As an Data Science & AI Workbench Administrator, you can create custom environments. These environments include specific packages and their dependencies. You can then create a custom installer for the environment, that can be shipped to HDFS and used in Spark jobs. Custom installers enable IT and Hadoop administrators to maintain close control of a Hadoop cluster while also making these tools available to data scientists who need Python and R libraries. They provide an easy way to ship multiple custom Anaconda distributions to multiple Hadoop clusters.

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Creating an environment

  1. Open the My Account dropdown menu and select Admin Console.
  2. Select Environments from the left-hand navigation.
  3. Click Create, give the environment a unique name, and then click Save.
    Environment names can contain alphanumeric characters and underscores only.
  4. Select the channel you want to choose packages from, then select the specific packages—and version of each—you want to include in the installer.
  5. Click Save to create the environment. Workbench resolves all the package dependencies and displays the environment in the list.
    If there is an issue resolving the dependencies, you’ll be notified and prompted to edit the environment.
You can now use the environment as a basis for creating additional versions of the environment or other environments.

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Editing an existing environment

  1. Click on an environment name to view details about the packages included in the environment, then click Edit.
  2. Change the channels and/or packages included in the environment, and enter a version number for the updated package before clicking Save. The new version is displayed in the list of environments.

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Creating a custom installer for an environment

Select the environment in the list, click Create installer, and then select the type of installer you want to create. Workbench creates the installer and displays it in the Installers list.
Use the icons at the top of the page to manage your environment. You can edit, duplicate, delete, and view logs and resolved packages for the selected environment.