Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You manage an eventstream in Microsoft Fabric that ingests JSON telemetry from Azure Event Hubs and writes the data to an existing Delta table called sensor_readings in a lakehouse. A new humidity attribute has been added to the incoming events. Soon after the change, the eventstream status changes to Stopped (Error), and the Diagnostics pane shows the message "Write operation failed. Column 'humidity' not found in target table." No events are reaching the lakehouse. You need to restore the eventstream to a healthy state so that new events continue to be ingested without losing the humidity data. What should you do?
Increase the Max writer wait time and restart the eventstream to clear the blockage.
Delete and recreate the lakehouse table so that the eventstream can automatically generate a new schema on the next run.
Execute an ALTER TABLE statement on sensor_readings to add a humidity column with the correct data type, then resume the eventstream.
Modify the eventstream to drop the humidity field from its output mapping and republish the stream.
The sink fails because the humidity field that now exists in the incoming JSON is missing from the sensor_readings Delta table. Eventstreams do not provide automatic schema-evolution for existing tables, so the column must be added manually. Execute an ALTER TABLE statement to add a humidity column of the appropriate data type, then resume the eventstream. After the schema aligns, new events will be written successfully. Removing the field from the output mapping does not stop the data from being ingested, deleting and recreating the table risks data loss, and increasing the Max writer wait time cannot resolve a schema mismatch.
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What is schema-evolution in Microsoft Fabric eventstreams?
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What happens if you drop fields from the output mapping in an eventstream?
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Microsoft Fabric Data Engineer Associate DP-700
Monitor and optimize an analytics solution
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