Machine learning (ML) techniques for optimizing data management problems have been
extensively studied and widely deployed in recent five years. However traditional ML …

The escalating complexity of micro-services architecture in cloud-native technologies poses
significant challenges for maintaining system stability and efficiency. To conduct root cause …

Query rewriting is one of the most effective techniques for coping with poorly written queries
before passing them down to the query optimizer. Manual rewriting is not scalable, as it is …

Traditional data analysis methods require users to write programming codes or issue SQL
queries to analyze the data, which are inconvenient for ordinary users. Large language …

As software systems grow increasingly intricate, Artificial Intelligence for IT Operations
(AIOps) methods have been widely used in software system failure management to ensure …

The development of Large Language Models (LLMs) has revolutionized Q&A across various
industries, including the database domain. However, there is still a lack of a comprehensive …

数据库是计算机服务中的重要基础组件, 然而其运行中可能出现性能异常, 影响业务服务质量.
如何对数据库产生的性能异常进行诊断成为工业界与学术界的热点问题. 近年来 …

While Large Language Models (LLMs) like ChatGPT and GPT-4 have demonstrated
exceptional proficiency in natural language processing, their efficacy in addressing complex …

With the growing significance of data analysis, several studies aim to provide precise
answers to users' natural language questions from tables, a task referred to as tabular …

Machine learning algorithms have shown promising performance in many data
management tasks, such as data processing [23], database optimization [30][17], data …