Individual skill
fabric-delta-spark-perf
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.
skills/fabric-delta-spark-perf/SKILL.md
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- Observed behavior
- Local scripts
- Last checked
- Nov 11, 2026
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- 17
- Repository last updated
- Jun 7, 2026
- License
- MIT
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- claude Repository topic
- claude-skills Repository topic
- copilot Repository topic
- copilot-skills Repository topic
- fabric Repository topic
- microsoft-fabric Repository topic
- operations Derived category
- data Derived category
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LICENSE.txtdoc · 11,358 bytesSKILL.mdcore · 8,348 bytesSKILL.mdcore · 8,348 bytesSKILL.mdcore · 8,348 bytesSKILL.mdcore · 8,348 bytesreferences/diagnostic-checklist.mddoc · 12,503 bytesreferences/spark-configurations.mddoc · 10,283 bytesreferences/table-maintenance-guide.mddoc · 11,556 bytesscripts/diagnose-delta-performance.pyruns · 12,670 bytesscripts/table-maintenance.pyruns · 9,423 bytestemplates/notebook-performance-template.pyruns · 6,062 bytes
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# Microsoft Fabric Delta Lake Spark Performance remediate
Systematic workflows for diagnosing and resolving Apache Spark and Delta Lake performance issues in Microsoft Fabric Lakehouse environments.
## When to Use This Skill
Activate when the user mentions any of the following:
- Spark job is slow, taking too long, or timing out
- Small file problem, too many small files, file fragmentation
- Data skew, straggler tasks, unbalanced partitions
- Out of memory (OOM) errors on driver or executor
- Shuffle spill, excessive shuffle read/write
- OPTIMIZE, VACUUM, bin-compaction, or table maintenance