Selection of Redundant and non Redundant Optimization Structures in VLDBs

Ladjel Bellatreche
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引用次数: 3

Abstract

Very large database applications are usually modelled using huge schemas with several large tables with many columns. Queries defined on those schemas are complex since they contain join and aggregation operations. In large databases, join operations are the most used and the most expensive, especially when the size of tables is very large. To optimize these complex queries, several optimization structures have been proposed. Selecting any optimization structure is NP-hard problems since their search spaces are very large. In this paper, we classify these structures into two main categories: (1) non redundant structures (horizontal and vertical partitioning, parallel processing) and (2) redundant structures (materialized views, indexing schemes). Our study focuses on two non redundant structures: horizontal and vertical partitioning and one redundant structure: bitmap join indexes, where formalizations of their selection problems and algorithms are presented. We propose an approach combining horizontal partitioning and bitmap join indexes to speed up queries and to reduce storage and maintenance costs of indexes. Finally, our proposed algorithms are validated using experimental studies.
vldb中冗余与非冗余优化结构的选择
非常大的数据库应用程序通常使用巨大的模式建模,其中包含几个具有许多列的大表。在这些模式上定义的查询很复杂,因为它们包含连接和聚合操作。在大型数据库中,连接操作是最常用的,也是最昂贵的,特别是当表的大小非常大时。为了优化这些复杂的查询,提出了几种优化结构。选择任何优化结构都是np困难问题,因为它们的搜索空间非常大。在本文中,我们将这些结构分为两大类:(1)非冗余结构(水平和垂直划分,并行处理)和(2)冗余结构(物化视图,索引方案)。我们的研究重点是两个非冗余结构:水平和垂直分区和一个冗余结构:位图连接索引,其中提出了它们的选择问题和算法的形式化。我们提出了一种结合水平分区和位图连接索引的方法来提高查询速度,降低索引的存储和维护成本。最后,用实验研究验证了我们提出的算法。
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