Cannot reference a Notebook "that attaching" to a different default lakehouse.

[todd-wilson]

I'm running a pipeline starting with a DAG. And getting an error I can't reference a notebook "that attaching to a different default lakehouse". I've tried passing "useRootDefaultLakehouse": True on runMultiple to ignore the error (although I don't prefer this) and configuring a default lakehouse for every script. I also tried removing and reattaching the lakehouse to all my notebooks. Any suggestions on how to fix this?

mssparkutils.notebook.runMultiple(DAG, {"displayDAGViaGraphviz": False, "DAGLayout": "spectral"})

%%configure -f

                 "name": '<lakehouse name>',

                 "id": '<lakehouse id>',

                 "workspaceId": '<workspace id>'

             }

 }

Notebook execution failed at Notebook service with http status code - '200', please check the Run logs on Notebook, additional details - 'Error name - Py4JJavaError, Error value - An error occurred while calling z:notebookutils.notebook.runMultiple.
: com.microsoft.spark.notebook.msutils.NotebookExecutionException: Cannot reference a Notebook that attaching to a different default lakehouse. You can pass the parameter useRootDefaultLakehouse to ignore it, for example in run API: mssparkutils.notebook.run('child_nb', 90, {'useRootDefaultLakehouse': True}), in runMultiple API, please run mssparkutils.notebook.help('runMultiple') for more details. You can check driver log or snapshot for detailed error info! See how to check logs: https://go.microsoft.com/fwlink/?linkid=2157243 .

[todd-wilson]

Thank you for the reply. RunMultiple doesn't work because of dependencies. I did run all of these in sequence and the notebook which loads from the bronze dlh to the silver dlh is the issue.

This error occurs if I use the notebook in the DAG and use runMultiple or if I run the notebook via a single run command. If I just run the notebook in a session without using mssparkutils it completes without error.

How can I make sure both reference to my bronze and silver datalake houses are present in my silver notebook? I have added the bronze dlh to my silver notebook, but the issue is persisting. 😞

[todd-wilson · Accepted solution]

So I fixed this by adding "useRootDefaultLakehouse": True arg to my dag under my silver script.

            "args": {

                "useRootDefaultLakehouse": True

            }

Larger snippet...

 {

            "name": "notebook_silver",

            "path": "Notebook Silver",

            "timeoutPerCellInSeconds": 3600,

            "dependencies": ["Notebook Bronze"],

            "args": {

                "useRootDefaultLakehouse": True

            },

        }

My notebook uses absolute abfss paths to access the bronze datalake and the silver datalake so I think it should have worked according to the docs.

"To specify the location to read from, you can use the relative path if the data is from the default lakehouse of your current notebook. Or, if the data is from a different lakehouse, you can use the absolute Azure Blob File"

Load data into your lakehouse with a notebook - Microsoft Fabric | Microsoft Learn

[Anonymous]

Thank you for sharing the solution with us!

[Anonymous]

Hi @todd-wilson 

If you run a notebook directly with below code (not calling by data pipeline), will it run successfully?

%%configure -f
{
    "defaultLakehouse": {
        "name": "<lakehouse name>",
        "id": "<lakehouse id>",
        "workspaceId": "<workspace id>"
    }
}

In addition, if you don't use a DAG in the data pipeline, just run multiple notebooks concurrently like below, will it run successfully?

mssparkutils.notebook.runMultiple(["notebook1", "notebook2", "notebook3"])

How many notebooks are running concurrently? Is it possible to reduce some notebooks or run them separately to check if this error occurs on a specific notebook or may occur on each notebook? 

Best Regards,
Jing

Community Support Team