Closed MarcAHunt closed 7 months ago
Yes, I am aware of this current limitation. This capability will be added in a future version (you will have another parameter to set the workspace for the new semantic model). Stay tuned...!
From: MarcAHunt @.> Sent: Wednesday, April 10, 2024 4:05:36 PM To: m-kovalsky/fabric_cat_tools @.> Cc: Subscribed @.***> Subject: [m-kovalsky/fabric_cat_tools] migrate_tables_columns_to_semantic_model - source- and target semantic models in different workspaces (Issue #2)
Hi m-kovalsky,
first of all thx for this great tool.
I have a small issue with migrating tables and columns to another semantic model.
It all works fine if source- and target-semantic-model reside in the same workspace, but I can not seem to get it to work if my target-semantic-model is in a different workspace.
What I actually would want to achieve is building new semantic models in a dev-workspace, once I am fine with it, push them to a production-workspace. Your tool indicates this could be possible.
Here is what I'm doing (copied of notebook cell): import fabric_cat_tools as fct import time
newDatasetName = 'targetSM' #Enter the new Direct Lake semantic model name """ comment -> I can create the newDataset in any workspace I want. """ fct.create_blank_semantic_model(newDatasetName, workspaceName='DevWS')
time.sleep(5)
""" comment -> re-creates all tables and columns of source_semantic_model (=param 1) in target_semantic_model (=param 2) -> lakehouseName and lakehouseWorkspaceName define the workspace and lakehouse where the data should be coming from. (Switching datasource, all fine!)
-> PROBLEM: It does not seem to work if source- and target-semantic-model do not reside in the same workspace! """ fct.migrate_tables_columns_to_semantic_model( 'sourceSM', 'targeSM', workspaceName= 'DevWS', lakehouseName= 'LH_Gold', lakehouseWorkspaceName='ProdWS')
fct.migrate_model_objects_to_semantic_model('sourceSM', 'targetSM', workspaceName= 'DevWS')
I am not sure if that's an issue. Could be a feature.
Thx a million for a feedback.
Best Regards from Germany, Marc
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Great. Thx. Any timeline?
Best Regards, Marc
Would you try using a beta version of 0.3.0 in this folder, along with the accompanying notebook. Note that parameter names have changed so following the new notebook will help with that.
https://github.com/m-kovalsky/fabric_cat_tools/tree/main/testing
It works like charm. Can't emphasis how much this is appreciated.
My test-case is as follows: In a dev-workspace I build a lakehouse and from that a new semantic-model and report.
Now, I want to bring it in production (separation of data and report workspaces) I am setting these vars:
dataset_name = 'my_dev_semantic_model' #Original or source semantic-modelworkspace_name = 'my_dev_workspace' #Workspace were source semantic-model residesnew_dataset_name = 'my_new_semantic_model_to_be_created' #New target semantic-model to be creatednew_dataset_workspace_name = 'my_prod_workspace' #Workspace were new target semantic-model is to be created
*lakehouse_name = 'my_prod_lakehouse' #Production lakehouse, of course holding the same schema as dev-lakehouselakehouse_workspace_name = 'my_prod_workspace_for_lakehouse' #Workspace of prod-lakehousenew_report_name = 'my_new_report_copied_from_dev_report_but_still_bound_to_dev_semantic_model'
'my_prod_report_workspace' #Workspace of report*
My findings:
fct.report_rebind( report = report_name ,new_dataset = new_dataset_name ,workspace=workspace_name)
I found these working parameters to run it against a different workspace: f
ct.report_rebind( report = new_report_name ,dataset = new_dataset_name ,dataset_workspace = new_dataset_workspace_name ,report_workspace=new_report_workspace_name) Would be great if example could be adjusted to all possible (and optional) parameters
But hey! You saved my day and a lot of manual work in my job. Thank you so much, Marc
Am Mo., 15. Apr. 2024 um 21:40 Uhr schrieb m-kovalsky < @.***>:
Would you try using a beta version of 0.3.0 in this folder, along with the accompanying notebook. Note that parameter names have changed so following the new notebook will help with that.
https://github.com/m-kovalsky/fabric_cat_tools/tree/main/testing
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-- Marc A. Hunt Rainerstr. 7 83059 Kolbermoor Mobil: +49 (0) 172 176 06 59 Email: @. @.>mail.com
Great to hear and thank you for testing! The notebook and documented parameters will all be updated once I release this new version. The pip install was still aligned to the main site instead of /testing so glad you used the correct pip install link.
You are very welcome.
One more question: Do you see any possibility to make this work for semantic-models based on warehouses instead of lakehouses? Currently it does seem to work.
Thx
Am Di., 16. Apr. 2024 um 09:59 Uhr schrieb m-kovalsky < @.***>:
Great to hear and thank you for testing! The notebook and documented parameters will all be updated once I release this new version. The pip install was still aligned to the main site instead of /testing so glad you used the correct pip install link.
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-- Marc A. Hunt Rainerstr. 7 83059 Kolbermoor Mobil: +49 (0) 172 176 06 59 Email: @. @.>mail.com
This is intended for migrating to Direct Lake which is predicated on a lakehouse, not a warehouse. If you are thinking of another idea, please explain further.
Btw, 0.3.0 is available and the function documentation has been updated.
From: MarcAHunt @.> Sent: Tuesday, April 16, 2024 10:14:08 AM To: m-kovalsky/fabric_cat_tools @.> Cc: Michael Kovalsky @.>; Comment @.> Subject: Re: [m-kovalsky/fabric_cat_tools] migrate_tables_columns_to_semantic_model - source- and target semantic models in different workspaces (Issue #2)
You are very welcome.
One more question: Do you see any possibility to make this work for semantic-models based on warehouses instead of lakehouses? Currently it does seem to work.
Thx
Am Di., 16. Apr. 2024 um 09:59 Uhr schrieb m-kovalsky < @.***>:
Great to hear and thank you for testing! The notebook and documented parameters will all be updated once I release this new version. The pip install was still aligned to the main site instead of /testing so glad you used the correct pip install link.
— Reply to this email directly, view it on GitHub https://github.com/m-kovalsky/fabric_cat_tools/issues/2#issuecomment-2058472765, or unsubscribe https://github.com/notifications/unsubscribe-auth/BHXG2MMH254KFFAS3UFH3FLY5TK4PAVCNFSM6AAAAABGANGHDOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDANJYGQ3TENZWGU . You are receiving this because you authored the thread.Message ID: @.***>
-- Marc A. Hunt Rainerstr. 7 83059 Kolbermoor Mobil: +49 (0) 172 176 06 59 Email: @. @.>mail.com
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Hi m-kovalsky,
first of all thx for this great tool.
I have a small issue with migrating tables and columns to another semantic model.
It all works fine if source- and target-semantic-model reside in the same workspace, but I can not seem to get it to work if my target-semantic-model is in a different workspace.
What I actually would want to achieve is building new semantic models in a dev-workspace, once I am fine with it, push them to a production-workspace. Your tool indicates this could be possible.
Here is what I'm doing (copied of notebook cell): import fabric_cat_tools as fct import time
newDatasetName = 'targetSM' #Enter the new Direct Lake semantic model name """ comment -> I can create the newDataset in any workspace I want. """ fct.create_blank_semantic_model(newDatasetName, workspaceName='DevWS')
time.sleep(5)
""" comment -> re-creates all tables and columns of source_semantic_model (=param 1) in target_semantic_model (=param 2) -> lakehouseName and lakehouseWorkspaceName define the workspace and lakehouse where the data should be coming from. (Switching datasource, all fine!)
-> PROBLEM: It does not seem to work if source- and target-semantic-model do not reside in the same workspace! """ fct.migrate_tables_columns_to_semantic_model( 'sourceSM', 'targeSM', workspaceName= 'DevWS', lakehouseName= 'LH_Gold', lakehouseWorkspaceName='ProdWS')
fct.migrate_model_objects_to_semantic_model('sourceSM', 'targetSM', workspaceName= 'DevWS')
I am not sure if that's an issue. Could be a feature.
Thx a million for a feedback.
Best Regards from Germany, Marc