Coordinator Server for Distributed Operation Deduplication
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Solution Overview
Problem
Deduplication techniques are difficult to apply across distributed computing systems, leading to unnecessary duplication of data and resources due to the lack of knowledge among compute or storage clusters about previously processed operations.
Innovation Solution
A server applies a mapping function to operation parameters to produce a mapping value in a target mapping space, partitioned among target servers proportional to their resource capacities, ensuring that operations are directed to the appropriate server for deduplication, even if a server becomes unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If deduplication techniques are applied within a single storage cluster, then data duplication is reduced within that cluster, but data may still be unnecessarily replicated across multiple storage clusters
Solution Approach 1:
The patent introduces a coordinator server as an intermediary component that manages deduplication across multiple storage clusters. The coordinator receives operations from client servers, determines the target storage cluster using a mapping function, and routes operations accordingly. This intermediary enables system-wide deduplication without requiring complex peer-to-peer communication between all storage clusters, thus reducing data duplication while maintaining manageable system complexity.
Solution Approach 2:
The system is segmented into distinct functional components: client servers that generate operations, a coordinator server that manages deduplication logic and routing, and storage clusters that execute operations. This segmentation allows deduplication to be implemented hierarchically, where the coordinator handles high-level deduplication decisions while individual storage clusters handle local operations, enabling scalable cross-cluster deduplication.
2Reliability
If operations are distributed across multiple storage clusters, then system capacity and availability are increased, but resource duplication occurs when identical operations are performed on multiple clusters
Solution Approach 1:
The system performs preliminary deduplication analysis before distributing operations to storage clusters. The coordinator server evaluates incoming operations against existing data across clusters using a mapping function, determining in advance whether an operation would result in duplicate data creation. This preliminary action prevents unnecessary operation distribution, reducing compute resource waste while maintaining the redundancy needed for system availability through selective replication.
Solution Approach 2:
The mapping function dynamically changes routing parameters based on the current state of storage clusters, including available capacity, data locality, and deduplication opportunities. By adjusting these parameters in real-time, the system optimizes operation distribution to minimize resource duplication while ensuring operations are routed to appropriate clusters for maintaining availability and load balancing.
3Reliability
If a storage cluster becomes unavailable, then system reliability is reduced, but operations may still be routed to the unavailable cluster causing failures
Solution Approach 1:
The coordinator server implements feedback mechanisms that monitor the availability status of storage clusters. When a cluster becomes unavailable, the coordinator receives feedback about this state and dynamically adjusts the mapping function to route operations away from the unavailable cluster. This feedback loop maintains system reliability by preventing operations from being sent to failed clusters while keeping routing logic relatively simple through centralized coordination.
Solution Approach 2:
The operation routing system is dynamic rather than static. The mapping function continuously adapts to changing system conditions, including cluster availability, by recalculating operation targets. This dynamic behavior allows the system to automatically respond to failures and maintenance events, maintaining reliability without requiring complex manual reconfiguration or static routing tables that would be difficult to update.
Data Source
AI summary
A system, computer-readable storage medium storing at least one program, and a computer-implemented method for facilitating deduplication of operations to be performed is presented. An operation to be performed is received. A mapping function is applied to at least one parameter of the operation to produce a mapping value in a target mapping space, the target mapping space being partitioned between target servers in a set of target servers proportional to resource capacities of the target servers in the set of target servers. A target server in the set of target servers whose portion of the target mapping space includes the mapping value is identified. The operation is issued to the target server.