I have set up a DLT with "testing" set as the target database. I need to join data that exists in a "keys" table in my "beta" database, but I get an AccessDeniedException, despite having full access to both databases via a normal notebook.

A snippet demonstrating the issue is below (Note that I don't appear to have the code snippet button available in Chrome):

The following would be data from the keys table:

```

key_df = spark.createDataFrame([[0, "State0"]], ['key', 'name'])

```

Then the DLT:

```

@dlt.table()

def dlt_test_data():

df = spark.createDataFrame([["40873", 0]], ['version', 'key'])

return df

@dlt.table()

def dlt_test_silver():

data_df = dlt.read("dlt_test_data")

key_df = enum_df = spark.table("beta.keys")

joined_df = data_df.join(key_df, "key")

return joined_df

```

I also tried importing the data in a view and reading from that in dlt_test_silver, but this also failed.

Is it possible to use other databases within a DLT pipeline? If so, how?