
```
```
+----+----+----+
|col0|col1|col3|
+----+----+----+
| 1| 2| 3|
| 6| 4| 5|
+----+----+----+
```
**R**
```R
df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
head(unionByName(limit(df1, 2), limit(df2, 2)))
```
```
carb am gear
1 4 1 4
2 4 1 4
3 4 1 4
4 4 1 4
```
## How was this patch tested?
Doctests for Python and unit test added in `test_sparkSQL.R` for R.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#19105 from HyukjinKwon/unionByName-r-python.
## What changes were proposed in this pull request?
fix the random seed to eliminate variability
## How was this patch tested?
jenkins, appveyor, lots more jenkins
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#19018 from felixcheung/rrftest.
## What changes were proposed in this pull request?
SPARK-21100 introduced a new `summary` method to the Scala/Java Dataset API that included expanded statistics (vs `describe`) and control over which statistics to compute. Currently in the R API `summary` acts as an alias for `describe`. This patch updates the R API to call the new `summary` method in the JVM that includes additional statistics and ability to select which to compute.
This does not break the current interface as the present `summary` method does not take additional arguments like `describe` and the output was never meant to be used programmatically.
## How was this patch tested?
Modified and additional unit tests.
Author: Andrew Ray <ray.andrew@gmail.com>
Closes#18786 from aray/summary-r.
## What changes were proposed in this pull request?
Support offset in SparkR GLM #16699
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18831 from actuaryzhang/sparkROffset.
## What changes were proposed in this pull request?
SPARK-20307 Added handleInvalid option to RFormula for tree-based classification algorithms. We should add this parameter for other classification algorithms in SparkR.
This is a followup PR for SPARK-20307.
## How was this patch tested?
New Unit tests are added.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#18605 from wangmiao1981/class.
## What changes were proposed in this pull request?
```RFormula``` should handle invalid for both features and label column.
#18496 only handle invalid values in features column. This PR add handling invalid values for label column and test cases.
## How was this patch tested?
Add test cases.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#18613 from yanboliang/spark-20307.
## What changes were proposed in this pull request?
- Remove Scala 2.10 build profiles and support
- Replace some 2.10 support in scripts with commented placeholders for 2.12 later
- Remove deprecated API calls from 2.10 support
- Remove usages of deprecated context bounds where possible
- Remove Scala 2.10 workarounds like ScalaReflectionLock
- Other minor Scala warning fixes
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#17150 from srowen/SPARK-19810.
## What changes were proposed in this pull request?
This PR supports schema in a DDL formatted string for `from_json` in R/Python and `dapply` and `gapply` in R, which are commonly used and/or consistent with Scala APIs.
Additionally, this PR exposes `structType` in R to allow working around in other possible corner cases.
**Python**
`from_json`
```python
from pyspark.sql.functions import from_json
data = [(1, '''{"a": 1}''')]
df = spark.createDataFrame(data, ("key", "value"))
df.select(from_json(df.value, "a INT").alias("json")).show()
```
**R**
`from_json`
```R
df <- sql("SELECT named_struct('name', 'Bob') as people")
df <- mutate(df, people_json = to_json(df$people))
head(select(df, from_json(df$people_json, "name STRING")))
```
`structType.character`
```R
structType("a STRING, b INT")
```
`dapply`
```R
dapply(createDataFrame(list(list(1.0)), "a"), function(x) {x}, "a DOUBLE")
```
`gapply`
```R
gapply(createDataFrame(list(list(1.0)), "a"), "a", function(key, x) { x }, "a DOUBLE")
```
## How was this patch tested?
Doc tests for `from_json` in Python and unit tests `test_sparkSQL.R` in R.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18498 from HyukjinKwon/SPARK-21266.
## What changes were proposed in this pull request?
For randomForest classifier, if test data contains unseen labels, it will throw an error. The StringIndexer already has the handleInvalid logic. The patch add a new method to set the underlying StringIndexer handleInvalid logic.
This patch should also apply to other classifiers. This PR focuses on the main logic and randomForest classifier. I will do follow-up PR for other classifiers.
## How was this patch tested?
Add a new unit test based on the error case in the JIRA.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#18496 from wangmiao1981/handle.
## What changes were proposed in this pull request?
This PR proposes to support a DDL-formetted string as schema as below:
```r
mockLines <- c("{\"name\":\"Michael\"}",
"{\"name\":\"Andy\", \"age\":30}",
"{\"name\":\"Justin\", \"age\":19}")
jsonPath <- tempfile(pattern = "sparkr-test", fileext = ".tmp")
writeLines(mockLines, jsonPath)
df <- read.df(jsonPath, "json", "name STRING, age DOUBLE")
collect(df)
```
## How was this patch tested?
Tests added in `test_streaming.R` and `test_sparkSQL.R` and manual tests.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18431 from HyukjinKwon/r-ddl-schema.
## What changes were proposed in this pull request?
Extend `setJobDescription` to SparkR API.
## How was this patch tested?
It looks difficult to add a test. Manually tested as below:
```r
df <- createDataFrame(iris)
count(df)
setJobDescription("This is an example job.")
count(df)
```
prints ...
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#18382 from HyukjinKwon/SPARK-21149.
## What changes were proposed in this pull request?
PR https://github.com/apache/spark/pull/17715 Added Constrained Logistic Regression for ML. We should add it to SparkR.
## How was this patch tested?
Add new unit tests.
Author: wangmiao1981 <wm624@hotmail.com>
Closes#18128 from wangmiao1981/test.
## What changes were proposed in this pull request?
Add `stringIndexerOrderType` to `spark.glm` and `spark.survreg` to support string encoding that is consistent with default R.
## How was this patch tested?
new tests
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18140 from actuaryzhang/sparkRFormula.
## What changes were proposed in this pull request?
Add SQL trunc function
## How was this patch tested?
standard test
Author: actuaryzhang <actuaryzhang10@gmail.com>
Closes#18291 from actuaryzhang/sparkRTrunc2.
## What changes were proposed in this pull request?
clean up after big test move
## How was this patch tested?
unit tests, jenkins
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#18267 from felixcheung/rtestset2.
## What changes were proposed in this pull request?
Move all existing tests to non-installed directory so that it will never run by installing SparkR package
For a follow-up PR:
- remove all skip_on_cran() calls in tests
- clean up test timer
- improve or change basic tests that do run on CRAN (if anyone has suggestion)
It looks like `R CMD build pkg` will still put pkg\tests (ie. the full tests) into the source package but `R CMD INSTALL` on such source package does not install these tests (and so `R CMD check` does not run them)
## How was this patch tested?
- [x] unit tests, Jenkins
- [x] AppVeyor
- [x] make a source package, install it, `R CMD check` it - verify the full tests are not installed or run
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#18264 from felixcheung/rtestset.
