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Larch 框架优化 AI SQL 查询执行

研究人员开发了 Larch,一个旨在优化 AI SQL 查询中语义过滤器执行的新框架。Larch 解决了语义运算符相关的高推理成本和延迟问题,这些运算符将 AI 生成的过滤器视为黑箱,阻碍了传统优化。该框架利用增强嵌入的神经网络和监督学习模型来预测过滤器选择性并确定最佳评估顺序,从而显著减少了 token 使用量。 AI

影响 优化 AI 驱动的数据库查询,可能降低 AI 数据分析的成本并提高其性能。

排序理由 这是一篇详细介绍查询优化新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Larch 框架优化 AI SQL 查询执行

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这是一篇详细介绍查询优化新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Fuheng Zhao, Pawel Liskowski, Zihan Li, Benjamin Han, Puxuan Yu, Varich Boonsanong, Dimitris Tsirogiannis, Anupam Datta ·

    Larch: 学习型查询优化器用于语义谓词

    arXiv:2606.07923v1 Announce Type: cross Abstract: With the advent of Large Language Models (LLMs), many database systems introduced semantic operators that enabled analytical queries over unstructured data (e.g. text, images, videos). Semantic operators typically incur high infer…