## What changes were proposed in this pull request?
Implement repartitionByColumn on DataFrame.
This will allow us to run R functions on each partition identified by column groups with dapply() method.
## How was this patch tested?
Unit tests
Author: NarineK <narine.kokhlikyan@us.ibm.com>
Closes#12887 from NarineK/repartitionByColumns.
## What changes were proposed in this pull request?
Fix warnings and a failure in SparkR test cases with testthat version 1.0.1
## How was this patch tested?
SparkR unit test cases.
Author: Sun Rui <sunrui2016@gmail.com>
Closes#12867 from sun-rui/SPARK-15091.
## What changes were proposed in this pull request?
* ```RFormula``` supports empty response variable like ```~ x + y```.
* Support formula in ```spark.kmeans``` in SparkR.
* Fix some outdated docs for SparkR.
## How was this patch tested?
Unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12813 from yanboliang/spark-15030.
## What changes were proposed in this pull request?
Continue the work of #12789 to rename ml.asve/ml.load to write.ml/read.ml, which are more consistent with read.df/write.df and other methods in SparkR.
I didn't rename `data` to `df` because we still use `predict` for prediction, which uses `newData` to match the signature in R.
## How was this patch tested?
Existing unit tests.
cc: yanboliang thunterdb
Author: Xiangrui Meng <meng@databricks.com>
Closes#12807 from mengxr/SPARK-14831.
## What changes were proposed in this pull request?
This PR splits the MLlib algorithms into two flavors:
- the R flavor, which tries to mimic the existing R API for these algorithms (and works as an S4 specialization for Spark dataframes)
- the Spark flavor, which follows the same API and naming conventions as the rest of the MLlib algorithms in the other languages
In practice, the former calls the latter.
## How was this patch tested?
The tests for the various algorithms were adapted to be run against both interfaces.
Author: Timothy Hunter <timhunter@databricks.com>
Closes#12789 from thunterdb/14831.
## What changes were proposed in this pull request?
dapply() applies an R function on each partition of a DataFrame and returns a new DataFrame.
The function signature is:
dapply(df, function(localDF) {}, schema = NULL)
R function input: local data.frame from the partition on local node
R function output: local data.frame
Schema specifies the Row format of the resulting DataFrame. It must match the R function's output.
If schema is not specified, each partition of the result DataFrame will be serialized in R into a single byte array. Such resulting DataFrame can be processed by successive calls to dapply().
## How was this patch tested?
SparkR unit tests.
Author: Sun Rui <rui.sun@intel.com>
Author: Sun Rui <sunrui2016@gmail.com>
Closes#12493 from sun-rui/SPARK-12919.
SparkR ```glm``` and ```kmeans``` model persistence.
Unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Author: Gayathri Murali <gayathri.m.softie@gmail.com>
Closes#12778 from yanboliang/spark-14311.
Closes#12680Closes#12683
## What changes were proposed in this pull request?
This PR adds a new function in SparkR called `sparkLapply(list, function)`. This function implements a distributed version of `lapply` using Spark as a backend.
TODO:
- [x] check documentation
- [ ] check tests
Trivial example in SparkR:
```R
sparkLapply(1:5, function(x) { 2 * x })
```
Output:
```
[[1]]
[1] 2
[[2]]
[1] 4
[[3]]
[1] 6
[[4]]
[1] 8
[[5]]
[1] 10
```
Here is a slightly more complex example to perform distributed training of multiple models. Under the hood, Spark broadcasts the dataset.
```R
library("MASS")
data(menarche)
families <- c("gaussian", "poisson")
train <- function(family){glm(Menarche ~ Age , family=family, data=menarche)}
results <- sparkLapply(families, train)
```
## How was this patch tested?
This PR was tested in SparkR. I am unfamiliar with R and SparkR, so any feedback on style, testing, etc. will be much appreciated.
cc falaki davies
Author: Timothy Hunter <timhunter@databricks.com>
Closes#12426 from thunterdb/7264.
Make the behavior of mutate more consistent with that in dplyr, besides support for replacing existing columns.
1. Throw error message when there are duplicated column names in the DataFrame being mutated.
2. when there are duplicated column names in specified columns by arguments, the last column of the same name takes effect.
Author: Sun Rui <rui.sun@intel.com>
Closes#10220 from sun-rui/SPARK-12235.
Added parameter drop to subsetting operator [. This is useful to get a Column from a DataFrame, given its name. R supports it.
In R:
```
> name <- "Sepal_Length"
> class(iris[, name])
[1] "numeric"
```
Currently, in SparkR:
```
> name <- "Sepal_Length"
> class(irisDF[, name])
[1] "DataFrame"
```
Previous code returns a DataFrame, which is inconsistent with R's behavior. SparkR should return a Column instead. Currently, in order for the user to return a Column given a column name as a character variable would be through `eval(parse(x))`, where x is the string `"irisDF$Sepal_Length"`. That itself is pretty hacky. `SparkR:::getColumn() `is another choice, but I don't see why this method should be externalized. Instead, following R's way to do things, the proposed implementation allows this:
```
> name <- "Sepal_Length"
> class(irisDF[, name, drop=T])
[1] "Column"
> class(irisDF[, name, drop=F])
[1] "DataFrame"
```
This is consistent with R:
```
> name <- "Sepal_Length"
> class(iris[, name])
[1] "numeric"
> class(iris[, name, drop=F])
[1] "data.frame"
```
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com>
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.attlocal.net>
Closes#11318 from olarayej/SPARK-13436.
## What changes were proposed in this pull request?
Added method histogram() to compute the histogram of a Column
Usage:
```
## Create a DataFrame from the Iris dataset
irisDF <- createDataFrame(sqlContext, iris)
## Render a histogram for the Sepal_Length column
histogram(irisDF, "Sepal_Length", nbins=12)
```
Note: Usage will change once SPARK-9325 is figured out so that histogram() only takes a Column as a parameter, as opposed to a DataFrame and a name
## How was this patch tested?
All unit tests pass. I added specific unit cases for different scenarios.
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com>
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.attlocal.net>
Closes#11569 from olarayej/SPARK-13734.
## What changes were proposed in this pull request?
```AFTSurvivalRegressionModel``` supports ```save/load``` in SparkR.
## How was this patch tested?
Unit tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12685 from yanboliang/spark-14313.
## What changes were proposed in this pull request?
SparkR ```NaiveBayesModel``` supports ```save/load``` by the following API:
```
df <- createDataFrame(sqlContext, infert)
model <- naiveBayes(education ~ ., df, laplace = 0)
ml.save(model, path)
model2 <- ml.load(path)
```
## How was this patch tested?
Add unit tests.
cc mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12573 from yanboliang/spark-14312.
## What changes were proposed in this pull request?
In order to support running SQL directly on files, we added some code in ResolveRelations to catch the exception thrown by catalog.lookupRelation and ignore it. This unfortunately masks all the exceptions. This patch changes the logic to simply test the table's existence.
## How was this patch tested?
I manually hacked some bugs into Spark and made sure the exceptions were being propagated up.
Author: Reynold Xin <rxin@databricks.com>
Closes#12634 from rxin/SPARK-14869.
## What changes were proposed in this pull request?
Changed class name defined in R from "DataFrame" to "SparkDataFrame". A popular package, S4Vector already defines "DataFrame" - this change is to avoid conflict.
Aside from class name and API/roxygen2 references, SparkR APIs like `createDataFrame`, `as.DataFrame` are not changed (S4Vector does not define a "as.DataFrame").
Since in R, one would rarely reference type/class, this change should have minimal/almost-no impact to a SparkR user in terms of back compat.
## How was this patch tested?
SparkR tests, manually loading S4Vector then SparkR package
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#12621 from felixcheung/rdataframe.
## What changes were proposed in this pull request?
The concurrency issue reported in SPARK-13178 was fixed by the PR https://github.com/apache/spark/pull/10947 for SPARK-12792.
This PR just removes a workaround not needed anymore.
## How was this patch tested?
SparkR unit tests.
Author: Sun Rui <rui.sun@intel.com>
Closes#12606 from sun-rui/SPARK-13178.
## What changes were proposed in this pull request?
This PR aims to add `setLogLevel` function to SparkR shell.
**Spark Shell**
```scala
scala> sc.setLogLevel("ERROR")
```
**PySpark**
```python
>>> sc.setLogLevel("ERROR")
```
**SparkR (this PR)**
```r
> setLogLevel(sc, "ERROR")
NULL
```
## How was this patch tested?
Pass the Jenkins tests including a new R testcase.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12547 from dongjoon-hyun/SPARK-14780.
## What changes were proposed in this pull request?
This issue aims to expose Scala `bround` function in Python/R API.
`bround` function is implemented in SPARK-14614 by extending current `round` function.
We used the following semantics from Hive.
```java
public static double bround(double input, int scale) {
if (Double.isNaN(input) || Double.isInfinite(input)) {
return input;
}
return BigDecimal.valueOf(input).setScale(scale, RoundingMode.HALF_EVEN).doubleValue();
}
```
After this PR, `pyspark` and `sparkR` also support `bround` function.
**PySpark**
```python
>>> from pyspark.sql.functions import bround
>>> sqlContext.createDataFrame([(2.5,)], ['a']).select(bround('a', 0).alias('r')).collect()
[Row(r=2.0)]
```
**SparkR**
```r
> df = createDataFrame(sqlContext, data.frame(x = c(2.5, 3.5)))
> head(collect(select(df, bround(df$x, 0))))
bround(x, 0)
1 2
2 4
```
## How was this patch tested?
Pass the Jenkins tests (including new testcases).
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12509 from dongjoon-hyun/SPARK-14639.
## What changes were proposed in this pull request?
Change the signature of as.data.frame() to be consistent with that in the R base package to meet R user's convention.
## How was this patch tested?
dev/lint-r
SparkR unit tests
Author: Sun Rui <rui.sun@intel.com>
Closes#11811 from sun-rui/SPARK-13905.
Add R API for `read.jdbc`, `write.jdbc`.
Tested this quite a bit manually with different combinations of parameters. It's not clear if we could have automated tests in R for this - Scala `JDBCSuite` depends on Java H2 in-memory database.
Refactored some code into util so they could be tested.
Core's R SerDe code needs to be updated to allow access to java.util.Properties as `jobj` handle which is required by DataFrameReader/Writer's `jdbc` method. It would be possible, though more code to add a `sql/r/SQLUtils` helper function.
Tested:
```
# with postgresql
../bin/sparkR --driver-class-path /usr/share/java/postgresql-9.4.1207.jre7.jar
# read.jdbc
df <- read.jdbc(sqlContext, "jdbc:postgresql://localhost/db", "films2", user = "user", password = "12345")
df <- read.jdbc(sqlContext, "jdbc:postgresql://localhost/db", "films2", user = "user", password = 12345)
# partitionColumn and numPartitions test
df <- read.jdbc(sqlContext, "jdbc:postgresql://localhost/db", "films2", partitionColumn = "did", lowerBound = 0, upperBound = 200, numPartitions = 4, user = "user", password = 12345)
a <- SparkR:::toRDD(df)
SparkR:::getNumPartitions(a)
[1] 4
SparkR:::collectPartition(a, 2L)
# defaultParallelism test
df <- read.jdbc(sqlContext, "jdbc:postgresql://localhost/db", "films2", partitionColumn = "did", lowerBound = 0, upperBound = 200, user = "user", password = 12345)
SparkR:::getNumPartitions(a)
[1] 2
# predicates test
df <- read.jdbc(sqlContext, "jdbc:postgresql://localhost/db", "films2", predicates = list("did<=105"), user = "user", password = 12345)
count(df) == 1
# write.jdbc, default save mode "error"
irisDf <- as.DataFrame(sqlContext, iris)
write.jdbc(irisDf, "jdbc:postgresql://localhost/db", "films2", user = "user", password = "12345")
"error, already exists"
write.jdbc(irisDf, "jdbc:postgresql://localhost/db", "iris", user = "user", password = "12345")
```
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#10480 from felixcheung/rreadjdbc.
## What changes were proposed in this pull request?
Expose R-like summary statistics in SparkR::glm for more family and link functions.
Note: Not all values in R [summary.glm](http://stat.ethz.ch/R-manual/R-patched/library/stats/html/summary.glm.html) are exposed, we only provide the most commonly used statistics in this PR. More statistics can be added in the followup work.
## How was this patch tested?
Unit tests.
SparkR Output:
```
Deviance Residuals:
(Note: These are approximate quantiles with relative error <= 0.01)
Min 1Q Median 3Q Max
-0.95096 -0.16585 -0.00232 0.17410 0.72918
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.6765 0.23536 7.1231 4.4561e-11
Sepal_Length 0.34988 0.046301 7.5566 4.1873e-12
Species_versicolor -0.98339 0.072075 -13.644 0
Species_virginica -1.0075 0.093306 -10.798 0
(Dispersion parameter for gaussian family taken to be 0.08351462)
Null deviance: 28.307 on 149 degrees of freedom
Residual deviance: 12.193 on 146 degrees of freedom
AIC: 59.22
Number of Fisher Scoring iterations: 1
```
R output:
```
Deviance Residuals:
Min 1Q Median 3Q Max
-0.95096 -0.16522 0.00171 0.18416 0.72918
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.67650 0.23536 7.123 4.46e-11 ***
Sepal.Length 0.34988 0.04630 7.557 4.19e-12 ***
Speciesversicolor -0.98339 0.07207 -13.644 < 2e-16 ***
Speciesvirginica -1.00751 0.09331 -10.798 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for gaussian family taken to be 0.08351462)
Null deviance: 28.307 on 149 degrees of freedom
Residual deviance: 12.193 on 146 degrees of freedom
AIC: 59.217
Number of Fisher Scoring iterations: 2
```
cc mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12393 from yanboliang/spark-13925.
* SparkR glm supports families and link functions which match R's signature for family.
* SparkR glm API refactor. The comparative standard of the new API is R glm, so I only expose the arguments that R glm supports: ```formula, family, data, epsilon and maxit```.
* This PR is focus on glm() and predict(), summary statistics will be done in a separate PR after this get in.
* This PR depends on #12287 which make GLMs support link prediction at Scala side. After that merged, I will add more tests for predict() to this PR.
Unit tests.
cc mengxr jkbradley hhbyyh
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#12294 from yanboliang/spark-12566.
#### What changes were proposed in this pull request?
This PR is to address the comment: https://github.com/apache/spark/pull/12146#discussion-diff-59092238. It removes the function `isViewSupported` from `SessionCatalog`. After the removal, we still can capture the user errors if users try to drop a table using `DROP VIEW`.
#### How was this patch tested?
Modified the existing test cases
Author: gatorsmile <gatorsmile@gmail.com>
Closes#12284 from gatorsmile/followupDropTable.
## What changes were proposed in this pull request?
The `window` function was added to Dataset with [this PR](https://github.com/apache/spark/pull/12008).
This PR adds the R API for this function.
With this PR, SQL, Java, and Scala will share the same APIs as in users can use:
- `window(timeColumn, windowDuration)`
- `window(timeColumn, windowDuration, slideDuration)`
- `window(timeColumn, windowDuration, slideDuration, startTime)`
In Python and R, users can access all APIs above, but in addition they can do
- In R:
`window(timeColumn, windowDuration, startTime=...)`
that is, they can provide the startTime without providing the `slideDuration`. In this case, we will generate tumbling windows.
## How was this patch tested?
Unit tests + manual tests
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#12141 from brkyvz/R-windows.
## What changes were proposed in this pull request?
Refactor RRDD by separating the common logic interacting with the R worker to a new class RRunner, which can be used to evaluate R UDFs.
Now RRDD relies on RRuner for RDD computation and RRDD could be reomved if we want to remove RDD API in SparkR later.
## How was this patch tested?
dev/lint-r
SparkR unit tests
Author: Sun Rui <rui.sun@intel.com>
Closes#12024 from sun-rui/SPARK-12792_new.
Refactor RRDD by separating the common logic interacting with the R worker to a new class RRunner, which can be used to evaluate R UDFs.
Now RRDD relies on RRuner for RDD computation and RRDD could be reomved if we want to remove RDD API in SparkR later.
Author: Sun Rui <rui.sun@intel.com>
Closes#10947 from sun-rui/SPARK-12792.
## What changes were proposed in this pull request?
This reopens#11836, which was merged but promptly reverted because it introduced flaky Hive tests.
## How was this patch tested?
See `CatalogTestCases`, `SessionCatalogSuite` and `HiveContextSuite`.
Author: Andrew Or <andrew@databricks.com>
Closes#11938 from andrewor14/session-catalog-again.
## What changes were proposed in this pull request?
This PR continues the work in #11447, we implemented the wrapper of ```AFTSurvivalRegression``` named ```survreg``` in SparkR.
## How was this patch tested?
Test against output from R package survival's survreg.
cc mengxr felixcheung
Close#11447
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#11932 from yanboliang/spark-13010-new.
## What changes were proposed in this pull request?
`SessionCatalog`, introduced in #11750, is a catalog that keeps track of temporary functions and tables, and delegates metastore operations to `ExternalCatalog`. This functionality overlaps a lot with the existing `analysis.Catalog`.
As of this commit, `SessionCatalog` and `ExternalCatalog` will no longer be dead code. There are still things that need to be done after this patch, namely:
- SPARK-14013: Properly implement temporary functions in `SessionCatalog`
- SPARK-13879: Decide which DDL/DML commands to support natively in Spark
- SPARK-?????: Implement the ones we do want to support through `SessionCatalog`.
- SPARK-?????: Merge SQL/HiveContext
## How was this patch tested?
This is largely a refactoring task so there are no new tests introduced. The particularly relevant tests are `SessionCatalogSuite` and `ExternalCatalogSuite`.
Author: Andrew Or <andrew@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Closes#11836 from andrewor14/use-session-catalog.
## What changes were proposed in this pull request?
This PR continues the work in #11486 from yinxusen with some code refactoring. In R package e1071, `naiveBayes` supports both categorical (Bernoulli) and continuous features (Gaussian), while in MLlib we support Bernoulli and multinomial. This PR implements the common subset: Bernoulli.
I moved the implementation out from SparkRWrappers to NaiveBayesWrapper to make it easier to read. Argument names, default values, and summary now match e1071's naiveBayes.
I removed the preprocess part that omit NA values because we don't know which columns to process.
## How was this patch tested?
Test against output from R package e1071's naiveBayes.
cc: yanboliang yinxusen
Closes#11486
Author: Xusen Yin <yinxusen@gmail.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#11890 from mengxr/SPARK-13449.
## What changes were proposed in this pull request?
This PR fixes all newly captured SparkR lint-r errors after the lintr package is updated from github.
## How was this patch tested?
dev/lint-r
SparkR unit tests
Author: Sun Rui <rui.sun@intel.com>
Closes#11652 from sun-rui/SPARK-13812.
## What changes were proposed in this pull request?
SparkR support first/last with ignore NAs
cc sun-rui felixcheung shivaram
## How was the this patch tested?
unit tests
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#11267 from yanboliang/spark-13389.
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.attlocal.net>
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com>
Closes#11220 from olarayej/SPARK-13312-3.
## What changes were proposed in this pull request?
Add ```approxQuantile``` for SparkR.
## How was this patch tested?
unit tests
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#11383 from yanboliang/spark-13504 and squashes the following commits:
4f17adb [Yanbo Liang] Add approxQuantile for SparkR
JIRA: https://issues.apache.org/jira/browse/SPARK-13472
## What changes were proposed in this pull request?
One Kmeans test in R is unstable and sometimes fails. We should fix it.
## How was this patch tested?
Unit test is modified in this PR.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#11345 from viirya/fix-kmeans-r-test and squashes the following commits:
f959f61 [Liang-Chi Hsieh] Sort resulted clusters.
This PR introduces several major changes:
1. Replacing `Expression.prettyString` with `Expression.sql`
The `prettyString` method is mostly an internal, developer faced facility for debugging purposes, and shouldn't be exposed to users.
1. Using SQL-like representation as column names for selected fields that are not named expression (back-ticks and double quotes should be removed)
Before, we were using `prettyString` as column names when possible, and sometimes the result column names can be weird. Here are several examples:
Expression | `prettyString` | `sql` | Note
------------------ | -------------- | ---------- | ---------------
`a && b` | `a && b` | `a AND b` |
`a.getField("f")` | `a[f]` | `a.f` | `a` is a struct
1. Adding trait `NonSQLExpression` extending from `Expression` for expressions that don't have a SQL representation (e.g. Scala UDF/UDAF and Java/Scala object expressions used for encoders)
`NonSQLExpression.sql` may return an arbitrary user facing string representation of the expression.
Author: Cheng Lian <lian@databricks.com>
Closes#10757 from liancheng/spark-12799.simplify-expression-string-methods.
Add ```covar_samp``` and ```covar_pop``` for SparkR.
Should we also provide ```cov``` alias for ```covar_samp```? There is ```cov``` implementation at stats.R which masks ```stats::cov``` already, but may bring to breaking API change.
cc sun-rui felixcheung shivaram
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10829 from yanboliang/spark-12903.
I've tried to solve some of the issues mentioned in: https://issues.apache.org/jira/browse/SPARK-12629
Please, let me know what do you think.
Thanks!
Author: Narine Kokhlikyan <narine.kokhlikyan@gmail.com>
Closes#10580 from NarineK/sparkrSavaAsRable.
The current parser turns a decimal literal, for example ```12.1```, into a Double. The problem with this approach is that we convert an exact literal into a non-exact ```Double```. The PR changes this behavior, a Decimal literal is now converted into an extact ```BigDecimal```.
The behavior for scientific decimals, for example ```12.1e01```, is unchanged. This will be converted into a Double.
This PR replaces the ```BigDecimal``` literal by a ```Double``` literal, because the ```BigDecimal``` is the default now. You can use the double literal by appending a 'D' to the value, for instance: ```3.141527D```
cc davies rxin
Author: Herman van Hovell <hvanhovell@questtec.nl>
Closes#10796 from hvanhovell/SPARK-12848.
shivaram sorry it took longer to fix some conflicts, this is the change to add an alias for `table`
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#10406 from felixcheung/readtable.
Currently this is reported when loading the SparkR package in R (probably would add is.nan)
```
Loading required package: methods
Attaching package: ‘SparkR’
The following objects are masked from ‘package:stats’:
cov, filter, lag, na.omit, predict, sd, var
The following objects are masked from ‘package:base’:
colnames, colnames<-, intersect, rank, rbind, sample, subset,
summary, table, transform
```
Adding this test adds an automated way to track changes to masked method.
Also, the second part of this test check for those functions that would not be accessible without namespace/package prefix.
Incidentally, this might point to how we would fix those inaccessible functions in base or stats.
Looking for feedback for adding this test.
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#10171 from felixcheung/rmaskedtest.
Slight correction: I'm leaving sparkR as-is (ie. R file not supported) and fixed only run-tests.sh as shivaram described.
I also assume we are going to cover all doc changes in https://issues.apache.org/jira/browse/SPARK-12846 instead of here.
rxin shivaram zjffdu
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#10792 from felixcheung/sparkRcmd.
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.usca.ibm.com>
Author: Oscar D. Lara Yejas <olarayej@mail.usf.edu>
Author: Oscar D. Lara Yejas <oscar.lara.yejas@us.ibm.com>
Author: Oscar D. Lara Yejas <odlaraye@oscars-mbp.attlocal.net>
Closes#9613 from olarayej/SPARK-11031.
This PR makes bucketing and exchange share one common hash algorithm, so that we can guarantee the data distribution is same between shuffle and bucketed data source, which enables us to only shuffle one side when join a bucketed table and a normal one.
This PR also fixes the tests that are broken by the new hash behaviour in shuffle.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#10703 from cloud-fan/use-hash-expr-in-shuffle.
Add ```read.text``` and ```write.text``` for SparkR.
cc sun-rui felixcheung shivaram
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10348 from yanboliang/spark-12393.
rxin davies shivaram
Took save mode from my PR #10480, and move everything to writer methods. This is related to PR #10559
- [x] it seems jsonRDD() is broken, need to investigate - this is not a public API though; will look into some more tonight. (fixed)
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#10584 from felixcheung/rremovedeprecated.
* Changes api.r.SQLUtils to use ```SQLContext.getOrCreate``` instead of creating a new context.
* Adds a simple test
[SPARK-11199] #comment link with JIRA
Author: Hossein <hossein@databricks.com>
Closes#9185 from falaki/SPARK-11199.
`ifelse`, `when`, `otherwise` is unable to take `Column` typed S4 object as values.
For example:
```r
ifelse(lit(1) == lit(1), lit(2), lit(3))
ifelse(df$mpg > 0, df$mpg, 0)
```
will both fail with
```r
attempt to replicate an object of type 'environment'
```
The PR replaces `ifelse` calls with `if ... else ...` inside the function implementations to avoid attempt to vectorize(i.e. `rep()`). It remains to be discussed whether we should instead support vectorization in these functions for consistency because `ifelse` in base R is vectorized but I cannot foresee any scenarios these functions will want to be vectorized in SparkR.
For reference, added test cases which trigger failures:
```r
. Error: when(), otherwise() and ifelse() with column on a DataFrame ----------
error in evaluating the argument 'x' in selecting a method for function 'collect':
error in evaluating the argument 'col' in selecting a method for function 'select':
attempt to replicate an object of type 'environment'
Calls: when -> when -> ifelse -> ifelse
1: withCallingHandlers(eval(code, new_test_environment), error = capture_calls, message = function(c) invokeRestart("muffleMessage"))
2: eval(code, new_test_environment)
3: eval(expr, envir, enclos)
4: expect_equal(collect(select(df, when(df$a > 1 & df$b > 2, lit(1))))[, 1], c(NA, 1)) at test_sparkSQL.R:1126
5: expect_that(object, equals(expected, label = expected.label, ...), info = info, label = label)
6: condition(object)
7: compare(actual, expected, ...)
8: collect(select(df, when(df$a > 1 & df$b > 2, lit(1))))
Error: Test failures
Execution halted
```
Author: Forest Fang <forest.fang@outlook.com>
Closes#10481 from saurfang/spark-12526.
Add ```write.json``` and ```write.parquet``` for SparkR, and deprecated ```saveAsParquetFile```.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10281 from yanboliang/spark-12310.
The existing sample functions miss the parameter `seed`, however, the corresponding function interface in `generics` has such a parameter. Thus, although the function caller can call the function with the 'seed', we are not using the value.
This could cause SparkR unit tests failed. For example, I hit it in another PR:
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/47213/consoleFull
Author: gatorsmile <gatorsmile@gmail.com>
Closes#10160 from gatorsmile/sampleR.
* ```jsonFile``` should support multiple input files, such as:
```R
jsonFile(sqlContext, c(“path1”, “path2”)) # character vector as arguments
jsonFile(sqlContext, “path1,path2”)
```
* Meanwhile, ```jsonFile``` has been deprecated by Spark SQL and will be removed at Spark 2.0. So we mark ```jsonFile``` deprecated and use ```read.json``` at SparkR side.
* Replace all ```jsonFile``` with ```read.json``` at test_sparkSQL.R, but still keep jsonFile test case.
* If this PR is accepted, we should also make almost the same change for ```parquetFile```.
cc felixcheung sun-rui shivaram
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10145 from yanboliang/spark-12146.
Fix ```subset``` function error when only set ```select``` argument. Please refer to the [JIRA](https://issues.apache.org/jira/browse/SPARK-12234) about the error and how to reproduce it.
cc sun-rui felixcheung shivaram
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10217 from yanboliang/spark-12234.
SparkR support ```read.parquet``` and deprecate ```parquetFile```. This change is similar with #10145 for ```jsonFile```.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10191 from yanboliang/spark-12198.
This PR:
1. Suppress all known warnings.
2. Cleanup test cases and fix some errors in test cases.
3. Fix errors in HiveContext related test cases. These test cases are actually not run previously due to a bug of creating TestHiveContext.
4. Support 'testthat' package version 0.11.0 which prefers that test cases be under 'tests/testthat'
5. Make sure the default Hadoop file system is local when running test cases.
6. Turn on warnings into errors.
Author: Sun Rui <rui.sun@intel.com>
Closes#10030 from sun-rui/SPARK-12034.
1, Add ```isNaN``` to ```Column``` for SparkR. ```Column``` should has three related variable functions: ```isNaN, isNull, isNotNull```.
2, Replace ```DataFrame.isNaN``` with ```DataFrame.isnan``` at SparkR side. Because ```DataFrame.isNaN``` has been deprecated and will be removed at Spark 2.0.
<del>3, Add ```isnull``` to ```DataFrame``` for SparkR. ```DataFrame``` should has two related functions: ```isnan, isnull```.<del>
cc shivaram sun-rui felixcheung
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10037 from yanboliang/spark-12044.
Change ```numPartitions()``` to ```getNumPartitions()``` to be consistent with Scala/Python.
<del>Note: If we can not catch up with 1.6 release, it will be breaking change for 1.7 that we also need to explain in release note.<del>
cc sun-rui felixcheung shivaram
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10123 from yanboliang/spark-12115.
Add support for for colnames, colnames<-, coltypes<-
Also added tests for names, names<- which have no test previously.
I merged with PR 8984 (coltypes). Clicked the wrong thing, crewed up the PR. Recreated it here. Was #9218
shivaram sun-rui
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9654 from felixcheung/colnamescoltypes.
Change ```cumeDist -> cume_dist, denseRank -> dense_rank, percentRank -> percent_rank, rowNumber -> row_number``` at SparkR side.
There are two reasons that we should make this change:
* We should follow the [naming convention rule of R](http://www.inside-r.org/node/230645)
* Spark DataFrame has deprecated the old convention (such as ```cumeDist```) and will remove it in Spark 2.0.
It's better to fix this issue before 1.6 release, otherwise we will make breaking API change.
cc shivaram sun-rui
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#10016 from yanboliang/SPARK-12025.
Added tests for function that are reported as masked, to make sure the base:: or stats:: function can be called.
For those we can't call, added them to SparkR programming guide.
It would seem to me `table, sample, subset, filter, cov` not working are not actually expected - I investigated/experimented with them but couldn't get them to work. It looks like as they are defined in base or stats they are missing the S3 generic, eg.
```
> methods("transform")
[1] transform,ANY-method transform.data.frame
[3] transform,DataFrame-method transform.default
see '?methods' for accessing help and source code
> methods("subset")
[1] subset.data.frame subset,DataFrame-method subset.default
[4] subset.matrix
see '?methods' for accessing help and source code
Warning message:
In .S3methods(generic.function, class, parent.frame()) :
function 'subset' appears not to be S3 generic; found functions that look like S3 methods
```
Any idea?
More information on masking:
http://www.ats.ucla.edu/stat/r/faq/referencing_objects.htmhttp://www.sfu.ca/~sweldon/howTo/guide4.pdf
This is what the output doc looks like (minus css):
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9785 from felixcheung/rmasked.
The goal of this PR is to add tests covering the issue to ensure that is was resolved by [SPARK-11086](https://issues.apache.org/jira/browse/SPARK-11086).
Author: zero323 <matthew.szymkiewicz@gmail.com>
Closes#9743 from zero323/SPARK-11281-tests.
Use `dropFactors` column-wise instead of nested loop when `createDataFrame` from a `data.frame`
At this moment SparkR createDataFrame is using nested loop to convert factors to character when called on a local data.frame. It works but is incredibly slow especially with data.table (~ 2 orders of magnitude compared to PySpark / Pandas version on a DateFrame of size 1M rows x 2 columns).
A simple improvement is to apply `dropFactor `column-wise and then reshape output list.
It should at least partially address [SPARK-8277](https://issues.apache.org/jira/browse/SPARK-8277).
Author: zero323 <matthew.szymkiewicz@gmail.com>
Closes#9099 from zero323/SPARK-11086.
switched stddev support from DeclarativeAggregate to ImperativeAggregate.
Author: JihongMa <linlin200605@gmail.com>
Closes#9380 from JihongMA/SPARK-11420.
Checked names, none of them should conflict with anything in base
shivaram davies rxin
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9489 from felixcheung/rstddev.
Follow up #9561. Due to [SPARK-11587](https://issues.apache.org/jira/browse/SPARK-11587) has been fixed, we should compare SparkR::glm summary result with native R output rather than hard-code one. mengxr
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9590 from yanboliang/glm-r-test.
This is a follow up on PR #8984, as the corresponding branch for such PR was damaged.
Author: Oscar D. Lara Yejas <olarayej@mail.usf.edu>
Closes#9579 from olarayej/SPARK-10863_NEW14.
Make sample test less flaky by setting the seed
Tested with
```
repeat { if (count(sample(df, FALSE, 0.1)) == 3) { break } }
```
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9549 from felixcheung/rsample.
Expose R-like summary statistics in SparkR::glm for linear regression, the output of ```summary``` like
```Java
$DevianceResiduals
Min Max
-0.9509607 0.7291832
$Coefficients
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.6765 0.2353597 7.123139 4.456124e-11
Sepal_Length 0.3498801 0.04630128 7.556598 4.187317e-12
Species_versicolor -0.9833885 0.07207471 -13.64402 0
Species_virginica -1.00751 0.09330565 -10.79796 0
```
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9561 from yanboliang/spark-11494.
https://issues.apache.org/jira/browse/SPARK-10116
This is really trivial, just happened to notice it -- if `XORShiftRandom.hashSeed` is really supposed to have random bits throughout (as the comment implies), it needs to do something for the conversion to `long`.
mengxr mkolod
Author: Imran Rashid <irashid@cloudera.com>
Closes#8314 from squito/SPARK-10116.
Because deparse() will break the long string into multiple lines, the deserialization will fail
Author: Davies Liu <davies@databricks.com>
Closes#9510 from davies/fix_glm.
Like ml ```LinearRegression```, ```LogisticRegression``` should provide a training summary including feature names and their coefficients.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#9303 from yanboliang/spark-9492.
Mapping spark.driver.memory from sparkEnvir to spark-submit commandline arguments.
shivaram suggested that we possibly add other spark.driver.* properties - do we want to add all of those? I thought those could be set in SparkConf?
sun-rui
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#9290 from felixcheung/rdrivermem.
SparkR should remove `.sparkRSQLsc` and `.sparkRHivesc` when `sparkR.stop()` is called. Otherwise even when SparkContext is reinitialized, `sparkRSQL.init` returns the stale copy of the object and complains:
```r
sc <- sparkR.init("local")
sqlContext <- sparkRSQL.init(sc)
sparkR.stop()
sc <- sparkR.init("local")
sqlContext <- sparkRSQL.init(sc)
sqlContext
```
producing
```r
Error in callJMethod(x, "getClass") :
Invalid jobj 1. If SparkR was restarted, Spark operations need to be re-executed.
```
I have added the check and removal only when SparkContext itself is initialized. I have also added corresponding test for this fix. Let me know if you want me to move the test to SQL test suite instead.
p.s. I tried lint-r but ended up a lots of errors on existing code.
Author: Forest Fang <forest.fang@outlook.com>
Closes#9205 from saurfang/sparkR.stop.
This PR introduce a new feature to run SQL directly on files without create a table, for example:
```
select id from json.`path/to/json/files` as j
```
Author: Davies Liu <davies@databricks.com>
Closes#9173 from davies/source.
…2 regularization if the number of features is small
Author: lewuathe <lewuathe@me.com>
Author: Lewuathe <sasaki@treasure-data.com>
Author: Kai Sasaki <sasaki@treasure-data.com>
Author: Lewuathe <lewuathe@me.com>
Closes#8884 from Lewuathe/SPARK-10668.
I was having issues with collect() and orderBy() in Spark 1.5.0 so I used the DataFrame.R file and test_sparkSQL.R file from the Spark 1.5.1 download. I only modified the join() function in DataFrame.R to include "full", "fullouter", "left", "right", and "leftsemi" and added corresponding test cases in the test for join() and merge() in test_sparkSQL.R file.
Pull request because I filed this JIRA bug report:
https://issues.apache.org/jira/browse/SPARK-10981
Author: Monica Liu <liu.monica.f@gmail.com>
Closes#9029 from mfliu/master.
Bring the change code up to date.
Author: Adrian Zhuang <adrian555@users.noreply.github.com>
Author: adrian555 <wzhuang@us.ibm.com>
Closes#9031 from adrian555/attach2.
as.DataFrame is more a R-style like signature.
Also, I'd like to know if we could make the context, e.g. sqlContext global, so that we do not have to specify it as an argument, when we each time create a dataframe.
Author: Narine Kokhlikyan <narine.kokhlikyan@gmail.com>
Closes#8952 from NarineK/sparkrasDataFrame.
Two points in this PR:
1. Originally thought was that a named R list is assumed to be a struct in SerDe. But this is problematic because some R functions will implicitly generate named lists that are not intended to be a struct when transferred by SerDe. So SerDe clients have to explicitly mark a names list as struct by changing its class from "list" to "struct".
2. SerDe is in the Spark Core module, and data of StructType is represented as GenricRow which is defined in Spark SQL module. SerDe can't import GenricRow as in maven build Spark SQL module depends on Spark Core module. So this PR adds a registration hook in SerDe to allow SQLUtils in Spark SQL module to register its functions for serialization and deserialization of StructType.
Author: Sun Rui <rui.sun@intel.com>
Closes#8794 from sun-rui/SPARK-10051.
1. Add a "col" function into DataFrame.
2. Move the current "col" function in Column.R to functions.R, convert it to S4 function.
3. Add a s4 "column" function in functions.R.
4. Convert the "column" function in Column.R to S4 function. This is for private use.
Author: Sun Rui <rui.sun@intel.com>
Closes#8864 from sun-rui/SPARK-10079.
[SPARK-10905][SparkR]: Export freqItems() for DataFrameStatFunctions
- Add function (together with roxygen2 doc) to DataFrame.R and generics.R
- Expose the function in NAMESPACE
- Add unit test for the function
Author: Rerngvit Yanggratoke <rerngvit@kth.se>
Closes#8962 from rerngvit/SPARK-10905.
the sort function can be used as an alternative to arrange(... ).
As arguments it accepts x - dataframe, decreasing - TRUE/FALSE, a list of orderings for columns and the list of columns, represented as string names
for example:
sort(df, TRUE, "col1","col2","col3","col5") # for example, if we want to sort some of the columns in the same order
sort(df, decreasing=TRUE, "col1")
sort(df, decreasing=c(TRUE,FALSE), "col1","col2")
Author: Narine Kokhlikyan <narine.kokhlikyan@gmail.com>
Closes#8920 from NarineK/sparkrsort.
The fix is to coerce `c("a", "b")` into a list such that it could be serialized to call JVM with.
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#8961 from felixcheung/rselect.
Created method as.data.frame as a synonym for collect().
Author: Oscar D. Lara Yejas <olarayej@mail.usf.edu>
Author: olarayej <oscar.lara.yejas@us.ibm.com>
Author: Oscar D. Lara Yejas <oscar.lara.yejas@us.ibm.com>
Closes#8908 from olarayej/SPARK-10807.
This integrates the Interaction feature transformer with SparkR R formula support (i.e. support `:`).
To generate reasonable ML attribute names for feature interactions, it was necessary to add the ability to read attribute the original attribute names back from `StructField`, and also to specify custom group prefixes in `VectorAssembler`. This also has the side-benefit of cleaning up the double-underscores in the attributes generated for non-interaction terms.
mengxr
Author: Eric Liang <ekl@databricks.com>
Closes#8830 from ericl/interaction-2.
1. Support collecting data of MapType from DataFrame.
2. Support data of MapType in createDataFrame.
Author: Sun Rui <rui.sun@intel.com>
Closes#8711 from sun-rui/SPARK-10050.
Adding STDDEV support for DataFrame using 1-pass online /parallel algorithm to compute variance. Please review the code change.
Author: JihongMa <linlin200605@gmail.com>
Author: Jihong MA <linlin200605@gmail.com>
Author: Jihong MA <jihongma@jihongs-mbp.usca.ibm.com>
Author: Jihong MA <jihongma@Jihongs-MacBook-Pro.local>
Closes#6297 from JihongMA/SPARK-SQL.
this PR :
1. Enhance reflection in RBackend. Automatically matching a Java array to Scala Seq when finding methods. Util functions like seq(), listToSeq() in R side can be removed, as they will conflict with the Serde logic that transferrs a Scala seq to R side.
2. Enhance the SerDe to support transferring a Scala seq to R side. Data of ArrayType in DataFrame
after collection is observed to be of Scala Seq type.
3. Support ArrayType in createDataFrame().
Author: Sun Rui <rui.sun@intel.com>
Closes#8458 from sun-rui/SPARK-10049.
Spark gives an error message and does not show the output when a field of the result DataFrame contains characters in CJK.
I changed SerDe.scala in order that Spark support Unicode characters when writes a string to R.
Author: CHOIJAEHONG <redrock07@naver.com>
Closes#7494 from CHOIJAEHONG1/SPARK-8951.
Add subset and transform
Also reorganize `[` & `[[` to subset instead of select
Note: for transform, transform is very similar to mutate. Spark doesn't seem to replace existing column with the name in mutate (ie. `mutate(df, age = df$age + 2)` - returned DataFrame has 2 columns with the same name 'age'), so therefore not doing that for now in transform.
Though it is clearly stated it should replace column with matching name (should I open a JIRA for mutate/transform?)
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#8503 from felixcheung/rsubset_transform.
This PR:
1. supports transferring arbitrary nested array from JVM to R side in SerDe;
2. based on 1, collect() implemenation is improved. Now it can support collecting data of complex types
from a DataFrame.
Author: Sun Rui <rui.sun@intel.com>
Closes#8276 from sun-rui/SPARK-10048.
I added lots of Column functinos into SparkR. And I also added `rand(seed: Int)` and `randn(seed: Int)` in Scala. Since we need such APIs for R integer type.
### JIRA
[[SPARK-9856] Add expression functions into SparkR whose params are complicated - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9856)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#8264 from yu-iskw/SPARK-9856-3.
- Add `when` and `otherwise` as `Column` methods
- Add `When` as an expression function
- Add `%otherwise%` infix as an alias of `otherwise`
Since R doesn't support a feature like method chaining, `otherwise(when(condition, value), value)` style is a little annoying for me. If `%otherwise%` looks strange for shivaram, I can remove it. What do you think?
### JIRA
[[SPARK-10075] Add `when` expressino function in SparkR - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-10075)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#8266 from yu-iskw/SPARK-10075.
### Summary
- Add `lit` function
- Add `concat`, `greatest`, `least` functions
I think we need to improve `collect` function in order to implement `struct` function. Since `collect` doesn't work with arguments which includes a nested `list` variable. It seems that a list against `struct` still has `jobj` classes. So it would be better to solve this problem on another issue.
### JIRA
[[SPARK-9871] Add expression functions into SparkR which have a variable parameter - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9871)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#8194 from yu-iskw/SPARK-9856.
This is a WIP patch for SPARK-8844 for collecting reviews.
This bug is about reading an empty DataFrame. in readCol(),
lapply(1:numRows, function(x) {
does not take into consideration the case where numRows = 0.
Will add unit test case.
Author: Sun Rui <rui.sun@intel.com>
Closes#7419 from sun-rui/SPARK-8844.
I added lots of expression functions for SparkR. This PR includes only functions whose params are only `(Column)` or `(Column, Column)`. And I think we need to improve how to test those functions. However, it would be better to work on another issue.
## Diff Summary
- Add lots of functions in `functions.R` and their generic in `generic.R`
- Add aliases for `ceiling` and `sign`
- Move expression functions from `column.R` to `functions.R`
- Modify `rdname` from `column` to `functions`
I haven't supported `not` function, because the name has a collesion with `testthat` package. I didn't think of the way to define it.
## New Supported Functions
```
approxCountDistinct
ascii
base64
bin
bitwiseNOT
ceil (alias: ceiling)
crc32
dayofmonth
dayofyear
explode
factorial
hex
hour
initcap
isNaN
last_day
length
log2
ltrim
md5
minute
month
negate
quarter
reverse
round
rtrim
second
sha1
signum (alias: sign)
size
soundex
to_date
trim
unbase64
unhex
weekofyear
year
datediff
levenshtein
months_between
nanvl
pmod
```
## JIRA
[[SPARK-9855] Add expression functions into SparkR whose params are simple - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9855)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#8123 from yu-iskw/SPARK-9855.
shivaram cafreeman Could you please help me in testing this out? Exposing and running `rPackageBuilder` from inside the shell works, but for some reason, I can't get it to work during Spark Submit. It just starts relaunching Spark Submit.
For testing, you may use the R branch with [sbt-spark-package](https://github.com/databricks/sbt-spark-package). You can call spPackage, and then pass the jar using `--jars`.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#7139 from brkyvz/r-submit and squashes the following commits:
0de384f [Burak Yavuz] remove unused imports 2
d253708 [Burak Yavuz] removed unused imports
6603d0d [Burak Yavuz] addressed comments
4258ffe [Burak Yavuz] merged master
ddfcc06 [Burak Yavuz] added zipping test
3a1be7d [Burak Yavuz] don't zip
77995df [Burak Yavuz] fix URI
ac45527 [Burak Yavuz] added zipping of all libs
e6bf7b0 [Burak Yavuz] add println ignores
1bc5554 [Burak Yavuz] add assumes for tests
9778e03 [Burak Yavuz] addressed comments
b42b300 [Burak Yavuz] merged master
ffd134e [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into r-submit
d867756 [Burak Yavuz] add apache header
eff5ba1 [Burak Yavuz] ready for review
8838edb [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into r-submit
e5b5a06 [Burak Yavuz] added doc
bb751ce [Burak Yavuz] fix null bug
0226768 [Burak Yavuz] fixed issues
8810beb [Burak Yavuz] R packages support
This PR adds synonyms for ```merge``` and ```summary``` in SparkR DataFrame API.
cc shivaram
Author: Hossein <hossein@databricks.com>
Closes#7806 from falaki/SPARK-9320 and squashes the following commits:
72600f7 [Hossein] Updated docs
92a6e75 [Hossein] Fixed merge generic signature issue
4c2b051 [Hossein] Fixing naming with mllib summary
0f3a64c [Hossein] Added ... to generic for merge
30fbaf8 [Hossein] Merged master
ae1a4cf [Hossein] Merge branch 'master' into SPARK-9320
e8eb86f [Hossein] Add a generic for merge
fc01f2d [Hossein] Added unit test
8d92012 [Hossein] Added merge as an alias for join
5b8bedc [Hossein] Added unit test
632693d [Hossein] Added summary as an alias for describe for DataFrame
Adds following aliases:
* unique (distinct)
* rbind (unionAll): accepts many DataFrames
* nrow (count)
* ncol
* dim
* names (columns): along with the replacement function to change names
Author: Hossein <hossein@databricks.com>
Closes#7764 from falaki/sparkR-alias and squashes the following commits:
56016f5 [Hossein] Updated R documentation
5e4a4d0 [Hossein] Removed extra code
f51cbef [Hossein] Merge branch 'master' into sparkR-alias
c1b88bd [Hossein] Moved setGeneric and other comments applied
d9307f8 [Hossein] Added tests
b5aa988 [Hossein] Added dim, ncol, nrow, names, rbind, and unique functions to DataFrames
With the change in this patch, I get no more warnings from `./dev/lint-r` in my machine
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#7834 from shivaram/sparkr-style-fixes and squashes the following commits:
716cd8e [Shivaram Venkataraman] Remaining SparkR style fixes
### JIRA
[[SPARK-9053] Fix spaces around parens, infix operators etc. - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9053)
### The Result of `lint-r`
[The result of lint-r at the rivision:a4c83cb1e4b066cd60264b6572fd3e51d160d26a](https://gist.github.com/yu-iskw/d253d7f8ef351f86443d)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#7584 from yu-iskw/SPARK-9053 and squashes the following commits:
613170f [Yu ISHIKAWA] Ignore a warning about a space before a left parentheses
ede61e1 [Yu ISHIKAWA] Ignores two warnings about a space before a left parentheses. TODO: After updating `lintr`, we will remove the ignores
de3e0db [Yu ISHIKAWA] Add '## nolint start' & '## nolint end' statement to ignore infix space warnings
e233ea8 [Yu ISHIKAWA] [SPARK-9053][SparkR] Fix spaces around parens, infix operators etc.
This patch improves SparkR error message reporting, especially with DataFrame API. When there is a user error (e.g., malformed SQL query), the message of the cause is sent back through the RPC and the R client reads it and returns it back to user.
cc shivaram
Author: Hossein <hossein@databricks.com>
Closes#7742 from falaki/SPARK-8742 and squashes the following commits:
4f643c9 [Hossein] Not logging exceptions in RBackendHandler
4a8005c [Hossein] Returning stack track of causing exception from RBackendHandler
5cf17f0 [Hossein] Adding unit test for error messages from SQLContext
2af75d5 [Hossein] Reading error message in case of failure and stoping with that message
f479c99 [Hossein] Wrting exception cause message in JVM
### JIRA
[[SPARK-9248] Closing curly-braces should always be on their own line - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9248)
## The result of `dev/lint-r`
[The result of `dev/lint-r` for SPARK-9248 at the revistion:6175d6cfe795fbd88e3ee713fac375038a3993a8](https://gist.github.com/yu-iskw/96cadcea4ce664c41f81)
Author: Yuu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#7795 from yu-iskw/SPARK-9248 and squashes the following commits:
c8eccd3 [Yuu ISHIKAWA] [SPARK-9248][SparkR] Closing curly-braces should always be on their own line
Otherwise, `sparkR.init()` with multiple `sparkPackages` results in this warning:
```
Warning message:
In if (packages != "") { :
the condition has length > 1 and only the first element will be used
```
Author: trestletech <jeff.allen@trestletechnology.net>
Closes#7701 from trestletech/compare-packages and squashes the following commits:
72c8b36 [trestletech] Correct function name.
c52db0e [trestletech] Added test for multiple packages.
3aab1a7 [trestletech] Use vector-friendly comparison for packages argument.
This adds StringType feature support via OneHotEncoder. As part of this task it was necessary to change RFormula to an Estimator, so that factor levels could be determined from the training dataset.
Not sure if I am using uids correctly here, would be good to get reviewer help on that.
cc mengxr
Umbrella design doc: https://docs.google.com/document/d/10NZNSEurN2EdWM31uFYsgayIPfCFHiuIu3pCWrUmP_c/edit#
Author: Eric Liang <ekl@databricks.com>
Closes#7574 from ericl/string-features and squashes the following commits:
f99131a [Eric Liang] comments
0bf3c26 [Eric Liang] update docs
c302a2c [Eric Liang] fix tests
9d1ac82 [Eric Liang] Merge remote-tracking branch 'upstream/master' into string-features
e713da3 [Eric Liang] comments
4d79193 [Eric Liang] revert to seq + distinct
169a085 [Eric Liang] tweak functional test
a230a47 [Eric Liang] Merge branch 'master' into string-features
72bd6f3 [Eric Liang] fix merge
d841cec [Eric Liang] Merge branch 'master' into string-features
5b2c4a2 [Eric Liang] Mon Jul 20 18:45:33 PDT 2015
b01c7c5 [Eric Liang] add test
8a637db [Eric Liang] encoder wip
a1d03f4 [Eric Liang] refactor into estimator
Add `crosstab` to SparkR DataFrames, which takes two column names and returns a local R data.frame. This is similar to `table` in R. However, `table` in SparkR is used for loading SQL tables as DataFrames. The return type is data.frame instead table for `crosstab` to be compatible with Scala/Python.
I couldn't run R tests successfully on my local. Many unit tests failed. So let's try Jenkins.
Author: Xiangrui Meng <meng@databricks.com>
Closes#7318 from mengxr/SPARK-8364 and squashes the following commits:
d75e894 [Xiangrui Meng] fix tests
53f6ddd [Xiangrui Meng] fix tests
f1348d6 [Xiangrui Meng] update test
47cb088 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-8364
5621262 [Xiangrui Meng] first version without test
This exposes the SparkR:::glm() and SparkR:::predict() APIs. It was necessary to change RFormula to silently drop the label column if it was missing from the input dataset, which is kind of a hack but necessary to integrate with the Pipeline API.
The umbrella design doc for MLlib + SparkR integration can be viewed here: https://docs.google.com/document/d/10NZNSEurN2EdWM31uFYsgayIPfCFHiuIu3pCWrUmP_c/edit
mengxr
Author: Eric Liang <ekl@databricks.com>
Closes#7483 from ericl/spark-8774 and squashes the following commits:
3dfac0c [Eric Liang] update
17ef516 [Eric Liang] more comments
1753a0f [Eric Liang] make glm generic
b0f50f8 [Eric Liang] equivalence test
550d56d [Eric Liang] export methods
c015697 [Eric Liang] second pass
117949a [Eric Liang] comments
5afbc67 [Eric Liang] test label columns
6b7f15f [Eric Liang] Fri Jul 17 14:20:22 PDT 2015
3a63ae5 [Eric Liang] Fri Jul 17 13:41:52 PDT 2015
ce61367 [Eric Liang] Fri Jul 17 13:41:17 PDT 2015
0299c59 [Eric Liang] Fri Jul 17 13:40:32 PDT 2015
e37603f [Eric Liang] Fri Jul 17 12:15:03 PDT 2015
d417d0c [Eric Liang] Merge remote-tracking branch 'upstream/master' into spark-8774
29a2ce7 [Eric Liang] Merge branch 'spark-8774-1' into spark-8774
d1959d2 [Eric Liang] clarify comment
2db68aa [Eric Liang] second round of comments
dc3c943 [Eric Liang] address comments
5765ec6 [Eric Liang] fix style checks
1f361b0 [Eric Liang] doc
d33211b [Eric Liang] r support
fb0826b [Eric Liang] [SPARK-8774] Add R model formula with basic support as a transformer
[[SPARK-9093] Fix single-quotes strings in SparkR - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-9093)
This is the result of lintr at the rivision:011551620faa87107a787530f074af3d9be7e695
[[SPARK-9093] The result of lintr at 011551620f](https://gist.github.com/yu-iskw/8c47acf3202796da4d01)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#7439 from yu-iskw/SPARK-9093 and squashes the following commits:
61c391e [Yu ISHIKAWA] [SPARK-9093][SparkR] Fix single-quotes strings in SparkR
JIRA: https://issues.apache.org/jira/browse/SPARK-8807
Add between operator in SparkR.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7356 from viirya/add_r_between and squashes the following commits:
7f51b44 [Liang-Chi Hsieh] Add test for non-numeric column.
c6a25c5 [Liang-Chi Hsieh] Add between function.
JIRA: https://issues.apache.org/jira/browse/SPARK-8840
Currently the type coercion rules don't include float type. This PR simply adds it.
Author: Liang-Chi Hsieh <viirya@appier.com>
Closes#7280 from viirya/add_r_float_coercion and squashes the following commits:
c86dc0e [Liang-Chi Hsieh] For comments.
dbf0c1b [Liang-Chi Hsieh] Implicitly convert Double to Float based on provided schema.
733015a [Liang-Chi Hsieh] Add test case for DataFrame with float type.
30c2a40 [Liang-Chi Hsieh] Update test case.
52b5294 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_r_float_coercion
6f9159d [Liang-Chi Hsieh] Add another test case.
8db3244 [Liang-Chi Hsieh] schema also needs to support float. add test case.
0dcc992 [Liang-Chi Hsieh] Add float coercion on SparkR.
Author: Sun Rui <rui.sun@intel.com>
Closes#7395 from sun-rui/SPARK-8808 and squashes the following commits:
ce603bc [Sun Rui] Use '<-' instead of '='.
88590b1 [Sun Rui] Use '<-' instead of '='.
[[SPARK-8549] Fix the line length of SparkR - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-8549)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#7204 from yu-iskw/SPARK-8549 and squashes the following commits:
6fb131a [Yu ISHIKAWA] Fix the typo
1737598 [Yu ISHIKAWA] [SPARK-8549][SparkR] Fix the line length of SparkR
1. Update the pattern 'expect_true(a == b)' to 'expect_equal(a, b)'.
2. Update the pattern 'expect_true(inherits(a, b))' to 'expect_is(a, b)'.
3. Update the pattern 'expect_true(identical(a, b))' to 'expect_identical(a, b)'.
Author: Sun Rui <rui.sun@intel.com>
Closes#7152 from sun-rui/SPARK-7714 and squashes the following commits:
8ad2440 [Sun Rui] Fix test case errors.
8fe9f0c [Sun Rui] Update the pattern 'expect_true(identical(a, b))' to 'expect_identical(a, b)'.
f1b8005 [Sun Rui] Update the pattern 'expect_true(inherits(a, b))' to 'expect_is(a, b)'.
f631e94 [Sun Rui] Update the pattern 'expect_true(a == b)' to 'expect_equal(a, b)'.
Add `getStaticClass` method in SparkR's `RBackendHandler`
This is a fix for the problem referenced in [SPARK-5185](https://issues.apache.org/jira/browse/SPARK-5185).
cc shivaram
Author: cafreeman <cfreeman@alteryx.com>
Closes#7001 from cafreeman/branch-1.4 and squashes the following commits:
8f81194 [cafreeman] Add missing license
31aedcf [cafreeman] Refactor test to call an external R script
2c22073 [cafreeman] Merge branch 'branch-1.4' of github.com:apache/spark into branch-1.4
0bea809 [cafreeman] Fixed relative path issue and added smaller JAR
ee25e60 [cafreeman] Merge branch 'branch-1.4' of github.com:apache/spark into branch-1.4
9a5c362 [cafreeman] test for including JAR when launching sparkContext
9101223 [cafreeman] Merge branch 'branch-1.4' of github.com:apache/spark into branch-1.4
5a80844 [cafreeman] Fix style nits
7c6bd0c [cafreeman] [SPARK-8607] SparkR
(cherry picked from commit 2579948bf5)
Signed-off-by: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Test `infer_type` using a more fine-grained approach rather than comparing environments. Since `all.equal`'s behavior has changed in R 3.2, the test became unpassable.
JIRA here:
https://issues.apache.org/jira/browse/SPARK-8662
Author: cafreeman <cfreeman@alteryx.com>
Closes#7045 from cafreeman/R32_Test and squashes the following commits:
b97cc52 [cafreeman] Add `checkStructField` utility
3381e5c [cafreeman] Update SparkSQL Test
(cherry picked from commit 78b31a2a63)
Signed-off-by: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Author: Holden Karau <holden@pigscanfly.ca>
Closes#6928 from holdenk/SPARK-8506-sparkr-does-not-provide-an-easy-way-to-depend-on-spark-packages-when-performing-init-from-inside-of-r and squashes the following commits:
b60dd63 [Holden Karau] Add an example with the spark-csv package
fa8bc92 [Holden Karau] typo: sparm -> spark
865a90c [Holden Karau] strip spaces for comparision
c7a4471 [Holden Karau] Add some documentation
c1a9233 [Holden Karau] refactor for testing
c818556 [Holden Karau] Add pakages to R
[[SPARK-8431] Add in operator to DataFrame Column in SparkR - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-8431)
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#6941 from yu-iskw/SPARK-8431 and squashes the following commits:
1f64423 [Yu ISHIKAWA] Modify the comment
f4309a7 [Yu ISHIKAWA] Make a `setMethod` for `%in%` be independent
6e37936 [Yu ISHIKAWA] Modify a variable name
c196173 [Yu ISHIKAWA] [SPARK-8431][SparkR] Add in operator to DataFrame Column in SparkR
[[SPARK-8548] Remove the trailing whitespaces from the SparkR files - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-8548)
- This is the result of `lint-r`
https://gist.github.com/yu-iskw/0019b37a2c1167f33986
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes#6945 from yu-iskw/SPARK-8548 and squashes the following commits:
0bd567a [Yu ISHIKAWA] [SPARK-8548][SparkR] Remove the trailing whitespaces from the SparkR files
This pull request adds following methods to SparkR:
```R
setJobGroup()
cancelJobGroup()
clearJobGroup()
```
For each method, the spark context is passed as the first argument. There does not seem to be a good way to test these in R.
cc shivaram and davies
Author: Hossein <hossein@databricks.com>
Closes#6889 from falaki/SPARK-8452 and squashes the following commits:
9ce9f1e [Hossein] Added basic tests to verify methods can be called and won't throw errors
c706af9 [Hossein] Added examples
a2c19af [Hossein] taking spark context as first argument
343ca77 [Hossein] Added setJobGroup, cancelJobGroup and clearJobGroup to SparkR
Author: hqzizania <qian.huang@intel.com>
Closes#6190 from hqzizania/R and squashes the following commits:
1641f9e [hqzizania] fixes and add test units
bb3411a [hqzizania] Convert NAs to null type in SparkR DataFrames
cc davies sun-rui
Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Closes#6620 from shivaram/sparkr-read-schema and squashes the following commits:
16a6726 [Shivaram Venkataraman] Fix loadDF to pass schema Also add a unit test
a229877 [Shivaram Venkataraman] Use wrapper function to DataFrameReader
ee70ba8 [Shivaram Venkataraman] Support user-specified schema in read.df
Author: Sun Rui <rui.sun@intel.com>
Closes#6183 from sun-rui/SPARK-7227 and squashes the following commits:
dd6f5b3 [Sun Rui] Rename readEnv() back to readMap(). Add alias na.omit() for dropna().
41cf725 [Sun Rui] [SPARK-7227][SPARKR] Support fillna / dropna in R DataFrame.
sqlCtx -> sqlContext
You can check the docs by:
```
$ cd docs
$ SKIP_SCALADOC=1 jekyll serve
```
cc shivaram
Author: Davies Liu <davies@databricks.com>
Closes#5442 from davies/r_docs and squashes the following commits:
7a12ec6 [Davies Liu] remove rdd in R docs
8496b26 [Davies Liu] remove the docs related to RDD
e23b9d6 [Davies Liu] delete R docs for RDD API
222e4ff [Davies Liu] Merge branch 'master' into r_docs
89684ce [Davies Liu] Merge branch 'r_docs' of github.com:davies/spark into r_docs
f0a10e1 [Davies Liu] address comments from @shivaram
f61de71 [Davies Liu] Update pairRDD.R
3ef7cf3 [Davies Liu] use + instead of function(a,b) a+b
2f10a77 [Davies Liu] address comments from @cafreeman
9c2a062 [Davies Liu] mention R api together with Python API
23f751a [Davies Liu] Fill in SparkR examples in programming guide
