Individual skill
fabric-spark-compute-perf-remediate
Diagnose and resolve performance issues in Microsoft Fabric Delta Lake and Spark workloads. Use when remediate slow Spark notebooks, long-running Spark jobs, Delta table query degradation, small file problems, VOrder configuration, resource profile tuning, autotune configuration, capacity throttling (HTTP 430), session startup delays, executor memory errors, skewed partitions, or streaming ingestion bottlenecks. Covers Lakehouse, SQL analytics endpoint, Spark compute, environment configuration, Delta OPTIMIZE, VACUUM, Z-Order, bin-compaction, and Fabric capacity SKU sizing.
skills/fabric-spark-compute-perf-remediate/SKILL.md
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- Last checked
- Nov 6, 2026
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- 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
- data Derived category
- data-databases Derived category
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LICENSE.txtdoc · 11,358 bytesSKILL.mdcore · 10,607 bytesSKILL.mdcore · 10,607 bytesSKILL.mdcore · 10,607 bytesreferences/capacity-throttling.mddoc · 4,146 bytesreferences/delta-table-health.mddoc · 6,783 bytesreferences/general-tuning.mddoc · 5,980 bytesreferences/memory-compute.mddoc · 4,993 bytesreferences/read-optimization.mddoc · 4,521 bytesreferences/session-startup.mddoc · 4,218 bytesreferences/streaming-perf.mddoc · 5,028 bytesscripts/Diagnose-DeltaTableHealth.ps1runs · 4,933 bytesscripts/Get-SparkCapacityStatus.ps1runs · 4,635 bytesscripts/Invoke-TableMaintenance.ps1runs · 6,322 bytestemplates/perf-diagnostic-notebook.pyruns · 8,497 bytes
Read excerpt
# Fabric Delta Lake & Spark Performance remediate
Systematic remediate toolkit for diagnosing and resolving performance issues across
Microsoft Fabric Spark compute, Delta Lake tables, and Lakehouse workloads.
## When to Use This Skill
- Spark notebooks or jobs running slower than expected
- Delta table queries degrading over time (small file problem)
- Capacity throttling errors (HTTP 430 / TooManyRequestsForCapacity)
- Session startup taking minutes instead of seconds
- Out-of-memory errors on executors or drivers
- Streaming ingestion falling behind or producing small files
- VOrder or resource profile misconfiguration
- Deciding between read-heavy vs. write-heavy workload profiles