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Import Model To Direct Lake Migration #202

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cvlmonica opened this issue Oct 14, 2024 · 10 comments
Open

Import Model To Direct Lake Migration #202

cvlmonica opened this issue Oct 14, 2024 · 10 comments
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@cvlmonica
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While doing the migration from import mode to direct lake.
It is considering #Measures as calculated table and it is stopping the migration.

Image

What should we do here?!
Any suggestions so that the Semantic-Link-Labs ignores this!?

@cvlmonica cvlmonica added the bug Something isn't working label Oct 14, 2024
@m-kovalsky
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What is the '# Measure' table? Is it a regular data table? Does it have any columns? Please share more details on the properties of this table.

@cvlmonica
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Yes, It is an empty calculated table! to place all the measures at one place!
Since we cannot have an empty table in lakehouse? how to do this?

@m-kovalsky
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You need to create a sort of 'dummy' table in the lakehouse, as such, add it to the model, and place all the measures in that table.

import sempy_labs as labs
import pandas as pd

df = pd.DataFrame(columns=['NewCol'])
schema = {
    "NewCol": "str",
}
labs.save_as_delta_table(dataframe=df, delta_table_name="MeasuresTable", write_mode='overwrite', schema=schema)

@cvlmonica
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I have tried running the above script and created an measures table and when I trying to run the migrate_model_objects_to_semantic_model() function, it is throwing below error:

Few measures are getting created which are not part of that measures table.

Image

Image

With this, what is happening is it is breaking at this point and it cannot create other objects in semantic model!

@cvlmonica
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Hi! any solution on this?

@m-kovalsky
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m-kovalsky commented Oct 31, 2024

What is the Dax behind the '# measures' calculated table?

@cvlmonica
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This is an empty calculated table which we are storing the all the measures. So it is an empty calculated table!

@m-kovalsky
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Please share the DAX behind the calculated table

@cvlmonica
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cvlmonica commented Nov 14, 2024

Yes sharing the DAX
#Measures =

@m-kovalsky
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Where is the dax?

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