Initialize an SSH Connection to Cloudera Data Science Workbench

The following task describes how to establish an SSH endpoint for Cloudera Data Science Workbench. Creating an SSH endpoint is the first step to configuring a remote editor for Cloudera Data Science Workbench.

  1. Log in to Cloudera Data Science Workbench with the CLI client. Depending on your deployment, make sure you add http or https to the URL as shown below:
    cdswctl login -n <username> -u http(s)://cdsw.your_domain.com
    For example, the following command logs the user sample_user into the https://cdsw.your_domain.com deployment:
    cdswctl login -n sample_user -u https://cdsw.your_domain.com
  2. Create a local SSH endpoint to Cloudera Data Science Workbench. Run the following command:
    cdswctl ssh-endpoint -p <username>/<project_name> [-c <CPU_cores>] [-m <memory_in_GB>] [-g <number_of_GPUs>]
    The command uses the following defaults for optional parameters:
    • CPU cores: 1
    • Memory: 1 GB
    • GPUs: 0
    For example, the following command starts a session for the logged-in user sample_user under the customerchurn project with .5 cores, .75 GB of memory, 0 GPUs, and the Python3 kernel:
    cdswctl ssh-endpoint -p customerchurn -c 0.5 -m 0.75

    To create an SSH endpoint in a project owned by another user or a team, for example finance, prepend the username to the project and separate them with a forward slash:

    cdswctl ssh-endpoint -p finance/customerchurn -c 0.5 -m 0.75
    This command creates session in the project customerchurn that belongs to the team finance.
    Information for the SSH endpoint appears in the output:
    ...
    You can SSH to it using
    
        ssh -p <some_port> cdsw@localhost
    ...
  3. Open a new command prompt and run the outputted command from the previous step:
    ssh -p <some_port> cdsw@localhost
    For example:
    ssh -p 9750 cdsw@localhost
    You will be prompted for the passphrase for the SSH key you entered in the Cloudera Data Science web UI.
    Once you are connected to the endpoint, you are logged in as the cdsw user and can perform actions as though you are accessing the terminal through the Cloudera Data Science Workbench web UI.
  4. Test the connection.
    If you run ls, the project files associated with the session you created are shown. If you run whoami, the command returns the cdsw user.