CREST: High-Performance Contention Resolution for Disaggregated Transactions
Qihan Kang, Mi Zhang, Patrick P. C. Lee, Yongkang Hu
Abstract
Distributed transaction systems can leverage memory disaggregation for efficient resource scaling, yet they experience significant performance degradation under high-contention workloads. We present CREST, a disaggregated transaction system that efficiently manages high-contention transaction workloads in disaggregated memory architectures via three key techniques: (i) cell-level concurrency control, which achieves more fine-grained transaction concurrency than existing record-level approaches and reduces remote access latencies using a metadata-aggregated record structure; (ii) localized execution, which allows compute nodes to operate on local uncommitted results to reduce blocking time; and (iii) parallel commits, which parallelize commit operations under transaction dependencies. Evaluation shows that CREST achieves a throughput gain of up to 1.92× over state-of-the-art systems under high-contention workloads.
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