Database operation method and device

Abstract

The invention provides a database operation method and device. The method includes the steps that prediction execution data generated when prediction execution is conducted on a to-be-executed event is obtained, wherein the prediction execution data includes a primary key value of target data required by the to-be-executed event and a value, adopted in the prediction execution process, of the target data; according to the primary key value of the target data, the current value of the target data is loaded from a target sub-database corresponding to the to-be-executed event; when the current value of the target data is different from the value, adopted in the prediction execution process, of the target data, whether the current value of the target data affects the business logic of the to-be-executed event is judged; if the current value of the target data does not affect the business logic of the to-be-executed event, the current value of the target data serves as version data corresponding to the to-be-executed event, and the version data is recorded in the target sub-database. According to the method and the device, the storage cost of multi-version concurrency control can be saved, and the disk capacity required by the database is reduced.

Description

[0001] 【Technical field】 [0002] The present application relates to the technical field of databases, in particular to a method and device for operating a database. [0003] 【Background technique】 [0004] Stand-alone databases can easily meet users' needs for relational queries, and are currently the most commonly used database type in business applications. However, for many applications, stand-alone databases will eventually encounter stand-alone performance bottlenecks, such as transaction processing per second (Transaction PerSecond, TPS), query per second (Query Per Second, QPS), memory capacity, disk A series of system resources such as capacity will encounter various restrictions. The distributed database was born to solve this problem. The data in the original stand-alone database is distributed and stored on multiple data storage nodes connected through the network to obtain larger storage capacity and higher concurrent access. [0005] In a distributed database sy...

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Problems solved by technology

[0006] However, the MVCC mechanism will increase the storage overhead of the database

For example, in a distributed database system, the processing speed is 100 batches of transactions per second. Suppose a sub-database is delayed for 10 minutes due to a failure, and other sub-databases need to save 10×60×100=60,000 data versions. This will take up a lot of disk capacity on the sub-library

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