spark-instrumented-optimizer/R
Maxim Gekk a5a5da78cf [SPARK-28471][SQL] Replace yyyy by uuuu in date-timestamp patterns without era
## What changes were proposed in this pull request?

In the PR, I propose to use `uuuu` for years instead of `yyyy` in date/timestamp patterns without the era pattern `G` (https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html). **Parsing/formatting of positive years (current era) will be the same.** The difference is in formatting negative years belong to previous era - BC (Before Christ).

I replaced the `yyyy` pattern by `uuuu` everywhere except:
1. Test, Suite & Benchmark. Existing tests must work as is.
2. `SimpleDateFormat` because it doesn't support the `uuuu` pattern.
3. Comments and examples (except comments related to already replaced patterns).

Before the changes, the year of common era `100` and the year of BC era `-99`, showed similarly as `100`.  After the changes negative years will be formatted with the `-` sign.

Before:
```Scala
scala> Seq(java.time.LocalDate.of(-99, 1, 1)).toDF().show
+----------+
|     value|
+----------+
|0100-01-01|
+----------+
```

After:
```Scala
scala> Seq(java.time.LocalDate.of(-99, 1, 1)).toDF().show
+-----------+
|      value|
+-----------+
|-0099-01-01|
+-----------+
```

## How was this patch tested?

By existing test suites, and added tests for negative years to `DateFormatterSuite` and `TimestampFormatterSuite`.

Closes #25230 from MaxGekk/year-pattern-uuuu.

Authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2019-07-28 20:36:36 -07:00
..
pkg [SPARK-28471][SQL] Replace yyyy by uuuu in date-timestamp patterns without era 2019-07-28 20:36:36 -07:00
.gitignore [MINOR][R] add SparkR.Rcheck/ and SparkR_*.tar.gz to R/.gitignore 2016-08-21 10:31:25 -07:00
check-cran.sh [SPARK-20123][BUILD] SPARK_HOME variable might have spaces in it(e.g. $SPARK… 2017-04-02 15:31:13 +01:00
CRAN_RELEASE.md [SPARK-26918][DOCS] All .md should have ASF license header 2019-03-30 19:49:45 -05:00
create-docs.sh [SPARK-20123][BUILD] SPARK_HOME variable might have spaces in it(e.g. $SPARK… 2017-04-02 15:31:13 +01:00
create-rd.sh [SPARK-20123][BUILD] SPARK_HOME variable might have spaces in it(e.g. $SPARK… 2017-04-02 15:31:13 +01:00
DOCUMENTATION.md [SPARK-26918][DOCS] All .md should have ASF license header 2019-03-30 19:49:45 -05:00
find-r.sh [SPARK-18828][SPARKR] Refactor scripts for R 2017-01-16 13:49:12 -08:00
install-dev.bat [SPARK-10500][SPARKR] sparkr.zip cannot be created if /R/lib is unwritable 2015-11-15 19:29:09 -08:00
install-dev.sh [SPARK-22167][R][BUILD] sparkr packaging issue allow zinc 2017-10-02 11:46:51 -07:00
install-source-package.sh [SPARK-20123][BUILD] SPARK_HOME variable might have spaces in it(e.g. $SPARK… 2017-04-02 15:31:13 +01:00
log4j.properties [SPARK-8350] [R] Log R unit test output to "unit-tests.log" 2015-06-15 08:16:22 -07:00
README.md [SPARK-28473][DOC] Stylistic consistency of build command in README 2019-07-23 16:29:46 -07:00
run-tests.sh [SPARK-22281][SPARKR] Handle R method breaking signature changes 2017-11-07 21:02:14 -08:00
WINDOWS.md [MINOR][DOCS] Tighten up some key links to the project and download pages to use HTTPS 2019-05-21 10:56:42 -07:00

R on Spark

SparkR is an R package that provides a light-weight frontend to use Spark from R.

Installing sparkR

Libraries of sparkR need to be created in $SPARK_HOME/R/lib. This can be done by running the script $SPARK_HOME/R/install-dev.sh. By default the above script uses the system wide installation of R. However, this can be changed to any user installed location of R by setting the environment variable R_HOME the full path of the base directory where R is installed, before running install-dev.sh script. Example:

# where /home/username/R is where R is installed and /home/username/R/bin contains the files R and RScript
export R_HOME=/home/username/R
./install-dev.sh

SparkR development

Build Spark

Build Spark with Maven and include the -Psparkr profile to build the R package. For example to use the default Hadoop versions you can run

./build/mvn -DskipTests -Psparkr package

Running sparkR

You can start using SparkR by launching the SparkR shell with

./bin/sparkR

The sparkR script automatically creates a SparkContext with Spark by default in local mode. To specify the Spark master of a cluster for the automatically created SparkContext, you can run

./bin/sparkR --master "local[2]"

To set other options like driver memory, executor memory etc. you can pass in the spark-submit arguments to ./bin/sparkR

Using SparkR from RStudio

If you wish to use SparkR from RStudio, please refer SparkR documentation.

Making changes to SparkR

The instructions for making contributions to Spark also apply to SparkR. If you only make R file changes (i.e. no Scala changes) then you can just re-install the R package using R/install-dev.sh and test your changes. Once you have made your changes, please include unit tests for them and run existing unit tests using the R/run-tests.sh script as described below.

Generating documentation

The SparkR documentation (Rd files and HTML files) are not a part of the source repository. To generate them you can run the script R/create-docs.sh. This script uses devtools and knitr to generate the docs and these packages need to be installed on the machine before using the script. Also, you may need to install these prerequisites. See also, R/DOCUMENTATION.md

Examples, Unit tests

SparkR comes with several sample programs in the examples/src/main/r directory. To run one of them, use ./bin/spark-submit <filename> <args>. For example:

./bin/spark-submit examples/src/main/r/dataframe.R

You can run R unit tests by following the instructions under Running R Tests.

Running on YARN

The ./bin/spark-submit can also be used to submit jobs to YARN clusters. You will need to set YARN conf dir before doing so. For example on CDH you can run

export YARN_CONF_DIR=/etc/hadoop/conf
./bin/spark-submit --master yarn examples/src/main/r/dataframe.R