Google's AI Mode synthesizes answers from multiple background queries. Here's how to optimize content passages for inclusion in AI responses.

In the ever-growing world of data management, Sayantan Saha explores the revolutionary advances in AI-powered query optimization. These innovations are reshaping how database systems handle complex ...

Contains implementations of various algorithms for database query optimization. The algorithms cover multiple problem variants (e.g., traditional and multi-objective query optimization) and offer ...

This paper describes an implementation of Kruskal's algorithm in query optimization process for generation of a near optimal execution query tree. The open source Post- greSQL DBMS was used in the ...

By combining machine learning and adaptive query execution, query optimization in Presto could become smarter and more efficient over repeated use.

Bitvector filtering is an important query processing technique that can significantly reduce the cost of execution, especially for complex decision support queries with multiple joins. Despite its ...

Query optimization is a fundamental problem in data management. Simply put, most database query languages are declarative rather than imperative—that is, they specify properties the answer should ...

Figure 6. Multi-objective parametric query optimization generalizes the cost models of multi-objective and of parametric query optimization. The algorithm that we propose in this paper allows to solve ...