Sharing Projects and Analysis Results

Cloudera Data Science Workbench supports several collaboration models.

Project Collaborators
Sharing Projects Publicly
Forking Projects
Sharing Results Externally

Project Collaborators

If you want to work closely with trusted colleagues on a particular project, add them to the project as collaborators. For instructions, see Adding Project Collaborators.

Warning:

Collaborating Securely on Projects

Before adding project collaborators, you must remember that giving a project collaborator write access to your project code is tantamount to giving them access to your data in CDH. Any collaborators with the Contributor and Admin roles have write-level access to the same project files as you, and therefore have the ability to use the project code to read/modify the data on your CDH cluster.

Another point to note is that project collaborators also have access to all actively running sessions and jobs. This means that a malicious user can easily impersonate you by accessing one of your active sessions and modifying project code on the fly. Therefore, it is extremely important to restrict project access to trusted collaborators only.

For these reasons, Cloudera recommends using Git to collaborate securely on shared projects. This will also help avoid file modification conflicts when your team is working on more elaborate projects.

Sharing Projects Publicly

Public projects on Cloudera Data Science Workbench grant read-level access to everyone with access to the Cloudera Data Science Workbench application. That means everyone can view the project's files and results, but only those whom you have granted write-level access or higher can edit files, run engines, or view the project's environment variables.

You can include a Markdown-formatted README.md file in public projects to document your project's purpose and usage.

If you are a project admin, you can set a project's visibility to Public from the Project > Settings > Options page. For instructions, see Modifying Project Settings.

Forking Projects

You can fork another user's project by clicking Fork on the Project page. Forking creates a new project under your account that contains all the files, libraries, configuration, and jobs from the original project.

Creating sample projects that other users can fork helps to bootstrap new projects and encourage common conventions.

Sharing Results Externally

Cloudera Data Science Workbench lets you easily share the results of your analysis with one click. Using rich visualizations and documentation comments, you can arrange your console log so that it is a readable record of your analysis and results. This log continues to be available even after the session stops.

To share results, click Share at the top of the console page. From here you can generate a link that includes a secret token that gives access to a single console output to anybody with access to the link. You can revoke access at any time. For jobs results, you can either share a link to the latest job result or a particular job run. To share the latest job result, click the Latest Run link for a job on the Overview page. This link will always have the latest job results. To share a particular run, click on a job run in the job's History page and share the corresponding link.

This method of sharing shows colleagues and collaborators your progress without your having to spend time creating a report.

If you want to share a single data visualization rather than an entire console, you can embed it in another web page. Click the small circular 'link' button located to the left of most rich visualizations to view the HTML snippet that you can use to embed the visualization.

Data Visualization

Jobs API