Troubleshoot and optimize Delta Lake and Apache Spark performance in Microsoft Fabric. Use when diagnosing slow Spark jobs, small file problems, data skew, shuffle bottlenecks, out-of-memory errors, V-Order tuning, OPTIMIZE/VACUUM operations, partition strategy, resource profile selection (writeHeavy, readHeavyForSpark, readHeavyForPBI), autotune configuration, Native Execution Engine, broadcast joins, AQE (Adaptive Query Execution), or when Spark notebooks or Spark Job Definitions run slower than expected in Fabric Lakehouse workloads.
$npx -y skills add patrickgallucci/fabric-skills --skill fabric-delta-spark-perfInstalls into the current project.
Run `npx skills use "https://github.com/patrickgallucci/fabric-skills" --skill "patrickgallucci/fabric-skills/fabric-delta-spark-perf"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/patrickgallucci/fabric-skills" that are relevant to the current task. Run `npx skills add "https://github.com/patrickgallucci/fabric-skills"` and select the relevant skills, then follow their instructions.