Data query method and device based on Elasticsearch

Abstract

The embodiment of the invention provides a data query method and device based on Elasticsearch, and relates to the technical field of data query, and the data query method based on Elasticsearch comprises the steps of firstly, acquiring an SQL data query instruction input by a user; then determining an aggregation statistical parameter according to the SQL data query instruction, and generating a comprehensive query statement according to the aggregation statistical parameter and the SQL data query instruction; and finally, performing Elasticsearch-based query according to the comprehensive query statement to obtain a data query result, so that multi-dimensional aggregation index statistics can be realized by directly compiling an SQL data query instruction, relatively complex Elasticsearch DSL query grammar does not need to be learned, the query grammar is simplified, the learning cost of business developers is reduced, and the retrieval efficiency is improved.

Description

technical field [0001] The present application relates to the technical field of data query, in particular, to an Elasticsearch-based data query method and device. Background technique [0002] ElasticSearch is a distributed, highly scalable, and high-real-time search and data analysis engine that enables the analysis of massive log data. Existing ElasticSearch-based data query methods are usually implemented through DSL (Domain Specific Language, Domain Specific Language) query statements. However, it has been found in practice that the existing data query methods based on ElasticSearch need to learn a more complex DSL language, which is too professional for most users and difficult to use. When you are not familiar with professional query syntax, use professional Syntax for retrieval is very inefficient. It can be seen that the existing data query method based on ElasticSearch needs to learn DSL language, which has high learning cost and reduces retrieval efficiency. C...

AI Technical Summary

Problems solved by technology

However, it has been found in practice that the existing data query methods based on ElasticSearch need to learn a more complex DSL language, which is too professional for most users and difficult to use. When you are not familiar with professional query syntax, use professional Grammatical retrieval is very inefficient

It can be seen that the existing ElasticSearch-based data query methods need to learn DSL language, which has high learning costs and reduces retrieval efficiency.

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