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A MapReduce-based Quick Search Approach Large Files

机译:基于MapReduce的快速搜索方法大文件

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摘要

String search is an important branch of pattern matching for information retrieval in various fields. In the past four decades, the research importance has been attached on skipping more unnecessary characters to improve the search performance, and never taken into consideration on large scale of data. In this paper, two major achievements are contributed. At first, we propose a Quick Search algorithm for data Stream (QSS) on a single machine to support string search in a large text file, as opposed to previous researches that limits to a bound memory. For the next, we implement the search algorithm on MapReduce framework to improve the velocity of retrieving the search results. The experiments demonstrate that our approach is fast and effective for large files.
机译:String Search是用于各种字段中信息检索的模式匹配的重要分支。在过去的四十年中,在跳过更多不必要的角色来提高搜索性能,并从未考虑过大规模数据的研究重视。在本文中,贡献了两项重大成就。首先,我们提出了一种在单个计算机上的数据流(QSS)的快速搜索算法,以支持大文本文件中的字符串搜索,而不是以前的研究限制了绑定存储器。对于下一步,我们在MapReduce框架上实现搜索算法,以提高检索搜索结果的速度。实验表明,我们的方法对于大型文件来说是快速而有效的。

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