Research On Query Optimization Algorithm Of Massive Data

As computer applications and network technology continues to develop and improve the present, more and more business and government need to operate massive data volume of data, such as the logistics industry, water conservancy departments, research departments, these departments are usually very great. And current data, including reports, text, sound, images, and other various types and levels of information, these data have great value. When the data in the database is too large, there will be low system efficiency, consumption and other issues; to be addressed on the other hand there are also a lot of useless data redundancy, designers need to store, manage, process optimization in all aspects, extract the desired information. So mass data storage management is increasingly important in the information technology industry in the process, has been widespread concern in the industry, and therefore the study of mass data storage query algorithm is very necessary.Research and Application of paper reviews the massive data management technology, the introduction of the underlying database data management, storage optimization, the index-based applications, top-k query algorithms, SQL statements, page breaks, etc. Some of optimization algorithms and techniques, proposed a set of comprehensive optimization program, and gives specific operational and experimental data, the final design and implementation of a large-scale real estate charging system, charging system and meticulous in all aspects of design, fully optimized. After laboratory tests, it is clear that real estate operations and query speed charging system has been significantly improved. Thus, the optimization of the grammar of the text used in massive data query optimization is correct and effective.