Mass data high performance reading display process

Abstract

The invention relates to a mass data high performance fetch display method, which can fully mine potential computational capabilities of a client, a cache and a database, wherein, the client is mainly responsible for transmission of data request and display of echo data; the cache adopts an optimized partition structure and comprises a mapping table region and a data region; a 'jump iterative algorithm' is adopted to realize asynchronous push of search data towards a foreground, and simultaneously pull of a next data block with given size to a background; an optimized LRU algorithm is used for the data region, thereby the hit ratio of cache data is greatly improved and the mean hit ratio reaches over 90 percent. By adoption of the 'soft RAID technology', the concurrency is improved, thereby the access performance of the database is obviously improved; the problems difficult to be solved of no time delay display of the client, high performance concurrent access, high throughput of data and so on during the process of operating the mass data are solved; moreover, the cost of integration and mining of the prior resources is minimized.

Description

technical field [0001] The invention relates to the access of massive data in the communication network management system, in particular to the high-performance display of the massive data in the communication network management system. Background technique [0002] In the real world, especially in the field of communication network management, there is often a demand for querying and displaying massive data. However, in the face of massive data, the first thing we need to consider is performance. At present, in order to improve the operation performance of massive data, the countermeasures taken mainly include: selecting excellent database tools, optimizing query SQL statements, increasing virtual Memory, partitioning data, establishing extensive indexes, using paging technology for batch processing, using temporary tables and intermediate tables, using data warehouses and multidimensional database storage, using sampled data for data mining, upgrading hardware and other st...

AI Technical Summary

Problems solved by technology

[0003] However, the implementation of these strategies requires huge cost input, either increasing capital investment, upgrading software and hardware; or increasing the requirements for developers, because optimization requires high skills and rich experience

Moreover, the above methods are partial solutions to this problem, and fail to form an overall architecture solution that makes full use of existing system resources and computing capabilities to solve performance problems.

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