I/O-efficient algorithms for answering pattern-based aggregate queries in a sequence OLAP system

C. Chui, B. Kao, Eric Lo, Reynold Cheng
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引用次数: 6

Abstract

Many kinds of real-life data exhibit logical ordering among their data items and are thus sequential in nature. In recent years, the concept of Sequence OLAP (S-OLAP) has been proposed. The biggest distinguishing feature of SOLAP from traditional OLAP is that data sequences managed by an S-OLAP system are characterized by the subsequence/substring patterns they possess. An S-OLAP system thus supports pattern-based grouping and aggregation. Conceptually, an S-OLAP system maintains a sequence data cube which is composed of sequence cuboids. Each sequence cuboid presents the answer of a pattern-based aggregate (PBA) query. This paper focuses on the I/O aspects of evaluating PBA queries. We study the problems of joining plan selection and execution planning, which are the core issues in the design of I/O-efficient cuboid materialization algorithms. Through an empirical study, we show that our algorithms lead to a very I/O-efficient strategy for sequence cuboid materialization.
用于回答序列OLAP系统中基于模式的聚合查询的I/ o高效算法
许多现实生活中的数据在它们的数据项之间表现出逻辑顺序,因此本质上是顺序的。近年来,序列OLAP (S-OLAP)的概念被提出。SOLAP与传统OLAP最大的区别在于,S-OLAP系统管理的数据序列由它们拥有的子序列/子字符串模式来表征。因此,S-OLAP系统支持基于模式的分组和聚合。从概念上讲,S-OLAP系统维护一个由序列长方体组成的序列数据立方体。每个序列长方体表示基于模式的聚合(PBA)查询的答案。本文主要关注评估PBA查询的I/O方面。我们研究了连接计划选择和执行计划问题,这是I/ o高效长方体物化算法设计中的核心问题。通过实证研究,我们表明我们的算法导致一个非常高效的I/ o策略序列长方体物化。
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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