Cache craftiness for fast multicore key-value storage
Proceedings of the 7th ACM european conference on Computer Systems
MemC3: compact and concurrent MemCache with dumber caching and smarter hashing
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
nsdi'13 Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation
TAO: Facebook's distributed data store for the social graph
USENIX ATC'13 Proceedings of the 2013 USENIX conference on Annual Technical Conference
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In-memory object caches are extensively used in today's web installations [1, 6]. Most existing systems adopt monolithic storage models and engineer optimizations on specific workload characteristics [3, 6] or operations [4, 5]. Such optimizations are insufficient as large-scale cloud workloads typically exhibit both temporal and spatial shifts - requirements vary within the same deployment over time and different parts of the same workload demonstrate different access patterns. To this end, we propose a caching tier that supports differentiated services in multiple dimensions. Since there is no best "one-size-fits-all" solution for all workload requirements, we argue that a fine-grained modular design will provide both high performance and flexibility in supporting multiple services.