基于缓存的冰山查询评估

V. Shankar, C. V. Guru Rao
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引用次数: 6

摘要

目前,人们更需要能够从大数据集中高效地检索小结果的技术。冰山查询是这样一种查询,它接受大数据作为输入,并根据用户指定的阈值(T)处理它们以检索小结果。以前,冰山查询可以通过多种方式处理,但在检索数据的速度上受到损害。因此,冰山查询评价方法的改进成为众多研究者关注的焦点。压缩位图索引是近年来发展起来的一种解决冰山查询的有效技术。在本文中,我们提出了“基于缓存的冰山查询评估”。冰山查询使用压缩位图索引技术在阈值等于1时进行评估,将结果保存在缓存中以供将来参考。对于冰山查询的进一步评估,大于1的阈值只是从缓存内存中选择结果,而不是再次在数据库表上执行。因此,策略明确指出,通过避免多次重复评估过程,IBQ的执行时间得到了改善。实验结果表明,基于缓存的评估策略优于现有的评估策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cache based evaluation of iceberg queries
Nowadays, it is more demanded for techniques that are efficient in retrieval of small results from large data sets. Iceberg queries are such a kind of queries which accepts large data as input and process them for retrieve small results upon user specified threshold (T). Earlier, the iceberg queries are processed by many ways but are compromised in speed with which the data is retrieved. Thus lots of researchers are concentrating on improvement of iceberg query evaluation methods. Compressed bitmap index is an efficient technique which is developed recently to answer iceberg queries. In this paper, we proposed “Cache Based Evaluation of Iceberg Queries”. An iceberg query is evaluated using compressed bitmap index technique for threshold equals to 1, save results in cache memory for future reference. For further evaluation of an iceberg query thresholds greater than 1 are just picking the results from the cache memory instead of executing once again on the database table. Thus strategy clearly stating that, an execution time of IBQ is improved by avoiding repetition of an evaluation process by multiple times. Experimental results are demonstrating our cache based evaluation strategy is better than existing strategy.
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