all AI news
LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency
April 22, 2024, 4:47 a.m. | Zhaodonghui Li, Haitao Yuan, Huiming Wang, Gao Cong, Lidong Bing
cs.CL updates on arXiv.org arxiv.org
Abstract: Query rewrite, which aims to generate more efficient queries by altering a SQL query's structure without changing the query result, has been an important research problem. In order to maintain equivalence between the rewritten query and the original one during rewriting, traditional query rewrite methods always rewrite the queries following certain rewrite rules. However, some problems still remain. Firstly, existing methods of finding the optimal choice or sequence of rewrite rules are still limited and …
abstract arxiv boosting cs.cl cs.db efficiency generate language language model large language large language model llm queries query research sql sql query type
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Data Engineer (m/f/d)
@ Project A Ventures | Berlin, Germany
Principle Research Scientist
@ Analog Devices | US, MA, Boston