fabric-notebook-perf-remediate

Tune Apache Spark in Fabric notebooks by applying automated health checks and remediation workflows that diagnose slow cells and timeouts, adjusting configurations for Native Execution Engine, V-Order, and memory pressure to speed up execution.

Resolving data skew and out of memory errors in Fabric Spark involves running diagnostic workflows that apply automated tuning and step-by-step remediation, capturing configuration recommendations to align capacity management and prevent HTTP 430 throttling.

Adaptive Query Execution improves Spark performance by dynamically optimizing query plans during runtime, and this Skill provides specific health-check tooling and configuration recommendations to apply AQE alongside V-Order and Delta table optimization.

You can use pyspark scripts to automate Delta table optimization and health checks by inserting the provided Spark configuration template as the first cell in your notebook, running the health check script, and applying the recommended settings.

Fabric notebooks experience HTTP 430 throttling due to capacity limits, which you can fix by applying the Skill's capacity management remediation steps and monitoring guidance to align configurations and reduce execution bottlenecks.