Processing method and system for differentiated secondary caching and synchronization of data of multiple clients

Abstract

The invention discloses a multi-client data differentiation secondary caching and synchronization processing method, which comprises the following steps that: a server responds to a data set calling request initiated by each client according to own service requirements, and if the server has a corresponding cached data set, the data set is sent to a matched client; if not, sending a data set acquisition request to a data source; the data source responds to a data set acquisition request initiated by the server and sends a corresponding data set to the server; the server receives the data set, caches the data set in a memory, and sends the data set to a corresponding client; and each client receives the data set paired with the tag of the own exclusive client and caches the data set in a memory. A large amount of data can be cached simultaneously and differentially at multiple points and each client, and the problems of data synchronization and timely updating between a data source and a server, between the server and multiple clients and between the clients are solved; and the requirements of personalized caching and data updating of different clients are met.

Description

technical field [0001] The invention relates to the fields of large data transmission, data synchronization and data cache, and in particular to a processing method and system for differentiating secondary cache and synchronization of multi-client data. Background technique [0002] With the development of Internet technology, the data processing volume of the software system is also increasing, the scale of data processing corresponding to the client is also increasing, and the data to be stored in the database is also increasing. For various reasons, it is necessary to perform multi-level caching on the data in the database, that is, to synchronize the data in the database to other business processing computer caches or databases or other clients. [0003] Due to the high concurrency and high performance requirements of the system, many systems almost use data caching technologies such as memory caching, memory databases, and redis caching databases. However, these caching...

AI Technical Summary

Problems solved by technology

[0003] Due to the high concurrency and high performance requirements of the system, many systems almost use data caching technologies such as memory caching, memory databases, and redis caching databases. However, these caching technologies have the following problems when they are applied: , will be directly linked to the data source, there will be disadvantages such as large data transmission volume or inflexible data update; if the data is cached at multiple points, it will be difficult to synchronize and update in time; when using the overall data cache, it cannot be realized Requirements for a single dataset personalized cache and multi-client differentiated cache

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