Clustered data query method, client side and system

Abstract

The invention discloses a clustered data query method, a client side and a system. The clustered data query method includes: connection is established with a data base agent device; query conditions are sent to the data base agent device; results which are respectively obtained on the query conditions by data base servers, obtained through each data base server in a data base cluster and returned from the data base agent device are received as first query results; the first query results are stored in an appointed data base server; query results which are obtained by dividing the first query results into groups according to preset conditions and returned by the appointed data base server based on grouping query conditions and stored data are received. According to the clustered data query method, the client side and the system, collective processing in data query is carried out without adopting MAPREDUCE, and simple operation of inserting data in the appointed data base server and returning to the inserted data again replaces the MAPREDUCE, so that the processing efficiency is high, and query response time delay is reduced.

Description

technical field [0001] The invention relates to a database technology, in particular to a database cluster data query method, client and system. Background technique [0002] With the maturity of traditional database technology, the rapid development of computer network technology and the expansion of application scope, database applications have been generally established on the computer network. At this time, the centralized database system shows its shortcomings: centralized processing will inevitably cause performance bottlenecks; the application program is concentrated on one computer, and once the computer fails, the entire system will be affected and the reliability is not high; The scale and configuration of the system are not flexible enough, and the scalability of the system is poor. In this situation, centralized databases will develop towards distributed databases. [0003] Database clustering is a technology that combines multiple servers to form a cluster to ...

AI Technical Summary

Problems solved by technology

At this time, the centralized database system shows its shortcomings: centralized processing will inevitably cause performance bottlenecks; the application program is concentrated on one computer, and once the computer fails, the entire system will be affected and the reliability is not high; The scale and configuration of the system are not flexible enough due to the traditional processing, and the scalability of the system is poor.

The disadvantage of this method is that it is slower

For example, when the amount of query result data exceeds 500,000, the speed of grouping and summarization will be intolerable, which may exceed 15 seconds

[0007] In addition, if you compile an algorithm to summarize the data selected by Amoeba when performing data query to obtain grouped data, when the amount of data is large, it will exceed the cache size setting allowed by APACHE, resulting in a 504 error on the server.

In addition, because the algorithm needs to be written manually, it requires programming workload and later maintenance, which is prone to bugs

Images