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fabric-lakehouse-views-perf-remediate

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Troubleshoot Microsoft Fabric materialized lake views (MLV) performance issues including slow refresh, incremental refresh failures, full refresh fallback, Spark job failures, lineage execution errors, data quality constraint violations, and optimal refresh configuration. Use when diagnosing MLV refresh duration, monitoring MLV runs in Monitor Hub, analyzing Spark logs for MLV failures, enabling change data feed (CDF), resolving delta table not found errors, or optimizing MLV query definitions for incremental refresh eligibility. Covers Spark SQL syntax, TBLPROPERTIES, PARTITIONED BY, CONSTRAINT CHECK ON MISMATCH DROP/FAIL, and custom environment configuration.

skills/fabric-lakehouse-views-perf-remediate/SKILL.md

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Jun 7, 2026
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# Fabric Materialized Lake Views Performance remediate

Diagnose and resolve performance issues with materialized lake views (MLVs) in Microsoft Fabric lakehouses. This skill covers refresh optimization, Spark job diagnostics, data quality constraint tuning, and lineage execution remediate.

## When to Use This Skill

- MLV refresh runs are taking longer than expected
- Incremental refresh is falling back to full refresh unexpectedly
- MLV lineage execution shows Failed or Skipped nodes
- Spark jobs for MLV refresh are failing with errors
- "Delta table not found" errors during MLV creation or refresh
- Data quality constraints causing unexpected pipeline failures
- Need to enable or verify optimal refresh configuration
- Custom Spark environment tuning for MLV workloads
- Monitoring and interpreting MLV run history
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