📄 中文摘要
该研究提出了一种混合 SQL 和向量检索系统，旨在处理长文本文件而无需进行模式更改、数据迁移或性能折衷。通过结合传统 SQL 数据库的结构化查询能力与向量检索的灵活性，系统能够高效地从长文本中提取信息，满足现代数据处理的需求。此方法不仅降低了成本，还提高了信息检索的效率，适用于各种应用场景，尤其是在需要处理大量文本数据的情况下。研究结果显示，该系统在保持高性能的同时，能够有效地管理复杂的数据集，为未来的数据库设计提供了新的思路。
在 SQL 表中构建成本高效的代理 RAG 以处理长文本文件
出处: Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
发布: 2026年2月18日
📄 English Summary
Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
This study presents a hybrid SQL and vector retrieval system designed to handle long-text documents without requiring schema changes, data migration, or performance trade-offs. By combining the structured query capabilities of traditional SQL databases with the flexibility of vector retrieval, the system efficiently extracts information from lengthy texts, addressing the demands of modern data processing. This approach not only reduces costs but also enhances the efficiency of information retrieval, making it suitable for various applications, particularly in scenarios involving large volumes of text data. Results indicate that the system effectively manages complex datasets while maintaining high performance, offering new insights for future database design.