Cloudera Docs

Editors

In addition to the built-in Cloudera Data Science Workbench editor, you can configure Cloudera Data Science Workbench to work with third-party, browser-based IDEs such as Jupyter and also certain local IDEs that run on your machine, such as PyCharm.

In the Cloudera Data Science Workbench documentation, browser-based IDEs such as Jupyter and RStudio are referred to as browser IDEs, whereas IDEs such as PyCharm that run on your local machine outside the browser are referred to as local IDEs.

You can use the browser or local IDE of your choice to edit and run code interactively. When you bring your own editor, you still get many of the benefits of Cloudera Data Science Workbench behind an editor interface you are familiar with:
  • Dependency management that lets you share code with confidence
  • CDH client configurations
  • Automatic Kerberos authentication through Cloudera Data Science Workbench
  • Reuse code in other Cloudera Data Science Workbench features such as experiments and jobs
  • Collaboration features such as teams
  • Compliance with IT rules for where compute, data, and/or code must reside. For example, compute occurs within the Cloudera Data Science Workbench deployment, not the local machine. Browser IDEs run within a Cloudera Data Science Workbench session and follow all the same compliance rules. Local IDEs, on the other hand, can bring data or code to a user's machine. Therefore, Site Administrators can opt to disable local IDEs to balance user productivity with compliance concerns.
Note that you can only edit and run code interactively with the IDEs. Tasks such as creating a project or deploying a model require the Cloudera Data Science Workbench web UI and cannot be completed through an editor.
The configuration for an IDE depends on which type of editor you want to use:
Workbench editor
The Workbench editor is the built-in editor for Cloudera Data Science Workbench. No additional configuration is required to use it. When you launch a session, select the Workbench editor.
Third-party, browser-based IDEs

Browser IDEs are editors such as Jupyter or RStudio. When you use a browser IDE, it runs within a session and allows you to edit and run code interactively. Changes that you make in the editor are propagated to the Cloudera Data Science Workbench project. Base Engine Image v8 ships with Jupyter preconfigured as a browser IDE. You can select it when you start a session or add a different browser IDE.

Keep the following in mind when using browser IDEs:
  • Engine Version Requirements
    • Browser-based IDEs that are configured using custom engines require Base Engine Image v8 or higher.
    • Browser-based IDEs that are configured directly within individual projects do not require a specific engine image. However, Cloudera recommends you use the latest engine image.
  • When you are finished using a browser IDE, you must exit the IDE properly, including saving your work if necessary. Do not just stop the Cloudera Data Science Workbench session. Doing so will cause you to lose your session state.
  • Depending on the behavior of the browser IDE, multiple users within a project may overwrite each other's state.
  • Browser IDEs do not adhere to the timeout set in
  • Logs for browser IDEs are available on the Logs tab of the session window. This includes information that the IDE may generate, such as error messages, in addition to any Cloudera Data Science Workbench logs.
Local IDE Editors on your machine that can use SSH-based remote editing

These editors, referred to as Local IDEs in the documentation, are editors such as PyCharm that run on your local machine. They connect to the Cloudera Data Science Workbench with an SSH endpoint and allow you to edit and run code interactively. You must manually configure some sort of file sync and ignore list between your local machine and Cloudera Data Science Workbench. You can use functionality within the local IDE, such as PyCharm's sync, or external tools that can sync via the SSH endpoint, such as mutagen.

Keep the following in mind before setting up local IDEs:
  • Local IDEs do not require a specific engine image, but Cloudera recommends you use the latest engine image.
  • Site Administrators should work with IT to determine the data access policies for your organization. For example, your data policy may not allow users to sync certain files to their machines from Cloudera Data Science Workbench. Verify that users understand the requirements and adhere to them when configuring their file sync behavior.
  • Users should ensure that the IDEs they want to use support SSH. For example, VS Code supports "remote development over SSH," and PyCharm supports using a "remote interpreter over SSH."

For more information, see AWS Account Requirements.