位图索引上范围查询处理的缓存支持

Sarah McClain, Manya Mutschler-Aldine, C. Monaghan, David Chiu, Jason Sawin, Patrick Jarvis
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引用次数: 0

摘要

位图通常用于索引只读数据集。属性的范围被分成若干个bin,其值被放置在其中:bij = 1表示第i个元组的值在第j个bin中,否则bij = 0。许多查询类型可以分解为布尔运算符在一组箱子上的系统应用程序。但是,当位图是高维的时,由于每个查询参与的bin数量增加,整体查询处理性能可能会下降。我们提出了一个缓存框架来组织、管理和集成缓存的部分结果,以加速高维位图上的查询处理。我们首先表明,为了解决一般复杂的析取和合取查询,部分位图结果的最优集的选择是np完全的。这个问题只考虑连续bin序列(公共范围和点查询的特征)的限制使我们能够有效地解决它。在TPC-H基准测试和真实的网络入侵数据集上对我们的缓存系统进行了几种工作负载的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Caching Support for Range Query Processing on Bitmap Indices
Bitmaps are commonly used for indexing read-mostly data sets. The range of an attribute is split into bins, where its values are placed: bij = 1 denotes the value of the ith tuple is in the jth bin, and bij = 0 otherwise. A number of query types can be decomposed into the systematic application of boolean operators over sets of bins. However, when bitmaps are high-dimensional, the overall query-processing performance can deteriorate due to the increased number of bins that participate per query. We propose a caching framework that organizes, manages, and integrates cached partial results to accelerate query processing on high-dimensional bitmaps. We begin by showing that, to resolve general complex disjunctive and conjunctive queries, the selection of an optimal set of partial bitmap results is NP-complete. A restriction on this problem to only consider consecutive bin sequences (characteristic of common range and point queries) allows us to solve it efficiently. The evaluation our caching system over several workloads carried out on the TPC-H benchmark and a real network-intrusion data set is presented.
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