Materialized View Refresh Path Analysis in Oracle Large-Scale Warehouses

Abstract

Materialized views play a critical role in large-scale Oracle data warehouses by enabling efficient
analytical query performance through precomputed summaries. However, the refresh behavior of
materialized views is highly sensitive to schema design, workload change patterns, and platform
deployment architecture. This study analyzes refresh paths under varying configurations, including
incremental and complete refresh strategies, partitioned and unpartitioned fact tables, and single
instance, RAC, and autonomous environments. The results show that incremental refresh achieves
optimal performance when change activity remains localized within partition boundaries, while non
local updates and missing dependency logs trigger fallback to complete refresh, significantly increasing
resource cost. Dependency chain length and platform coordination overhead further influence refresh
stability. These findings highlight the importance of refresh-aware schema planning and workload
driven scheduling to maintain scalable and predictable warehouse performance.