Icon

Conda_​Environment_​Propagation_​for_​R

Outside of KNIME:1. Download and install Anaconda3 or Miniconda3 (see https://docs.anaconda.com/anaconda/install/)2. Create an R environment that contains RServe (which is required by KNIME), e.g. using the Anaconda Prompt on Windows or theterminal on macOS/Linux.The following command creates a sample environment named my-r-environment containing the R interpreter, Rserve, and some basepackages in versions that are known to work with KNIME. Note, however, that conda-forge is being used as additional sourcerespository channel, which is a community-driven repository and thus may not be suitable for enterprise environments due topossible security concerns: conda create -n my-r-environment -c defaults -c conda-forge r-base=3.6.1 r-rserve=1.8_7 r-essentials=3.6.0 Creating the environment might take a while and requires an active internet connection.Also see https://docs.anaconda.com/anaconda/user-guide/tasks/using-r-language/ and https://docs.knime.com/latest/r_installation_guide/index.html for more details.In KNIME:1. Install KNIME Interactive R Statistics Integration and KNIME Python Integration (which contains the Conda EnvironmentPropagation node)2. Point KNIME to the base directory of the Anaconda3 or Miniconda3 installation via File > Preferences > KNIME > Python > Path tothe Conda installation directory3. Add a Conda Environment Propagation node to the workflow. Open its configuration dialog and select the created R environment viathe Conda environment drop-down list. Optionally select the relevant packages and the validation method4. Add an R scripting node to the workflow. Configure it to use the propagated environment by setting the following options underAdvanced > Path to R Home in its configration dialog: - Check Overwrite default path to R home - Select Use conda environment to find R home - Select the correct Conda environment flow variable Propagates"my-r-environment"Configured to use"my-r-environment" Data Generator Conda EnvironmentPropagation R Snippet Outside of KNIME:1. Download and install Anaconda3 or Miniconda3 (see https://docs.anaconda.com/anaconda/install/)2. Create an R environment that contains RServe (which is required by KNIME), e.g. using the Anaconda Prompt on Windows or theterminal on macOS/Linux.The following command creates a sample environment named my-r-environment containing the R interpreter, Rserve, and some basepackages in versions that are known to work with KNIME. Note, however, that conda-forge is being used as additional sourcerespository channel, which is a community-driven repository and thus may not be suitable for enterprise environments due topossible security concerns: conda create -n my-r-environment -c defaults -c conda-forge r-base=3.6.1 r-rserve=1.8_7 r-essentials=3.6.0 Creating the environment might take a while and requires an active internet connection.Also see https://docs.anaconda.com/anaconda/user-guide/tasks/using-r-language/ and https://docs.knime.com/latest/r_installation_guide/index.html for more details.In KNIME:1. Install KNIME Interactive R Statistics Integration and KNIME Python Integration (which contains the Conda EnvironmentPropagation node)2. Point KNIME to the base directory of the Anaconda3 or Miniconda3 installation via File > Preferences > KNIME > Python > Path tothe Conda installation directory3. Add a Conda Environment Propagation node to the workflow. Open its configuration dialog and select the created R environment viathe Conda environment drop-down list. Optionally select the relevant packages and the validation method4. Add an R scripting node to the workflow. Configure it to use the propagated environment by setting the following options underAdvanced > Path to R Home in its configration dialog: - Check Overwrite default path to R home - Select Use conda environment to find R home - Select the correct Conda environment flow variable Propagates"my-r-environment"Configured to use"my-r-environment"Data Generator Conda EnvironmentPropagation R Snippet

Nodes

Extensions

Links