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* [SPARK-10903][SPARKR] R - Simplify SQLContext method signatures and use a ↵felixcheung2016-05-261-1/+1
| | | | | | | | | | | | | | singleton Eliminate the need to pass sqlContext to method since it is a singleton - and we don't want to support multiple contexts in a R session. Changes are done in a back compat way with deprecation warning added. Method signature for S3 methods are added in a concise, clean approach such that in the next release the deprecated signature can be taken out easily/cleanly (just delete a few lines per method). Custom method dispatch is implemented to allow for multiple JVM reference types that are all 'jobj' in R and to avoid having to add 30 new exports. Author: felixcheung <felixcheung_m@hotmail.com> Closes #9192 from felixcheung/rsqlcontext.
* [SPARK-15439][SPARKR] Failed to run unit test in SparkRwm624@hotmail.com2016-05-251-1/+5
| | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? (Please fill in changes proposed in this fix) There are some failures when running SparkR unit tests. In this PR, I fixed two of these failures in test_context.R and test_sparkSQL.R The first one is due to different masked name. I added missed names in the expected arrays. The second one is because one PR removed the logic of a previous fix of missing subset method. The file privilege issue is still there. I am debugging it. SparkR shell can run the test case successfully. test_that("pipeRDD() on RDDs", { actual <- collect(pipeRDD(rdd, "more")) When using run-test script, it complains no such directories as below: cannot open file '/tmp/Rtmp4FQbah/filee2273f9d47f7': No such file or directory ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) Manually test it Author: wm624@hotmail.com <wm624@hotmail.com> Closes #13284 from wangmiao1981/R.
* [SPARK-15091][SPARKR] Fix warnings and a failure in SparkR test cases with ↵Sun Rui2016-05-031-1/+1
| | | | | | | | | | | | | | testthat version 1.0.1 ## 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.
* [SPARK-7264][ML] Parallel lapply for sparkRTimothy Hunter2016-04-281-0/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## 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.
* [SPARK-14780] [R] Add `setLogLevel` to SparkRDongjoon Hyun2016-04-211-0/+5
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## 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.
* [SPARK-13905][SPARKR] Change signature of as.data.frame() to be consistent ↵Sun Rui2016-04-191-1/+1
| | | | | | | | | | | | | | | | with the R base package. ## 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.
* [SPARK-14353] Dataset Time Window `window` API for RBurak Yavuz2016-04-051-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | ## 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.
* [SPARK-12204][SPARKR] Implement drop method for DataFrame in SparkR.Sun Rui2016-01-201-1/+1
| | | | | | Author: Sun Rui <rui.sun@intel.com> Closes #10201 from sun-rui/SPARK-12204.
* [SPARK-12232][SPARKR] New R API for read.table to avoid name conflictfelixcheung2016-01-191-7/+8
| | | | | | | | 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.
* [SPARK-12168][SPARKR] Add automated tests for conflicted function in Rfelixcheung2016-01-191-0/+23
| | | | | | | | | | | | | | | | | | | | | | | | | | | | 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.
* [SPARK-12034][SPARKR] Eliminate warnings in SparkR test cases.Sun Rui2015-12-071-0/+114
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.