Mounting NB on- the-fly

Here is a solution which doesn't involve mounting or attaching Lakehouses to the Notebook:

Perhaps you can use temporary views to be able to work with Spark SQL without having a default Lakehouse for your Notebook.

In this example I have a Notebook without any default Lakehouse and without any mounted/attached lakehouses.

I create a dataframe to connect to data from a lakehouse using the abfss path, and create a temporary view based on that dataframe. 

df = spark.read.load("abfss://<workspaceID>@onelake.dfs.fabric.microsoft.com/<lakehouseID>/Tables/<tableName>")

df.createOrReplaceTempView("MyView_Read")

I use Spark SQL to do some modifications to the temporary view, and save it as another temporary view.

%%sql
CREATE OR REPLACE TEMPORARY VIEW MyView_Write AS SELECT *, Current_Timestamp as LoadTime FROM MyView_Read;

I create a new dataframe from the new temporary new.

I then write this new dataframe to another lakehouse table in another workspace.

df_write = spark.sql("SELECT * FROM MyView_Write")

df_write.write.mode("append").save("<anotherWorkspaceID>@onelake.dfs.fabric.microsoft.com/<anotherLakehouseName>/Tables/<anotherTableName>")​

This seems to work fine for me.