Four-layer structure data acquisition method and device based on distributed system

Abstract

The invention provides a four-layer structure data acquisition method and device based on a distributed system. The method comprises the following steps: receiving a service processing request sent bya user; if the service processing request is executed and data needs to be called calling the data in a local cache, a remote database used for storing the first type of data, a public server cache and a public database used for storing the second type of data in sequence until target data is obtained. Different types of data are distinguished, a four-layer structure data storage, acquisition andsynchronization scheme based on the distributed system is achieved, the method and device are suitable for solving the performance problem of the bank distributed system in a high-concurrency and high-frequency access scene, the database pressure can be remarkably reduced, the system performance is effectively improved, the system can stably operate in the high-concurrency scene, and the user experience is further improved.

Description

technical field [0001] The invention relates to the field of distributed technology, in particular to a method and device for acquiring four-layer structure data based on a distributed system. Background technique [0002] With the development of big data and distributed technology, caching technology has also been widely used. For a system with a small amount of data, the single-point cache server can quickly respond to user read and write requests and reduce the pressure on the database server. However, for a system with high timeliness and a large amount of concurrency, the single-point cache server cannot To quickly respond to user requests, a distributed cache system is required to store data. [0003] The traditional approach is usually to simply use the combination of NoSQL and relational databases. Among them, NoSQL is used as a cache database to store data that needs to be frequently accessed during the operation of the system. When a read request arrives, it first...

AI Technical Summary

Problems solved by technology

For a system with a small amount of data, the single-point cache server can quickly respond to user read and write requests and reduce the pressure on the database server. However, for a system with high timeliness and a large amount of concurrency, the single-point cache server cannot To respond quickly to user requests, a distributed cache system is required to store data

[0003] The traditional approach is usually to simply use the combination of NoSQL and relational databases. Among them, NoSQL is used as a cache database to store data that needs to be frequently accessed during the operation of the system. When a read request arrives, it first checks whether the cache database exists. Target data, if so, return the target data directly from the cache database, otherwise query the relational database to obtain the target data and return it, and write the query results to the cache database at the same time, but this approach has certain limitations: for all data Generally speaking, when a read request is received for the first time, the target data must be obtained from the relational database. In the case of a large amount of concurrency, it will put pressure on the relational database and seriously affect system performance.

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