Microsoft Fabric Data Engineer Associate DP-700 Practice Question
A Fabric solution ingests telemetry from IoT devices at a sustained rate of 250 000 events per second. You use an Eventstream to land the data into a Fabric Eventhouse table that analysts query with T-SQL. During peak traffic, analysts report slow query response times even after data has fully landed. Investigation shows that events often arrive several minutes late, causing multiple small, temporally-overlapping segments to be created in the table.
You need to improve both data-write and query performance while keeping compute consumption as low as possible.
Which change should you implement first?
Create a materialized view on the Eventhouse table that pre-aggregates the most common queries.
Scale the SQL analytics endpoint of the workspace to a higher capacity tier during peak hours.
Increase the number of physical partitions in the Eventhouse to match the number of IoT devices.
Enable the Optimize for out-of-order data feature on the destination Eventhouse table.
Eventhouse tables write incoming data into compressed columnar segments. When events arrive out of order-as is typical with IoT telemetry-the engine may create many segments whose timestamp ranges overlap, reducing compression and preventing effective segment pruning. Enabling the Optimize for out-of-order data setting buffers late-arriving events and periodically rewrites segments so that data is stored in near-temporal order. This improves compression, reduces the volume of data scanned by timestamp-filtered queries, and lowers overall compute use.
Creating materialized views can speed up specific queries but does not fix the underlying write-path inefficiency. Simply scaling the SQL analytics endpoint or increasing physical partitions can raise throughput or cost, yet unordered segments will still force larger scans and slow queries.
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What is the purpose of the 'Optimize for out-of-order data' feature in Eventhouse tables?
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Why does out-of-order IoT telemetry cause performance issues in Eventhouse tables?
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What are columnar segments, and how do they affect query performance in Eventhouse tables?
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Microsoft Fabric Data Engineer Associate DP-700
Monitor and optimize an analytics solution
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