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Parallel processing of XML databases

机译:XML数据库的并行处理

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摘要

Beowulf cluster is a name given to a high performance, low-cost parallel computer system made of commodity hardware and software components. It consists of a number of processing nodes, interconnected via a switch. The extensible markup language (XML) data model, on the other hand, has recently gained huge popularity because of its ability to represent a wide variety of structured (tabular-like) and semi-structured (textual-like) data. Several query languages have been proposed for the XML data model, the most-widely known is XQuery. This paper reviews the XML data model and its query language within the context of cluster/parallel computing environment. It examines several techniques for structuring and storing XML data across the different cluster nodes. It develops a number of algorithms suitable for processing a certain class of queries, namely, the containment queries, against the parallel XML database. This paper also shows that one of these algorithms, the one that takes advantage of the parallelism existing between the different documents within the XML database, is outperforming all of the other presented ones
机译:Beowulf群集是由商品硬件和软件组件组成的高性能,低成本并行计算机系统的名称。它由多个处理节点组成,这些节点通过交换机互连。另一方面,可扩展标记语言(XML)数据模型由于能够表示各种结构化(表格形式)和半结构化(文字形式)数据而最近获得了巨大的普及。已经为XML数据模型提出了几种查询语言,其中最广为人知的是XQuery。本文在集群/并行计算环境的背景下回顾了XML数据模型及其查询语言。它研究了在不同集群节点之间构造和存储XML数据的几种技术。它开发了许多算法,适用于针对并行XML数据库处理特定类别的查询,即包含查询。本文还表明,其中一种算法(利用XML数据库中不同文档之间存在的并行性)优于其他所有算法。

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