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.
Log in to Cloudera Data Science Workbench with the CLI client. Depending on your
deployment, make sure you add
httpsto the URL as shown below:
For example, the following command logs the user
cdswctl login -n <username> -u http(s)://cdsw.your_domain.com
cdswctl login -n sample_user -u https://cdsw.your_domain.com
Create a local SSH endpoint to Cloudera Data Science Workbench. Run the following
cdswctl ssh-endpoint -p <username>/<project_name> [-c <CPU_cores>] [-m <memory_in_GB>] [-g <number_of_GPUs>] [-r <runtime ID> ]
If the project is configured to use ML runtimes, the
-rparameter must be specified, otherwise it must be omitted. See Using ML runtimes with cdswctl documentation page for more information.The command uses the following defaults for optional parameters:
For example, the following command starts a session for the logged-in user
- CPU cores: 1
- Memory: 1 GB
- GPUs: 0
customerchurnproject 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:
This command creates session in the project
cdswctl ssh-endpoint -p finance/customerchurn -c 0.5 -m 0.75
customerchurnthat 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 ...
Open a new command prompt and run the outputted command from the previous step:
ssh -p <some_port> cdsw@localhost
You will be prompted for the passphrase for the SSH key you entered in the Cloudera Data Science web UI.
ssh -p 9750 cdsw@localhostOnce you are connected to the endpoint, you are logged in as the
cdswuser and can perform actions as though you are accessing the terminal through the Cloudera Data Science Workbench web UI.
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