![]() I checked as well - same error.Īfter the run reports success I go in and find that the address is not updated for the Lake Database table dbo.LocalPAtientAddress, but it is updated for the Azure SQL database table fhir.LocalPatientAddress. I tried a concatenation of 'fhir.' and $TableName (for which it does not error), and then attempt to query fhir.LocalPatient in the Lake Database. I am using dynamic tables so enabling mapping is not an option. I added the schema to the Lake database, but there is no option for specifying the schema in the data flow. I would rather they are on the fhir schema. When the pipeline runs these tables are created on the dbo schema (as dbo.LocalPatient and dbo.LocalPAtientAddress). The relevant tables are fhir.LocalPatient and fhir.LocalPatientAddress from the Azure SQL database side. The second activity reports success, however the new data is not there (it still says 929). ![]() A subsequent select reveals the address does indeed now start with 930. If I then make a change in Fhir (example changing address from 930 to 929) and I run it again the first activity works and upserts the data to Azure SQL database. If the table doesn't exist it is created and populated with data appropriately. For which I have selected "Recreate table". In the settings of the lake sink there is only a single option "Table action". Second, in my 2nd dataflow activity I use Azure SQL database as the source, add a couple columns via derivedcolumn and sink the data to Azure Lake database. copy data from Azure SQL Server as source to Azure Lake as sink.įirst, is this the best practice flow? Is it necessary to have 2 dataflow activities to copy data from Fhir (via a CDM source) to Azure SQL database and then to Azure Lake database? I feel like there are efficiencies to be had. copy data from Fhir as source to Azure SQL Server as sink and 2. I have a pipeline set up in Synapse which runs 2 dataflow activities which is supposed to 1.
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