Abstract: With the increasing of electrical architecture, a large amount of driving data will be reported during vehicle operation. The amount of data processed in the database increases, and the difficulty of request is also upgrading. In order to save a large amount of vehicle data for a long time and stably, quickly query the required data to provide data analysis for R&D engineers, it is necessary to design a relational database suitable for storing vehicle data. As an advanced open source database, PostgreSQL supports complex queries, concurrency control and other functions. This paper proposes a design optimization method of multi thread parallel query, creating data table index, adding database partition and application connection pool for vehicle based relational database, and provides targeted optimization strategies for database operation efficiency. The test results show that the database performance improvement method proposed in this paper can improve the data request efficiency several times, and the database performance has been greatly improved.

Key words: Relational database; PostgreSQL; Parallel query; Data table index; Database partition

摘要： 随着电器架构的日益增多，车辆运行过程中会上报大量的行车数据，使用数据库处理 的数据量增加，请求难度也在升级，为了能够长期稳定地保存大量的车辆数据，快速查询出 所需数据为研发工程师提供数据分析，需要设计出适合存放车辆数据的关系型数据库。 PostgreSQL 作为先进的开源数据库，支持复杂查询、并发控制等功能。文章针对基于车辆的 关系型数据库提出多线程并行查询、创建数据表索引、添加数据库分区以及应用程序连接池 的设计优化方法，针对性地对数据库的运行效率提供优化策略。测试结果表明，文章所提出 的数据库性能提升方法能将数据请求效率提升数倍，数据库的性能得到极大提升。

关键词: 关系型数据库；PostgreSQL；并行查询；数据表索引；数据库分区