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

As volumes of data grow and become more diverse, legacy query optimization techniques are no longer able to cope. Legacy database systems, based on static models and heuristics, are poorly suited to ...

SQL query optimization aims to choose an optimal Query Execution Plan (QEP) for a query. The existing optimizers usually choose the plan with the minimal execution cost. However, in some real ...

This repository presents research on SQL query optimization, exploring how different indexing strategies and PostgreSQL configurations impact query performance. The project, which earned second place ...

Query Optimization is principally a multifaceted exploration job that searches for best plan amongst the semantically equal plans that are obtained from any given query. The execution of any ...

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 ...