A MapReduce-based Quick Search Approach on Large Files

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.