Dataset Beast Modes and Sandbox

DomoDork Contributor

From a sandbox perspective, I know that it doesnt actually promote/copy datasets from one instance (dev) to another instance (prod). However, we have some Dremio federated datasets currently in dev with a bunch of dataset calculations on them and we're trying to avoid having to re-create all the beast modes everytime we're ready to link/move in federated dataset into prod. I know you can duplicate/copy beast modes via the Beast Mode manager, but it seems that only targets datasets in the same instance.

Does anyone have any insights or ideas on how sandbox works with calculations on the datasets as far as the schema that does get mapped as part of the promotion process? I know beast modes are promoted with cards, but I cant find much information on dataset level calculations.

Or, is there some other non-convoluted that won't need us to create some custom programmatic API way to copy dataset beast modes between instances?



  • GrantSmith
    GrantSmith Coach
    edited July 2023

    Per the KB article ( :

    What happens to data when promoting content with Sandbox?

    Sandbox moves content, not data. The best practice is to keep the data in the production instance and make it available in the development instance using either Virtual DataSets or the DataSet Copy Connector.

    Because the beast mode is stored on the dataset it won't get copied. Have you tried utilizing a dataset view and store the beast modes on that view instead of the dataset directly?

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  • DomoDork
    DomoDork Contributor
    edited July 2023

    Hey Grant,

    The source datasets are federated Dremio datasets so we're not actually copying data and federated datasets arent supported with virtual datasets. We don't want to copy data at all (since thats live data) and views seem to add alot of overhead on top of federated datasets. So we're just trying to figure out a way that if we add a beast mode in a dev copy of that federated dataset, we have an easy way to add that beastmode metadata to the same dataset in prod in a mroe automated fashion as some datasets will have 100+ standard calculations on them.