Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You need a Microsoft Fabric pipeline to load data daily from an Azure SQL Database table into a Delta table in a Lakehouse. The source has an integer LastModifiedVersion column that increases on each change. The load must copy only rows modified since the previous run and merge them into the Delta table, inserting new rows and updating matches. Which design meets the requirements with the least custom code?
A stored procedure activity that calls a SQL stored procedure to read changed rows and write them into the Lakehouse by using a PolyBase external table
A single Copy activity that uses LastModifiedVersion as a watermark column and the Upsert update method when writing to the Lakehouse Delta table
A pipeline that creates a shortcut to the source table and lets reports read the data directly through the shortcut
A pipeline that copies the full source table into a staging Lakehouse folder and then runs a Spark notebook with a MERGE INTO statement
The Copy activity natively supports incremental extraction as well as upsert into a Delta-format Lakehouse table. By configuring the activity to use the LastModifiedVersion column as the watermark, only rows with higher values than the stored maximum are read. When the sink is a Lakehouse Delta table, the Upsert update method merges incoming rows based on a designated key, inserting new rows and updating matches. A notebook could also perform the operation but would require custom Spark code, a stored procedure cannot write directly to a Delta table through PolyBase, and shortcuts do not move data.
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Microsoft Fabric Data Engineer Associate DP-700
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