Vers l'auto-administration des entrepôts de données
Vers l'auto-administration des entrepôts de données
摘要：
随着一般数据库和特别是数据仓库的广泛发展，减少数据库管理员必须手动执行的任务是重要的。使用数据采掘技术从数据本身中提取有用的管理知识的想法已经存在了一些年。然而，很少有研究取得了成果。本研究的目的是寻找一种方法，从存储的数据中提取有用的知识，自动应用性能优化技术，更具体地说，索引技术。我们设计了一个工具，从给定的工作负载中提取频繁项集来计算索引配置，以帮助优化数据访问时间。我们执行的实验表明，我们的工具生成的索引配置允许在测试数据库和测试数据仓库上获得15%到25%的性能提升。
英文摘要：
With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The idea of using data mining techniques to extract useful knowledge for administration from the data themselves has existed for some years. However, little research has been achieved. The aim of this study is to search for a way of extracting useful knowledge from stored data to automatically apply performance optimization techniques, and more particularly indexing techniques. We have designed a tool that extracts frequent itemsets from a given workload to compute an index configuration that helps optimizing data access time. The experiments we performed showed that the index configurations generated by our tool allowed performance gains of 15% to 25% on a test database and a test data warehouse.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
