Research And Implementation Of Approximate Substring Query Processing And A System On Compressed Data

With the development of society, the amount of information data is continuously expanding. Surge in the amount of data has brought great pressure on the preservation and use of data.In order to solve the increase of data size and storage space conflicts, efficient compression algorithms have been proposed. Data query technology are essential in all fields, however, data compression techniques bring great challenges for query. How to query the compressed data becomes main research topic of this article.This study is made based on an existing data lossless compression technique, proposed and designed to support compressed data to achieve approximate substring query technology. This lossless compression technology takes advantage of high similarity property among string data. In order to efficiently query the data, this paper uses efficient B+-tree structure and the advanced inverted list index technology on the compressed data, we can locate the query sequence by the information provided from the inverted list index quickly, B+-tree structure can quickly access information. Through improving two kinds of indexing techniques, we can use them into approximate substring query algorithm. Proposing high-efficiency-related filtering method, and designing the perfect approximate algorithm finally.Based on the detailed introduction of the theory to the system, the feasibility and function of system and the requirement of all needs to do a detailed analysis, decided to adopt the system in the form of B/S framework, through the network to user. After running and performance tests, the system can provide services of stability.