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数据库是存储、管理和利用大量信息的有效工具。大数据环境下数据库不仅作用于结构化数据,而是更关注对非结构化数据的处理。索引是实现数据库高效检索的有效工具,数据库索引性能提升对于应对数据库处理对象复杂化具有重要意义。随着数据库类型、功能的发展,数据库索引编制也呈现出由简单到复杂、由结构到内容、由机械式到智能式的发展历程。本文结合数据库索引编制相关研究成果,对数据库索引的概念、编制原理、技术等进行分类归纳,分析了大数据时代数据库索引编制的研究呈现出索引编制对象多样化、索引内容深入化、索引技术智能化、索引呈现可视化的趋势。
Databases are powerful tools for storing, managing, and exploiting vast amounts of information. In big data environment, the database not only acts on structured data, but also focuses more on the processing of unstructured data. Indexing is an effective tool for efficient database retrieval. The performance improvement of database indexes is of great significance for dealing with the complexity of database processing objects. With the development of database types and functions, the database indexing system also shows the development process from simple to complex, from structure to content, from mechanical to intelligent. Based on the research of database indexing, this paper classifies and summarizes the concept, principle and technology of database indexing. It analyzes the research of database indexing in big data era, which shows the diversification of indexing objects, the deepening of indexing content, the indexing technology intelligence The index shows the trend of visualization.