Data query system and method, server and computer readable storage medium

Abstract

The invention relates to a data query system and method, a server and a computer readable storage medium. The system comprises an analysis layer module, an adapter layer module and a storage engine layer module, wherein the analysis layer module is configured to analyze query parameters of each query request and send the query parameters to the adapter layer module; the adapter layer module is configured to match a target storage engine from a plurality of preset storage engines according to the query parameters, adapt the query parameters to a query model of the target storage engine, generate a query plan and send the query plan to the storage engine layer module; and the storage engine layer module is configured to execute and call a target storage engine, query target data according to the query plan, and output the target data as a query result of the query request. According to the embodiment, multiple different storage engines are arranged, so that the characteristics of each storage engine can be exerted, the data query efficiency can be improved, and the method is particularly suitable for a multi-concurrent query scene.

Description

technical field [0001] The present disclosure relates to the technical field of big data query, and in particular to a data query system, method, server, and computer-readable storage medium. Background technique [0002] At present, in related technologies, after the report is synchronized to the MySQL database, the report service can directly query the MySQL database to obtain the report required by the user. During the query process, when the total amount of queried data is less than tens of millions, the response time of the MySQL database in related technologies can be optimized to within ten seconds; however, when the total amount of queried data exceeds tens or hundreds of millions Even when there are one billion entries, due to the bottleneck of the number of searches in the storage engine, no matter how you optimize or change the indexing method, it cannot meet the requirements of multiple concurrent queries that require fast response, and will also put a lot of pre...

AI Technical Summary

Problems solved by technology

During the query process, when the total amount of queried data is less than tens of millions, the response time of the MySQL database in related technologies can be optimized to within ten seconds; however, when the total amount of queried data exceeds tens or hundreds of millions Even when there are one billion entries, due to the bottleneck of the number of searches in the storage engine, no matter how you optimize or change the indexing method, it cannot meet the requirements of multiple concurrent queries that require fast response, and will also put a lot of pressure on the database

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