Memory access method and device supporting data persistence

Abstract

The invention discloses a memory access method and a device supporting data persistence. The method comprises the following steps of S1, receiving a data request of a client end, judging whether the data request meets a standard protocol or not, if yes, carrying out S2, and if not, rejecting the data request; S2, judging whether the data request is a data reading request or a data writing request, if the data request is the data writing request, carrying out S3, and if the data request is the data reading request, carrying out S4; S3, analyzing the data writing request, building a corresponding data structure according to data to be written, and calling a storage interface to store the data to be written to a data storage end; S4, analyzing the data reading request, and calling the storage interface to acquire corresponding data from the data storage end. Memcached and Berkeleydb are combined to obtain a memory Key-value database system supporting data persistence, and the database system is utilized to carry out data access service, so that high-speed reading and writing of data can be ensured; persistence modules are combined to form a cluster example, so that the storage of the data is more stable.

Description

technical field [0001] The invention relates to a data access method based on a memory object cache system supporting data persistence. Background technique [0002] Memcached is a high-performance memory object caching system for dynamic web applications to reduce database load. It reduces the number of times to read the database by caching data and objects in memory, thereby improving the speed of dynamic, database-driven websites, but Memcached is only a memory caching system, and data cannot be stored permanently. When it is closed, the data will be completely lost, which is not suitable for high security requirements, which greatly limits its applicable scenarios. Berkeleydb is a high-performance key-value, embedded database. The database is lightweight and efficient. It can support thousands of concurrent threads to operate the database at the same time. It supports up to 256TB of data. It supports cluster functions, data synchronization, cluster high availability and...

AI Technical Summary

Problems solved by technology

It reduces the number of times to read the database by caching data and objects in memory, thereby improving the speed of dynamic, database-driven websites, but Memcached is only a memory caching system, and data cannot be stored permanently. When it is closed, the data will be completely lost, which is not suitable for high security needs, which greatly limits its applicable scenarios

Berkeleydb is a high-performance key-value, embedded database. The database is lightweight and efficient. It can support thousands of concurrent threads to operate the database at the same time. It supports up to 256TB of data. It supports cluster functions, data synchronization, cluster high availability and many other functions. But Berkeleydb is An embedded database, which only provides API, does not have a friendly network interface and access protocol, cluster addition, deletion, cluster configuration, and startup have strict requirements. It is still far away from the actual use environment and must go through a lot of development and testing.

Images