Research on Big Data Storage Structure and Query Optimization

Big data not only requires massive storage systems, but also requires high speed data loading, fast query processing, high utilization of storage space, and adaptive dynamic high load. Because the traditional relational database has encountered various difficulties and obstacles in managing big data, a new distributed system has emerged. But in large data storage and query there are still shortcomings, this article from two aspects of data storage structure and correlation graphs homework for distributed system of data storage structure and query optimization analysis. In this paper, from the input correlation, correlation data transformation, three aspects of job stream correlation is optimized to improve the result of the translation, and gives optimization conditions and optimization rules, merging redundant graphs assignments in order to reduce unnecessary resource consumption, thus improve the big data query speed.