Managing Notebooks

An administrator can perform the following tasks to manage notebooks.

Configuring Interpreters

An administrator can configure interpreter settings that are then used across all notebooks.

To configure an interpreter:
  1. Access the notebook application. See Accessing Big Data Studio.
  2. Click the Interpreters icon on the left.
  3. Click an interpreter in the list on the left and then configure settings for that interpreter as desired. All new and current notebooks that use this interpreter will use these settings.
Note

Interpreter variants cannot be created and are not supported.

Stopping and Starting Big Data Studio

An administrator can stop and start the Big Data Studio notebook application. You might want to stop or disable the application so it doesn't consume resources, such as memory. Restarting might also help with unexpected issues or behavior.

To perform these actions, you must have access rights on the cluster through the operating system.

To stop and start Big Data Studio:

  1. Connect as opc user to the utility node where Big Data Studio resides (the second utility node of an HA (highly-available) cluster, or the first and only utility node of a non-HA cluster).
  2. Use sudo to manage the datastudio Linux service. The commands are as follows:

    sudo systemctl start datastudio

    sudo systemctl stop datastudio

    sudo systemctl restart datastudio

    sudo systemctl status datastudio

    For information about managing Oracle Linux 7 services with the systemctl command, see Working With System Services in Oracle Linux 7 Managing Core System Configuration.

    For information about logging into an Oracle Cloud Infrastructure instance, see Connecting to Your Instance.

Monitoring Notebook Activities

An administrator can monitor notebook activities.

To view notebook activities:
  1. Access the notebook application. See Accessing Big Data Studio.
  2. Click the Tasks icon on the left.

    The Tasks page displays, listing activities for each notebook, such as which paragraphs were run, which interpreters were used, what the status of the task was (success, error, and so on), when the task was performed, how long it took to run, and which user performed the task. You can also filter or search for tasks.