## What changes were proposed in this pull request?
Add coalesce on DataFrame for down partitioning without shuffle and coalesce on Column
## How was this patch tested?
manual, unit tests
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16739 from felixcheung/rcoalesce.
## What changes were proposed in this pull request?
With doc to say this would convert DF into RDD
## How was this patch tested?
unit tests, manual tests
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16668 from felixcheung/rgetnumpartitions.
## What changes were proposed in this pull request?
To allow specifying number of partitions when the DataFrame is created
## How was this patch tested?
manual, unit tests
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#16512 from felixcheung/rnumpart.
## What changes were proposed in this pull request?
Rename RDD functions for now to avoid CRAN check warnings.
Some RDD functions are sharing generics with DataFrame functions (hence the problem) so after the renames we need to add new generics, for now.
## How was this patch tested?
unit tests
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#14626 from felixcheung/rrddfunctions.
## What changes were proposed in this pull request?
Fix R SparkSession init/stop, and warnings of reusing existing Spark Context
## How was this patch tested?
unit tests
shivaram
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#14177 from felixcheung/rsessiontest.
## What changes were proposed in this pull request?
This PR introduces the new SparkSession API for SparkR.
`sparkR.session.getOrCreate()` and `sparkR.session.stop()`
"getOrCreate" is a bit unusual in R but it's important to name this clearly.
SparkR implementation should
- SparkSession is the main entrypoint (vs SparkContext; due to limited functionality supported with SparkContext in SparkR)
- SparkSession replaces SQLContext and HiveContext (both a wrapper around SparkSession, and because of API changes, supporting all 3 would be a lot more work)
- Changes to SparkSession is mostly transparent to users due to SPARK-10903
- Full backward compatibility is expected - users should be able to initialize everything just in Spark 1.6.1 (`sparkR.init()`), but with deprecation warning
- Mostly cosmetic changes to parameter list - users should be able to move to `sparkR.session.getOrCreate()` easily
- An advanced syntax with named parameters (aka varargs aka "...") is supported; that should be closer to the Builder syntax that is in Scala/Python (which unfortunately does not work in R because it will look like this: `enableHiveSupport(config(config(master(appName(builder(), "foo"), "local"), "first", "value"), "next, "value"))`
- Updating config on an existing SparkSession is supported, the behavior is the same as Python, in which config is applied to both SparkContext and SparkSession
- Some SparkSession changes are not matched in SparkR, mostly because it would be breaking API change: `catalog` object, `createOrReplaceTempView`
- Other SQLContext workarounds are replicated in SparkR, eg. `tables`, `tableNames`
- `sparkR` shell is updated to use the SparkSession entrypoint (`sqlContext` is removed, just like with Scale/Python)
- All tests are updated to use the SparkSession entrypoint
- A bug in `read.jdbc` is fixed
TODO
- [x] Add more tests
- [ ] Separate PR - update all roxygen2 doc coding example
- [ ] Separate PR - update SparkR programming guide
## How was this patch tested?
unit tests, manual tests
shivaram sun-rui rxin
Author: Felix Cheung <felixcheung_m@hotmail.com>
Author: felixcheung <felixcheung_m@hotmail.com>
Closes#13635 from felixcheung/rsparksession.
## 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 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.
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.
2015-12-07 10:38:17 -08:00
Renamed from R/pkg/inst/tests/test_rdd.R (Browse further)
