Although it has been commercially successful to deploy weakly consistent but highly-responsive distributed datastores, the tension between developing complex applications and obtaining only weak consistency guarantees becomes more and more severe. The almost strong consistency tradeoff aims at achieving both strong consistency and low latency in the common case. In distributed storage systems, we investigate the generic notion of almost strong consistency in terms of designing fast read algorithms while guaranteeing Probabilistic Atomicity with well-Bounded staleness (PAB). This problem has been explored in the case where only one client can write the data. However, the more general case where multiple clients can write the data has not been studied. In this article, we study the fast read algorithm for PAB in the multi-writer case. We show the bound of data staleness and the probability of atomicity violation by decomposing inconsistent reads into the read inversion and the write inversion patterns. We implement the fast read algorithm and evaluate the consistency-latency tradeoffs based on the instrumentation of Cassandra and the YCSB benchmark framework. The theoretical analysis and the experimental evaluations show that our fast read algorithm guarantees PAB, even when faced with dynamic changes in the computing environment.

中文翻译：

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在分布式数据存储中实现具有界限明确的陈旧性和低读取延迟的概率原子性

尽管部署弱一致性但响应迅速的分布式数据存储在商业上取得了成功，但开发复杂应用程序与仅获得弱一致性保证之间的紧张关系变得越来越严重。几乎强一致性权衡旨在在常见情况下实现强一致性和低延迟。在分布式存储系统中，我们研究了在设计快速读取算法的同时保证概率原子性和有界陈旧性 (PAB) 的几乎强一致性的通用概念。这个问题已经在只有一个客户端可以写入数据的情况下进行了探索。但是，尚未研究多个客户端可以写入数据的更一般情况。在本文中，我们研究了多写入器情况下 PAB 的快速读取算法。我们通过将不一致的读取分解为读反转和写反转模式来展示数据陈旧的界限和原子性违规的概率。我们实现了快速读取算法，并基于 Cassandra 和 YCSB 基准框架的检测来评估一致性-延迟权衡。理论分析和实验评估表明，即使面临计算环境的动态变化，我们的快速读取算法也能保证 PAB。