fabric-spark-perf-remediate

Diagnose slow Fabric Spark notebooks by running systematic diagnostics across Spark UI, Monitoring Hub, and Delta Lake to identify performance bottlenecks. The workflow analyzes slow sessions and applies recommended tunings to accelerate execution and reduce queueing delays.

Fix Delta Lake data skew and small-files problems through end-to-end workflows for partitioning, table maintenance, and Delta Lake optimization. These workflows improve throughput and latency by addressing file distribution and data distribution bottlenecks directly.

Autotune for Fabric Spark capacity throttling applies integrated runtime features and resource profiles to optimize resource sizing. It provides tunings that address queueing delays and improve throughput across throttled Fabric workloads.

Use REST API-based diagnostics scripts to remediate Spark performance problems in Fabric. The scripts integrate with Fabric Spark runtime features and the Monitoring Hub to retrieve session data and apply performance tunings systematically.

Fabric Spark capacity throttling occurs when resource limits are exceeded, causing queueing delays. Resolve it by applying resource sizing, partitioning adjustments, and autotune configurations provided through end-to-end diagnostic workflows.

Access to Spark UI and Monitoring Hub is needed to perform systematic diagnostics across Fabric workloads. These tools provide the session metrics and telemetry required to identify bottlenecks and apply appropriate performance tunings.