R integration¶
Due to the large number of additional system dependencies, DSS R integration is not installed by default.
You can install R integration at any time.
Prerequisites¶
DSS requires R version 3.6 or R version 4.
Only a single version of R can be used.
Note
On some platforms (notably, at the time of writing, SLES 15 systems) the version of R available through the system package manager may not be compatible with DSS.
In that case, automatic installation of R itself by the DSS installer is not possible, and integrating DSS with R requires manually installing a compatible version of R.
On macOS, you must first install R from http://www.r-project.org/. Note that you might need to also install XQuartz.
On Dataiku Cloud, to install R you only need to activate the R integration in the Extension tab of the Launchpad. For more details see see the dedicated documentation.
Case 1: Automatic installation, if your DSS server has Internet access¶
This procedure installs the required R packages and configures R integration for DSS. It prompts you to install any missing dependency as root if needed. Internet access (direct or through a proxy) may be needed to download missing packages.
Go to the DSS data dir
cd DATADIR
Stop DSS
./bin/dss stop
Run the installation script
./bin/dssadmin install-R-integration
Note
The install-R-integration script automatically checks for any missing system dependencies. If any is missing, it will give you the command to run to install them with superuser privileges. After the installation of dependencies is complete, you can retry the install-R-integration script
Start DSS
./bin/dss start
Note
The above procedure downloads missing R packages from a default Internet-based repository using the HTTPS protocol.
If required, you can switch to another repository (CRAN mirror)
by specifying option -repo REPO_URL
, as in:
./bin/dssadmin install-R-integration -repo http://cran.univ-paris1.fr
Note
If the DSS server has Internet access only through a web proxy, you can configure it using the standard http_proxy
and/or https_proxy
environment variables, as follows:
export http_proxy=http://PROXY_HOST:PROXY_PORT
export https_proxy=http://PROXY_HOST:PROXY_PORT
./bin/dssadmin install-R-integration
Case 2: If your DSS server does not have Internet access¶
To help with R package installation when the DSS server does not have Internet access (directly nor through a proxy), the DSS installation kit includes a standalone script which may be used to download the required set of R package sources on a third-party Internet-connected system, and store them to a directory suitable for offline installation on the DSS server.
Check for missing system dependencies on the DSS server, including the base R system, the development tools, and libraries required by the mandatory R packages. If any dependency is missing, you will need to install it from a local package repository for your OS distribution.
dataiku-dss-VERSION/scripts/install/install-deps.sh -check -without-java -without-python -with-r
Retrieve the standalone download script
dataiku-dss-VERSION/scripts/install/download-R-packages.sh
and transport it to the system which you will use for download. This system should run Linux or macOS, should have R installed, and should have Internet connection, directly or through a proxy.On this download system, run the download script as follows:
./download-R-packages.sh -dir DIR
where
DIR
is a temporary directory which will hold the downloaded packages.Transport the resulting directory
DIR
to the DSS server.On the DSS server, install any missing R packages from this download directory, and finish configuring DSS R integration:
DATADIR/bin/dssadmin install-R-integration -pkgDir DIR
Restart DSS
DATADIR/bin/dss restart
Note
The download-R-packages.sh
can be run with additional command-line arguments naming R packages. It will then download these packages
along with their dependencies in addition to the mandatory set of packages required by DSS.
This can be used to install additional R packages to DSS on a server without Internet access, by running DATADIR/bin/R
and calling
install.packages(PACKAGE_NAME, repos = "file://PATH_TO_PKGDIR_DIRECTORY")
Case 3: Custom installation¶
Installing DSS R integration consists in the following steps, which you can perform in any way suitable to your environment:
Install R on the DSS server (version 3.6 or version 4)
Data Science Studio references it by looking up “R” in the PATH. If needed, you can override this by defining environment variable
DKURBIN
in the local customization fileDATADIR/bin/env-site.sh
.Install the following R packages, either in the global R library, or in the user library of the DSS user account:
Packages
Repository
httr RJSONIO dplyr curl IRkernel sparklyr ggplot2 gtools tidyr rmarkdown base64enc filelock
CRAN (https://cran.r-project.org)
Configure DSS R integration, with the option which omits the default dependency check, and restart DSS
cd DATADIR ./bin/dssadmin install-R-integration -noDeps ./bin/dss restart
Troubleshooting¶
Rebuilding the R environment¶
In case a system upgrade of the DSS host installed a new version of R (for example: R 3.4.x to R 3.5.x), DSS-installed R packages may become incompatible and stop working properly.
You should then force a full rebuild of all R environments, as follows:
Rebuilding the default R environment¶
Rename the
DATADIR/R.lib
directory intoDATADIR/R.lib.BAK
Replay the
dssadmin install-R-integration
command using one of the methods above, to reinstall all required R packages from scratchOptionally, check the
DATADIR/R.lib.BAK
directory for additional packages which you would have manually installed, and reinstall those as wellRestart DSS
Once R has been checked to work correctly, remove the backup directory.
Rebuilding managed R code environments¶
You should force a full rebuild of all R-based managed code environments by navigating to the Administration / Code Envs page, opening each R environment, selecting “Rebuild env” and clicking “UPDATE”.
Warning
If any R packages were manually installed in the default R library (typically, by calling “install.packages()” from a R session run by the root account), they may need to be reinstalled as well.
macOS¶
Some R versions (notably the one coming through Homebrew) are configured to use source packages by default rather than binary packages. If you leave this option, automatic installation may fail as you need the development tools installed, and quite a number of additional libraries.
If you get a compilation error when installing one of the missing packages while running install-R-integration, you may try to manually install the binary version of this package instead. At the R prompt:
options(pkgType="both")
install.packages("PACKAGE_NAME", repos = "http://cloud.r-project.org/")
Then run the install-R-integration command again.
Anaconda R¶
An alternative to the above is to use the Anaconda R distribution, and install the required R packages using conda install
.
You will need to set the DKURBIN
environment variable to the fully-qualified path to the R entry point of the
corresponding conda environment so that DSS uses it instead of the default R command.