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人工智能增强的数据库管理系统

AI-Enhanced Database Management System

  • 摘要: 随着大数据和云计算的发展,传统数据库管理系统在处理海量数据规模、复杂业务需求上面临显著挑战。人工智能技术的快速发展为数据库系统的智能化演进提供了新的解决方案。本文探讨了人工智能增强的数据库管理系统的关键技术及未来趋势,重点分析了深度学习、强化学习在存储优化、索引优化、查询代价估计、自动调参等方面的应用,并展望了前沿人工智能技术与数据库融合的发展趋势。通过将人工智能技术与数据库系统深度融合,可显著提升系统的自治能力与性能表现,为下一代智能数据库管理系统发展提供重要技术支撑。

     

    Abstract: With the rapid development of big data and cloud computing, traditional database management systems face significant challenges in handling massive data volumes and complex business requirements. The advancement of artificial intelligence (AI) technologies provides new solutions for the intelligent evolution of database systems. This article explores the key technologies and future trends of AI-enhanced database management systems, with a focus on the applications of deep learning and reinforcement learning in storage optimization, index optimization, query cost estimation, and automated parameter tuning. Furthermore, we discuss the emerging trends in the integration of cutting-edge AI technologies with database systems. By deeply integrating AI techniques into database systems, the autonomy and performance of these systems can be significantly improved, providing essential technical support for the development of next-generation intelligent database management systems.

     

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