Achieving convergent causal consistency and high availability with asynchronous replication

Yu Tang, Hailong Sun, Xu Wang, Xudong Liu, Zhenglin Xia
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引用次数: 2

Abstract

Nowadays, distributed data stores have become a fundamental infrastructure for large-scale Internet services, and they usually replicate data partitions to achieve high scalability and availability. To achieve better performance and availability, many Internet services embrace eventual consistency. However, stronger consistency is always desirable for system correctness. Recent studies [1][2] pay more attention to the convergent causal consistency, which is proved to be one of the strongest consistency models that can be achieved together with high availability in the presence of network partitions [3]. Convergent causal consistency couples the virtues of causal consistency and eventual consistency. As a result, convergent causal consistency not only guarantees that clients observe causality throughout, but also ensures that all replicas converge to the same state, which are critical for implementing reasonable application behaviors.
通过异步复制实现聚合因果一致性和高可用性
如今,分布式数据存储已经成为大规模Internet服务的基础设施,它们通常复制数据分区以实现高可伸缩性和可用性。为了获得更好的性能和可用性,许多Internet服务采用最终一致性。然而,为了保证系统的正确性,更强的一致性总是可取的。最近的研究[1][2]更加关注收敛因果一致性,它被证明是在存在网络分区的情况下,可以与高可用性一起实现的最强的一致性模型之一[3]。收敛因果一致性将因果一致性和最终一致性的优点结合在一起。因此,收敛因果一致性不仅保证客户端始终遵循因果关系,而且还确保所有副本收敛到相同的状态,这对于实现合理的应用程序行为至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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