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PatrickGallucci
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fabric-lakehouse-views-perf-remediate

Diagnose and remediate Microsoft Fabric materialized lake view performance issues.

16|1|Updated Feb 10, 2026
Search Tags:#performance#monitoring#diagnostics#spark#fabric#lakehouse#mlv
One-click install
npx skills add https://github.com/PatrickGallucci/fabric-skills --skill fabric-lakehouse-views-perf-remediate
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fabric-lakehouse-views-perf-remediate
Source: https://github.com/PatrickGallucci/fabric-skills/tree/main/skills/fabric-lakehouse-views-perf-remediate
Command: npx skills add https://github.com/PatrickGallucci/fabric-skills --skill fabric-lakehouse-views-perf-remediate

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Diagnoses and remediates performance issues in Microsoft Fabric materialized lake views (MLVs), covering slow refresh, incremental vs full refresh, Spark job failures, lineage execution problems, and data quality constraint failures.

Core Features & Use Cases

  • Diagnose slow MLV refresh and identify bottlenecks across the lineage.
  • Enable and verify optimal refresh configuration, including CDF status across source tables.
  • Provide step-by-step remediation workflows and reference materials for Spark environment tuning.

Quick Start

Load this skill and run the diagnostic notebook against the target lakehouse to begin diagnosing MLV performance issues and apply recommended remediations.

Frequently Asked Questions about fabric-lakehouse-views-perf-remediate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why is my Fabric materialized lake view refresh slow and how can I diagnose it?▼

Fabric materialized lake view refresh slows when bottlenecks exist across the lineage or Change Data Feed is disabled. Run diagnostic scripts against the target lakehouse to identify slow refresh issues and apply recommended remediations.

How do I enable Change Data Feed for Fabric lakehouse tables to fix MLV refresh failures?▼

Change Data Feed for Fabric lakehouse tables is enabled by setting the delta.enableChangeDataFeed property. Verify CDF status across source tables to ensure incremental refresh works properly and reduce full refresh overhead.

What's the best way to troubleshoot Spark job failures during Fabric lakehouse view refresh?▼

Troubleshoot Spark job failures during Fabric lakehouse view refresh by monitoring runs in Monitor Hub and applying step-by-step remediation workflows. Reference materials guide Spark environment tuning and partitioning strategies.

Do I need to configure PARTITIONED BY for Fabric materialized lake views to improve performance?▼

Configuring PARTITIONED BY for Fabric materialized lake views optimizes refresh performance by organizing data distribution. Familiarity with MLV definitions and relevant properties like PARTITIONED BY is required for effective remediation.

What causes lineage execution errors in Fabric materialized lake views and how do I fix them?▼

Lineage execution errors in Fabric materialized lake views stem from misconfigured source tables or failed Spark jobs. Diagnose bottlenecks across the lineage and verify CDF status to remediate execution problems.

Can incremental refresh work without Change Data Feed enabled on Fabric lakehouse source tables?▼

Incremental refresh for Fabric lakehouse materialized views requires Change Data Feed enabled on source tables. Without the delta.enableChangeDataFeed property, the system falls back to full refresh, increasing processing time.

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