Using Spark to accelerate your lakehouse architecture with Fabric
summary
Microsoft Fabric shows how to build a lakehouse that auto-creates Delta tables, exposes a SQL endpoint and semantic dataset, and lets you add S3 data via shortcuts without copying. The Spark runtime upgrades to Spark 3.3.1 and Delta 2.2, offers partition caching, Autotune that makes some customer jobs run two times faster, starter pools that give ~10–15 second notebook starts, upcoming high‑concurrency sessions, VS Code integration, notebook Spark advisor, and Data Wrangler scaling.
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chapters (15)
- 0:00Start
- 2:43Data ingestion into lakehouse
- 3:37Lakehouse security
- 3:54Lakehouse sharing
- 7:47Fabric runtime
- 8:50Performance by default
- 10:36Spark admin settings
- 14:52Notebook overview
- 16:09Data wrangler
- 16:52Copilot integration
- 20:15VS Code integration
- 20:57Spark job definiton
- 24:30Enterprise information management
- 25:14Spark monitoring
- 25:45Capacity metrics reporting
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