Aurogon: Taming Aborts in All Phases for Distributed In-Memory Transactions


Tianyang Jiang, Guangyan Zhang, Zhiyue Li, and Weimin Zheng, Tsinghua University


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 4.1x and cuts transaction abort rate by up to 73% compared with three state-of-the-art distributed transaction systems.

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This content is available to:

@inproceedings {277812,
author = {Tianyang Jiang and Guangyan Zhang and Zhiyue Li and Weimin Zheng},
title = {Aurogon: Taming Aborts in All Phases for Distributed {In-Memory} Transactions},
booktitle = {20th USENIX Conference on File and Storage Technologies (FAST 22)},
year = {2022},
isbn = {978-1-939133-26-7},
address = {Santa Clara, CA},
pages = {217--232},
url = {},
publisher = {USENIX Association},
month = feb

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