Create a Project from a Built-in Template

Cloudera Data Science Workbench is organized around projects. Projects hold all the code, configuration, and libraries needed to reproducibly run analyses.

To help you get started, Cloudera Data Science Workbench includes sample template projects in R, Python, PySpark, and Scala. Using a template project gives you the impetus to start using the Cloudera Data Science Workbench right away.
Create a Template Project

To create a template project:

  1. Sign in to Cloudera Data Science Workbench.
  2. Click New Project.
  3. Enter the account and project name.
  4. Under the Template tab, you can choose one of the programming languages to create a project from one of the built-in templates. Alternatively, if your site administrator has added any custom template projects, those will also be available in this dropdown list.
  5. Click Create Project.
After creating your project, you see your project files and the list of jobs defined in your project. These project files are stored on an internal NFS server, and are available to all your project sessions and jobs, regardless of the gateway hosts they run on. Any changes you make to the code or libraries you install into your project will be immediately available when running an engine.