Forum Discussion
Dataflow incremental refresh with primary key
I SO GLAD someone asked this question too!
Currently incremental refresh works for the data was updated based on datetime stamp, say last 10 days. It does not take into consideration the Primary Key that might have been inserted in the past.
Eg: lets say a "Sales Order" was created 3 months with a Status "Open", but only today its status was changed to "Shipped". Since I am only looking for past 10 days data for incremental refresh, a new Sales Order row gets inserted into the Dataset causing my "Sales Order" table to be duplicated.
How can we avoid this? Ideally along with the Datetime stamp, there needs to be a option where we specify the Unique Key column too. If incremental refresh contains any of the Unique Keys loaded in the past, they need to be deleted too and reinserted.
Hey SamRock,
Any update regarding consideration of primary key when incrementally refreshing? I have a similar situation and I am not sure Power BI dataflows can solve my issue.
- Hi there
Currently incremental refresh only works with dates and unfortunately not with a primary keyIs there any timeline for if/when it will be added as a feature for dataflows? This can be seen as a critical feature for refreshing data dependent on past state changes (i.e. Orders, Status, Deliveries, Inventory, Requests, etc)
The underlying technology for incremental refresh seems to be based on Partitions from SSAS. Therefore my guess is I don't think this will fundamentally change to support a primary key upsert any time soon.
Assuming therefore that when a record is updated it will appear in your incremental refresh therefore creating a duplicate you should add extra steps in your MCode to remove duplicates keeping the Max Primary Key therefore pruning the data in your Dataflows ETL process.
