BAD_REQUEST: ExperimentIds cannot be empty when checking ACLs in bulk

[stanjs]

I encountered the error when using Databricks CE to log experiments from mlflow. It worked perfectly fine before, but now I cannot open any of my experiments. I tried clean the cookies, change the browser, and create a new account to manually create a new experiment, but this error persisted. It seems to be a universal issue, how can I resolve that?

[Kaniz]

Hi @stanjs, I understand that you’re facing issues with accessing your MLflow experiments in Databricks CE. Let’s troubleshoot this together.

Here are some steps you can take to resolve the issue:

1. Check Experiment Permissions:

   • With the extension of MLflow experiment permissions to artifacts, you must have explicit permission to access artifacts of an MLflow experiment.
   • If you encounter a “PERMISSION_DENIED” error, it suggests that you do not have permission to access the experiment’s artifacts.
   • Ask the experiment owner to grant you the appropriate level of permissions to access the experiment¹.

2. Verify MLflow Configuration:

   • Ensure that your MLflow configuration is correctly set up.
   • If you’re using Databricks, make sure you’ve configured the tracking URI to point to Databricks. You can do this using mlflow.set_tracking_uri('databricks').
   • If you haven’t configured the CLI yet, run /opt/project/mlflow_test.py configure to set it up².

3. Artifact Access and MLflow Client Version:

   • Artifacts stored in dbfs:/databricks/mlflow-tracking/ can only be accessed using MLflow client version 1.9.1 or above.
   • If you’re using an older version, consider upgrading to MLflow client version 1.9.1 or higher to dow...³.

4. Create a New Workspace Experiment:

   • To create a new workspace experiment using the Databricks UI:
     • Click on “Workspace” in the sidebar.
     • Navigate to the folder where you want to create the experiment.
     • Right-click on the folder and select “Create > MLflow experiment.”
     • Enter a name for the experiment and an optional artifact location.
     • Click “Create.”
   • You can also create a new workspace experiment from the Experiments page by using the drop-down menu⁴.

[stanjs]

Hello, thx for your reply but it seems to me that this issue lies in Databricks CE UI itself. I have no permission denied error and I can still manually download all experiments from Databricks. I can also access the server with `mlflow.login()` and log in new experiments, but I cannot navigate them on Databricks CE's UI. I tried directly create new experiments using the UI and I asked several friends to try this, but they all encountered the same `

BAD_REQUEST: ExperimentIds cannot be empty when checking ACLs in bulk`.