Data processing method and device, equipment and storage medium

Abstract

The invention discloses a data processing method which comprises the steps that a received first data operation message is sent to a first data access layer, the first data operation message relates to a writing method, the grammar of the first data operation message is a first grammar, and the first data access layer corresponds to a first data storage system supporting the first grammar; calling a first interface through the first data access layer so as to send the first data operation message to the first data storage system through the first interface; determining a second data operation message obtained after the first data operation message is subjected to grammar conversion through a data synchronization program, wherein the grammar of the second data operation message is a second grammar; and sending the second data operation message to a second data storage system supporting a second grammar through the called second interface. The invention further discloses another data processing method, a device for implementing the data processing method, equipment and a storage medium.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technology, and relate to but are not limited to a data processing method, device, device, and storage medium. Background technique [0002] With the rapid growth of business data volume, the query volume and calculation complexity are very large, it is difficult for the relational database management system (mySQL) to support the existing business volume. In order to expand the capacity, the current solution is to divide the database and table (sharding)) to complete the horizontal expansion. However, after sub-database and sub-table, the problem brought about is that the query must bring routing fields, which makes cross-database complex, resulting in low efficiency of joint table query and data statistics. At this time, distributed Multi-user capable full-text search engine (Elasticsearch) to solve the problem of low efficiency. [0003] However, after the search engine is i...

AI Technical Summary

Problems solved by technology

[0002] With the rapid growth of business data volume, the query volume and calculation complexity are very large, it is difficult for the relational database management system (mySQL) to support the existing business volume. In order to expand the capacity, the current solution is to divide the database and table (sharding)) to complete the horizontal expansion. However, after sub-database and sub-table, the problem brought about is that the query must bring routing fields, which makes cross-database complex, resulting in low efficiency of joint table query and data statistics. At this time, distributed A full-text search engine (Elasticsearch) with multi-user capabilities to solve the problem of low efficiency

[0003] However, after the search engine is introduced, developers need to re-learn the Application Programming Interface (API) of Elasticsearch, resulting in an increase in learning costs and development costs

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