Relational Database Query Optimization Strategy Based on Industrial Internet Situation Awareness System

Abstract

In relational databases, when the amount of data in a single table is too large, the retrieval performance of the data table will drop sharply. In this regard, this paper proposes a retrieval optimization strategy of relational databases based on the change data capture mechanism. Log-based data capture mechanism to capture the addition, deletion, and modification of relational databases in real time, and synchronize the changes of specified fields in the relational database to the non-relational database Elasticsearch in near real time. Elasticsearch stores all search conditions. Using Elasticsearch's advantages in the field of massive data retrieval, it effectively solves the retrieval problem of data tables with excessive data in a single table. At the same time, through the change data capture mechanism, unnecessary indexes in relational databases are reduced, and database data writing is improved. Performance. Applying the retrieval strategy proposed in this article to an industrial Internet situational awareness system proves that the strategy can effectively improve the data retrieval ability and performs well.