Tuning a Fabric warehouse for faster queries

Optimizing a Fabric data warehouse focuses on ensuring queries use efficient distribution and statistics, minimizing data movement, and using appropriate table structures and V-Order optimization. Monitoring tools like Query Insights, Dynamic Management Views (DMVs), and the Fabric Capacity Metrics app help identify bottlenecks such as long-running queries, resource contention, or skewed data distribution.

1 · Learn the must-know

• 1Fabric Warehouse automatically manages statistics, but you can manually update them using CREATE STATISTICS or UPDATE STATISTICS when auto-generated stats are stale or insufficient for complex queries.
• 2The queryinsights schema (exec_requests_history, exec_sessions_history, frequently_run_queries) provides historical query performance data useful for identifying slow or resource-intensive queries.
• 3V-Order is a write-time optimization applied to Parquet files in Fabric that improves compression and read performance for Power BI and SQL engines, and is enabled by default for Warehouse tables.
• 4Minimizing data movement is critical: use appropriate JOIN strategies and avoid unnecessary CROSS JOINs or SELECT * on large fact tables to reduce compute and I/O overhead.
• 5Result set caching can improve performance for repeated identical queries, but is invalidated whenever underlying table data changes, so it's most effective for stable reporting workloads.
• 6DMVs like sys.dm_exec_requests and sys.dm_pdw_exec_requests (in the Warehouse SQL endpoint) let you monitor active queries in real time to detect blocking, long-running operations, or excessive resource consumption.

2 · Check your understanding