Multi-Cluster Warehouse Scaling for Concurrent Queries and Fault Resilience

The patent divides the warehouse into multiple independent clusters, each capable of handling queries autonomously. This segmentation enables parallel query processing across clusters, significantly improving concurrency while maintaining manageable complexity through modular architecture. Each cluster operates as an independent unit with its own compute resources, allowing the system to scale horizontally.

The patent extracts compute resources from their tight coupling with storage resources, creating independent compute clusters that can be scaled and managed separately. This extraction allows the system to adapt compute capacity independently of storage capacity, enabling flexible resource allocation. The complexity of managing separate resource pools is offset by the significant gain in scaling flexibility and resource optimization.

The patent implements dynamic resource allocation where compute clusters can be added, removed, or scaled based on real-time workload demands. The system monitors query queues and workload metrics, automatically adjusting cluster capacity to match demand. This dynamic approach improves workload handling efficiency by ensuring adequate compute resources are available during peak periods while reducing resources during low-demand periods, optimizing both performance and cost.

The patent segments the query routing across multiple clusters, distributing query traffic based on cluster availability, load conditions, and data locality. This segmentation provides fault resilience by allowing queries to be rerouted to healthy clusters if one fails, and improves availability by enabling parallel query processing. The routing complexity is managed through systematic load balancing algorithms that consider multiple factors including cluster health, current load, and data placement.