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Charline_74's avatar
Charline_74
Resolver I
1 year ago
Solved

Change Default Lakehouse

Hello, In a notebook which is in DEV I use this code to get the ID of the Lakehouse in DEV and the ID of the Workspace DEV : df_Lakehouse = labs.list_lakehouses() lakehouse_row = df_Lakehouses[df_...
data engineering
lakehouse
notebook
  • nilendraFabric's avatar
    nilendraFabric
    1 year ago

    Hi Charline_74 

    To change the default lakehouse in a Microsoft Fabric notebook, you can use the %%configure magic command with the defaultLakehouse parameter. However, the issue in your code is that you're trying to use Python variables directly within the JSON configuration, which isn't possible. Instead, you need to format the JSON string with the variable values.

     

    could you please give this a try :


    df_Lakehouses = labs.list_lakehouses()
    lakehouse_row = df_Lakehouses[df_Lakehouses["Lakehouse Name"] == "Lakehouse"]
    lakehouse_id = lakehouse_row.iloc[0]["Lakehouse ID"]
    workspace_id = spark.conf.get("trident.workspace.id")

    %%configure -f
    {
    "defaultLakehouse": {
    "name": "Lakehouse",
    "id": "%s",
    "workspaceId": "%s"
    }
    }
    """ % (lakehouse_id, workspace_id)


    Please give kudos and mark this as solution if this helps.

    Thanks

ObungiNiels's avatar
ObungiNiels
Resolver III
1 year ago

Hi Charline_74 , 

I just tried it out and you can change the notebook definition including metdata using notebookutils, so we don't even need to explicitely invoke an API call. 🙂 

 

This is what worked for me: 

 

 

import sempy.fabric as fabric

# INSERT YOUR WORKSPACES SPECIFIC INFORMATION HERE

workspace_name = "workspace_id"
item_name = "notebook_name"

replacement_dict = {
    "lakehouse_id" : {
        "old" : "LH_ID_old",
        "new" : "LH_ID_new",
    },
    "lakehouse_name" : {
        "old" : "LH_old",
        "new" : "LH_new",
    },
    "workspace_id_of_lakehouse" : {
        "old" : "workspace_id_old",
        "new" : "workspace_id_new",
    },
}

workspace_id = fabric.resolve_workspace_id(workspace_name)
items = fabric.list_items(workspace=workspace_name)
item_id = items.where(items["Display Name"] == f"{item_name}").dropna().Id.item()
item_type = items.where(items["Display Name"] == f"{item_name}").dropna().Type.item()

definition = notebookutils.notebook.getDefinition(item_name, workspace_id)

for replacement in replacement_dict.keys():
    definition = definition.replace(replacement_dict[replacement]["old"], replacement_dict[replacement]["new"])

notebookutils.notebook.updateDefinition(name=item_name, content=definition, workspaceId=workspace_id)

 

This is essentially doing a search and replace in the current definition of your notebook and overwrites the specific part concerning the default lakehouse. If your items are in the same workspace you could skip the "workspace_id_of_lakehouse" key in the dict since it doesn't need to be changed. 

 

We found great success using these commands to change information which for instance cannot be parametrized during deployment via (the current form of) deployment pipelines. 

 

Hope this helps you out. 🙂