Databricks Materialized View Demo: Incremental Refresh, Updates, Inserts, and Optimizer Behavior

Part 2 of the Databricks Materialized View demo series takes a closer look at refresh behavior after real data changes. In this video, we test multiple scenarios including single-row updates, multi-million-row updates, small date-based changes, and append-only inserts to see how Databricks handles materialized view maintenance. Along the way, we review performance metrics, scan pruning, event log details, and optimizer-driven decisions between row-based maintenance and complete recompute. If you want to understand how Databricks materialized views behave in real-world refresh scenarios, this demo walks through the details step by step. Topics covered: • Incremental refresh after source table updates • Row-based maintenance behavior • Append-only refresh behavior • Performance observations from bytes read and bytes written • Event log and planning details • Optimizer decision-making for refresh strategy Part 1 covered the foundational concepts. This follow-up focuses on what happens when those concepts are put into action. Part 1 - https://greenleafgrp.com/insights/dat... Green Leaf Consulting Group - https://greenleafgrp.com/solutions/da... #databricks #databrickstutorial #dataengineering #dataanalytics #dataoptimization #queryoptimization