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Dwarf尺寸的进一步缩减
引用本文:向隆刚,龚健雅. Dwarf尺寸的进一步缩减[J]. 计算机科学, 2007, 34(7): 103-105
作者姓名:向隆刚  龚健雅
作者单位:武汉大学,测绘遥感信息工程国家重点实验室,武汉430079;武汉大学,测绘遥感信息工程国家重点实验室,武汉430079
基金项目:国家重点基础研究发展计划(973计划)
摘    要:Dwarf不仅降低了数据立方的存储开销,而且具有结构简单、易于实现、查询和维护等优点,是一种比较理想的数据立方组织方法。为了进一步缩减Dwarf的存储尺寸,本文通过研究Dwarf结构,分别提出了浓缩Dwarf和冰山Dwarf:前者从Dwarf结构中删除了对于查询来说冗余的内容,而后者从Dwarf结构中去掉了对于用户来说琐碎的内容。实验和分析表明,浓缩Dwarf有效地减小了Dwarf的存储尺寸,而冰山Dwarf适合于忽略细节的应用场合,极大地降低了Dwarf的存储开销。

关 键 词:数据立方  Dwarf  浓缩Dwarf  冰山Dwarf

Further Compression of Dwarf Size
XIANG Long-Gang,GONG Jian-Ya. Further Compression of Dwarf Size[J]. Computer Science, 2007, 34(7): 103-105
Authors:XIANG Long-Gang  GONG Jian-Ya
Affiliation:State Key Laboratory of Information Engineer in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079
Abstract:Dwarf is an appropriate way for data cube store because it not only reduces the storage size, but also has a simple structure and is easy to be queried and maintained. For further compression of Dwarf, we proposes Condensed Dwarf and Iceberg Dwarf respectively, the former deletes from Dwarf structure redundant store, while the latter deletes from Dwarf structure trivial store. Our experiments and analysis show that Condensed Dwarf reduces the storage size of Dwarf effectively, while Iceberg Dwarf works well in detail-overlooked situation, and it can reduce the storage size of Dwarf significantly in such cases.
Keywords:Data cube   Dwarf   Condensed dwarf   Iceberg dwarf
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