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Get started with Python
Step 0: Orient yourself to DominoStep 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get started with R
Step 0: Orient yourself to Domino (R Tutorial)Step 1: Create a projectStep 2: Configure your projectStep 3: Start a workspaceStep 4: Get your files and dataStep 5: Develop your modelStep 6: Clean up WorkspacesStep 7: Deploy your model
Get Started with MATLAB
Step 1: Orient yourself to DominoStep 2: Create a Domino ProjectStep 3: Configure Your Domino ProjectStep 4: Start a MATLAB WorkspaceStep 5: Fetch and Save Your DataStep 6: Develop Your ModelStep 7: Clean Up Your Workspace
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Step 9: Working with Domino Datasets
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About Domino
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User Guide
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Domino Runs
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Advanced Options for Domino Runs
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Run States

Run States

When you start a Run in Domino, the Run will move through several lifecycle states.

This page describes what these different stages mean.

  1. Queued

    The Run is waiting for a machine of your specified hardware tier to become available. If one is available, it will quickly leave this state. However if no slots are available, it can take several minutes to start up a new machine.

  2. Scheduled

    This is when the dispatcher has requested an executor to process the Run and the executor acknowledges this request, but hasn’t begun the processing yet. A Run only remains in this state for a few seconds.

  3. Preparing

    Your project files are being copied to the executor where your code will run. Depending on the size of your data and the number of files in your project, this might finish quickly, or may take a while. Files are cached when possible, so if you start a Run on a hardware tier you used recently with the same project, this may be quick, even for projects with large files.

  4. Building

    If you are using a custom environment, you may need to wait for the Docker image to build. This is cached whenever possible, so subsequent Runs on the same hardware tier may skip this step.

  5. Pulling

    When your Docker image has been saved to a network-attached repository, this state indicates we are fetching the image.

  6. Running

    Your code is executing. You can view the console output and resource usage on the Jobs or Workspaces dashboard.

  7. Finishing

    Your Run has completed, and any file changes are being copied back to the Domino file store.

  8. Succeeded

    Your Run has finished without error.

  9. StopRequested

    The request to stop your Run has been received.

  10. Stopping

    If you manually stop your Run, it will enter this state while any new or updated files are synced back to the project.

  11. Stopped

    The Run has been manually stopped.

  12. Failed

    Your Run did not complete due to a problem with your code.

  13. Error

    Some problem outside your code caused the Run to terminate.

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