Research And Application Of Large Data Storage Method Based On MongoDB

The significance of study on large data storage is very important. People’s life style changes without paper flows, and we put bits of life records with writting blog,publishing in computer; In the course of our meeting, the main content is recorded in the computer, replaced prior to everywhere with pen and paper habits; Our amateur life also changed by previous sitting in chat together into his squat to surf the Internet at home, play games, of course, and these online games will also produce large amounts of data stored in a computer. So, we need a large storage space to complete our growing data volume. People began to hope and to produce high quality, high capacity of hardware equipment. But the fact is that, this does not meet the age requirements, we need a more sophisticated means to solve such a large demand for storage.After recent years of distributed storage technology development, proving distributed storage can not only provide scalable storage capacity, also developed the new way of storing, and query method. With a variety of emerging technology, we can more easily, safe and efficient process with massive data.MongoDB is one of the very popular database in today’s non relational database,because of its support for distributed storage, So in the era of big dat a it is widely used by the majority of users. In the era of big data, the unbalanced distribution will cause the data relocation, consume a lot of resources. Therefore, the consistency of the hash algorithm is applied to MongoDB, it can make the distribution of the load balance, and ensure the normal operation of the system.this paper, by the concept of data storage, the principle of the query dat a, has a research and analysis in large data storage technology. The typical lar ge data memory optimization techniques include increasing the virtual memory and a cache mechanism. difficulties of the traditional storage technology in the big data storage implementation is pointed out, and on this basis, the paper f ocuses on the analysis of the P2 P distributed storage system, and automatic sli ce technology, and the load balancing in the automatic technology, some impro ved algorithms have been proposed.This paper presents a dynamic load balancing technique. Through the comparison of experiments, it can be proved that the equilibrium technology of the consistency hash algorithm is superior to the scope of the MongoDB. When ins erting a new data to the database, data will exist in partition that is also uncer tain. If there is a lot of partition in the load and a few partitions without data,it is bound to cause uneven distribution of data. Due to the limitations of Mo ngoDB, the will cause a lot of data migration, resulting in insufficient memory problem..This paper suggests using simple data type keys to create an index, and is the only index, which can effectively reduce the memory usage of memory. Index is indispensable in the process of database technology and memory greatly. Adding an index can improve the search speed, which in any of a class of database is required. MongoDB is a memory database, in the possible conditions should save memory usage, reduce unnecessary loss. The index optimization is an effective measure, and does not waste too much resources.In this paper, we prove that the results of the same query operation are different when the query environment is changed by the study of the Skip function. Using the Mongo database comes with functions that can simplify the code, easy to read. However, the understanding of the function is not thorough, not comprehensive,will lead to the late query and other operational efficiency is low, the impact of the whole system and efficient operation.