Efficiently Supporting Adaptive Multi-Level Serializability Models in Distributed Database Systems

Zhanhao Zhao
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Abstract

Informally, serializability means that transactions appear to have occurred in some total order. In this paper, we show that only the serializability guarantee with some total order is not enough for many real applications. As a complement, extra partial orders of transactions, like real-time order and program order, need to be introduced. Motivated by this observation, we present a framework that models serializable transactions by adding extra partial orders, namely multi-level serializability models. Following this framework, we propose a novel concurrency control algorithm, called bi-directionally timestamp adjustment (BDTA), to supporting multi-level serializability models in distributed database systems. We integrate the framework and BDTA into Greenplum and Deneva to show the benefits of our work. Our experiments show the performance gaps among serializability levels and confirm BDTA achieves up to 1.7× better than state-of-the-art concurrency control algorithms.
分布式数据库系统中有效支持自适应多级序列化模型
非正式地说,可序列化性意味着事务似乎是以某种总顺序发生的。在许多实际应用中,我们证明了仅具有一定总序的可序列化性保证是不够的。作为补充,需要引入额外的部分事务顺序,如实时顺序和程序顺序。受此启发,我们提出了一个框架,该框架通过添加额外的部分顺序来建模可序列化事务,即多级可序列化模型。在此框架下,我们提出了一种新的并发控制算法,称为双向时间戳调整(BDTA),以支持分布式数据库系统中的多级序列化模型。我们将框架和BDTA集成到Greenplum和Deneva中,以显示我们工作的好处。我们的实验显示了串行化级别之间的性能差距,并证实BDTA比最先进的并发控制算法提高了1.7倍。
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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