S\'election simultan\'ee d'index et de vues mat\'erialis\'ees

TL;DR

This paper proposes a combined approach for selecting indexes and materialized views in data warehouses, optimizing storage and performance by considering their interactions.

Contribution

It introduces a joint selection method using cost models and a greedy algorithm to improve over independent selection strategies.

Findings

Joint selection outperforms independent methods in experiments.

Cost models effectively evaluate benefits of indexes and views.

Strategy reduces storage overhead while maintaining query performance.

Abstract

Indices and materialized views are physical structures that accelerate data access in data warehouses. However, these data structures generate some maintenance overhead. They also share the same storage space. The existing studies about index and materialized view selection consider these structures separately. In this paper, we adopt the opposite stance and couple index and materialized view selection to take into account the interactions between them and achieve an efficient storage space sharing. We develop cost models that evaluate the respective benefit of indexing and view materialization. These cost models are then exploited by a greedy algorithm to select a relevant configuration of indices and materialized views. Experimental results show that our strategy performs better than the independent selection of indices and materialized views.