Aurogon: Taming Aborts in All Phases for Distributed In-Memory Transactions
Tianyang Jiang, Guangyan Zhang, Zhiyue Li, Weimin Zheng
Abstract
Flourishing OLTP applications promote transaction systems to scale out to datacenter-level clusters. Benefiting from high scalability, timestamp ordering (T/O) approaches tend to win out from a number of concurrency control protocols. However, under workloads with skewed access patterns, transaction systems based on T/O approaches still suffer severe performance degradation due to frequent transaction aborts.
We present Aurogon, a distributed in-memory transaction system that pursues taming aborts in all execution phases of a T/O protocol. The key idea of Aurogon is to mitigate request reordering, the major cause of transaction aborts in T/O-based systems, in all phases: in the timestamp allocation phase, Aurogon uses a clock synchronization mechanism called 2LClock to provide accurate distributed clocks; in the request transfer phase, Aurogon adopts an adaptive request deferral mechanism to alleviate the impact of nonuniform data access latency; in the request execution phase, Aurogon pre-attaches certain requests to target data in order to prevent these requests from being issued late. Our evaluation shows that Aurogon increases throughput by up to 4.1× and cuts transaction abort rate by up to 73%, compared with three state-of-the-art distributed transaction systems.
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