8fc5cb6285
## What changes were proposed in this pull request?
Change the format of the build command in the README to start with a `./` prefix
./build/mvn -DskipTests clean package
This increases stylistic consistency across the README- all the other commands have a `./` prefix. Having a visible `./` prefix also makes it clear to the user that the shell command requires the current working directory to be at the repository root.
## How was this patch tested?
README.md was reviewed both in raw markdown and in the Github rendered landing page for stylistic consistency.
Closes #25231 from Mister-Meeseeks/master.
Lead-authored-by: Douglas R Colkitt <douglas.colkitt@gmail.com>
Co-authored-by: Mister-Meeseeks <douglas.colkitt@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
70 lines
3.3 KiB
Markdown
70 lines
3.3 KiB
Markdown
# R on Spark
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SparkR is an R package that provides a light-weight frontend to use Spark from R.
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### Installing sparkR
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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`.
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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.
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Example:
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```bash
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# where /home/username/R is where R is installed and /home/username/R/bin contains the files R and RScript
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export R_HOME=/home/username/R
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./install-dev.sh
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```
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### SparkR development
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#### Build Spark
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Build Spark with [Maven](https://spark.apache.org/docs/latest/building-spark.html#buildmvn) and include the `-Psparkr` profile to build the R package. For example to use the default Hadoop versions you can run
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```bash
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./build/mvn -DskipTests -Psparkr package
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```
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#### Running sparkR
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You can start using SparkR by launching the SparkR shell with
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./bin/sparkR
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The `sparkR` script automatically creates a SparkContext with Spark by default in
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local mode. To specify the Spark master of a cluster for the automatically created
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SparkContext, you can run
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./bin/sparkR --master "local[2]"
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To set other options like driver memory, executor memory etc. you can pass in the [spark-submit](https://spark.apache.org/docs/latest/submitting-applications.html) arguments to `./bin/sparkR`
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#### Using SparkR from RStudio
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If you wish to use SparkR from RStudio, please refer [SparkR documentation](https://spark.apache.org/docs/latest/sparkr.html#starting-up-from-rstudio).
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#### Making changes to SparkR
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The [instructions](https://spark.apache.org/contributing.html) for making contributions to Spark also apply to SparkR.
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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.
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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.
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#### Generating documentation
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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](https://github.com/apache/spark/tree/master/docs#prerequisites). See also, `R/DOCUMENTATION.md`
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### Examples, Unit tests
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SparkR comes with several sample programs in the `examples/src/main/r` directory.
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To run one of them, use `./bin/spark-submit <filename> <args>`. For example:
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```bash
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./bin/spark-submit examples/src/main/r/dataframe.R
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```
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You can run R unit tests by following the instructions under [Running R Tests](https://spark.apache.org/docs/latest/building-spark.html#running-r-tests).
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### Running on YARN
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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
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```bash
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export YARN_CONF_DIR=/etc/hadoop/conf
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./bin/spark-submit --master yarn examples/src/main/r/dataframe.R
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```
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