Differentiated Key-Value Storage Management for Balanced I/O Performance
Yongkun Li, Zhen Liu, Patrick P. C. Lee, Jiayu Wu, Yinlong Xu, Yi Wu, Liu Tang, Qi Liu, Qiu Cui
Abstract
Modern key-value (KV) stores adopt the LSM-tree as the core data structure for managing KV pairs, but suffer from high write and read amplifications. Existing LSM-tree optimizations often make design trade-offs and are unable to simultaneously achieve high performance in writes, reads, and scans. To resolve the design tensions, we propose DiffKV, which builds on KV separation to carefully manage the ordering for keys and values. DiffKV manages keys using the conventional LSM-tree with fully-sorted ordering (within each level of the LSM-tree), while managing values with partially-sorted ordering with respect to the fully-sorted ordering of keys in a coordinated way for preserving high scan performance. We further propose fine-grained KV separation to differentiate KV pairs by size, so as to realize balanced performance under mixed workloads. Experimental results show that DiffKV can simultaneously achieve the best performance in all aspects among existing LSM-tree-optimized KV stores.
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