Design And Implementation Of Full-Text Search System Based On Cloud Storage

In recent years, as the hardware costs and bandwidth costs decline, ad the rate of development of broadband, based on demand data security and data synchronization. More and more people choose the way of cloud storage for storing data. With the growth of the amount of data, the data retrieval of cloud storage is also increasingly difficult, and thus the cloud storage data retrieval in the field of personal cloud storage data. The Full-Text Search applications base on cloud storage can facilitate the users in huge amounts of data fast positioning need to improve the retrieval accuracy and reduce data retrieval time cost and labor costs.Cloud storage application development time is shorter in the country, making the large amount of user data, users need to spend a lot of time and energy to traverse each folder and file to find the files they need. In the context of this application, a distributed full-text retrieval system based on cloud storage can help users to quickly locate a file, reduce the users local file migration to the cloud need to increase the time and labor costs, and improve the user experience and increase the availability of the product.This thesis is the design and development of distributed text retrieval system based on cloud storage, cloud storage document retrieval, the content of user needs and system applications to collect and collate, combined with full-text search, cloud storage in the country, analysis of the need to implement a distributed full-text search based on cloud storage capabilities, and technical difficulties and facing difficulty, the use of a mature open source technologies, designed to achieve a stable retrieval system. This paper describes the open source technology with Lucene to complete the core search function, combined with the system messaging, message merging and many other needs, design a cloud-based storage, Distributed text retrieval system.Finally, we introduction the system testing and optimization direction, test and finish the application of full-text search in the experimental environment.