Microsoft Fabric Data Engineer Associate DP-700 Practice Question

Query performance in an Eventhouse (based on Azure Data Explorer) is strongly influenced by the size and number of data extents. Many very small extents force the engine to open and scan more files, increasing latency. The recommended way to avoid this is to adjust the ingestion batching policy so that incoming data is combined into larger batches (for example by increasing maximum batch time or size). Larger, fewer extents are more efficient for both data management operations and query execution, and the policy takes effect transparently without pausing the Eventstream. Reducing the Eventstream output window to 500 ms would create more small batches, worsening the issue. Creating an update policy adds storage and compute overhead but does not solve the underlying extent fragmentation. Enabling change data capture affects downstream data movement only and has no impact on query execution speed.