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Design, Implementation, and Performance of the LHAM Log-Structured History Data Access Method

机译:LHAM日志结构历史数据访问方法的设计,实现和性能

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Numerous applications such as stock market or medical information systems require that both historical and current data be logically integrated into a temporal database. The underlying access method must support different forms of "time-travel" queries, the migration of old record versions onto inexpensive archive media, and high insert and update rates. This paper introduces a new access method for transaction-time temporal data, called the Log-structured History Data Access Method (LHAM) that meets these demands. The basic principle of LHAM is to partition the data into successive components based on the timestamps of the record versions. Components are assigned to different levels of a storage hierarchy, and incoming data is continuously migrated through the hierarchy. The paper discusses the LHAM concepts, including concurrency control and recovery, our full-fledged LHAM implementation, and experimental performance results based on this implementation. A detailed comparison with the TSB-tree, both analytically and based on experiments with real implementations, shows that LHAM is highly superior in terms of insert performance while query performance is in almost all cases at least as good as for the TSB-tree; in many cases it is much better.
机译:诸如股票市场或医疗信息系统之类的许多应用要求历史和当前数据逻辑上集成到时间数据库中。底层访问方法必须支持不同形式的“时间旅行”查询,旧记录版本的迁移到廉价的存档介质,以及高插入和更新速率。本文介绍了一种用于交易时间时间数据的新访问方法,称为满足这些需求的日志结构历史数据访问方法(LHAM)。 LHAM的基本原理是根据记录版本的时间戳将数据分配到连续组件中。组件分配给不同级别的存储层级,并且通过层次结构持续迁移传入数据。本文讨论了LHAM概念,包括并发控制和恢复,我们的全面的LHAM实施以及基于该实施的实验性能结果。与TSB树进行详细的分析和基于实际实施实验的比较,表明LHAM在插入性能方面高度优越,而查询性能几乎所有情况都至少与TSB树一样好;在许多情况下,它更好。

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