Learning Journal

In this video, we cover Delta Lake's DELETE and UPDATE operations, and how to design idempotent pipelines that are safe to retry without creating duplicate or inconsistent data. These are the building blocks of production-grade Delta Lake pipelines that can recover gracefully from failures.

This is video L8 in the Delta Lake Complete Guide 2026 series.

What we cover in this video: ▸ Row-level DELETE in Delta Lake — syntax and behaviour ▸ Conditional DELETE — removing rows matching complex predicates ▸ Row-level UPDATE — partial updates on Delta tables ▸ How DELETE and UPDATE interact with the transaction log ▸ What idempotency means in a Delta Lake context ▸ Designing idempotent write patterns — merge-based and overwrite-based ▸ Why idempotency matters for pipeline fault tolerance and retries

By the end of this video, you will be able to safely delete and update rows in Delta tables and design pipelines that handle retries and failures without corrupting data.

━━━━━━━━━━━━━━━━━━━━━━━━━ 🔗 LINKS ━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ Spark Performance Tuning course: www.scholarnest.com ▸ Generative AI for Data Engineers course: www.scholarnest.com

━━━━━━━━━━━━━━━━━━━━━━━━━ 📌 ABOUT THIS SERIES ━━━━━━━━━━━━━━━━━━━━━━━━━ The Delta Lake Complete Guide 2026 is a free, structured 11-part series for data engineers who want to go beyond the basics. Every video is recorded as part of a full Databricks on AWS course — launching on Udemy on 15 July 2026.

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━━━━━━━━━━━━━━━━━━━━━━━━━ 👤 ABOUT THE INSTRUCTOR ━━━━━━━━━━━━━━━━━━━━━━━━━ Data engineer and architect with 25 years of industry experience. I create self-paced courses on Apache Spark, Databricks, Kafka, and Generative AI for data engineers.

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