Method and apparatus for caching data

Abstract

The present invention discloses a method and apparatus for caching data, and relates to the technical field of computers. One specific embodiment of the method comprises presetting a first storage area and a second storage area, and the maximum stored data size of each of the first storage area and the second storage area is a preset upper limit value. The method comprises the steps of (1) storingto-be-cached data into the first storage area; (2) exchanging the stored data in the first storage area and the stored data in the second storage area after the stored data size of the first storagearea reaches the upper limit value; and (3) after exchange is executed, executing the step one if the current stored data size of the first storage area does not reach the upper limit value; otherwise, emptying the current stored data in the first storage area, and executing the step one. According to the embodiments, the cache hit ratio can be increased, storage overflow can be prevented, application risk can be reduced, the total cached data size can be controlled, hot spot data can be cached, and computation complexity is low.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method and device for caching data, electronic equipment, and a computer-readable medium. Background technique [0002] With the continuous development of information technology, the number of Internet users has increased rapidly, and the acquisition of various information has shown an explosive trend. Traditional databases are inefficient and slow, and how to store information for high-speed access has become a problem that needs to be solved. Existing NoSQL (non-relational database) technologies such as Redis (a memory-based key-value storage system) and MongoDB (distributed document storage database) require a large number of network interactions, and performance is limited by factors such as network bandwidth. influences. [0003] Existing data storage solutions usually use relational databases, or use NoSQL such as Redis to store data, or use HashMap (a data st...

AI Technical Summary

Problems solved by technology

[0004] For the above existing storage solutions, relational databases can reach thousands of requests per second, and Redis can reach tens of thousands of requests per second. In some specific cases, the performance can no longer meet the system requirements, and the system needs to be buffered again. storage

HashMap and other data storage methods can be used as a good cache tool because they are stored in local memory with high efficiency. However, because the storage space is not considered in their design, long-term use will cause errors such as memory overflow.

Images