Cost Models for Selecting Materialized Views in Public Clouds

TL;DR

This paper presents new cost models tailored for selecting materialized views in cloud data warehouses, balancing query performance and monetary costs in a pay-as-you-go environment.

Contribution

It introduces novel cost models for view selection in cloud data warehouses, considering both performance and cost, and formulates an optimization problem for effective materialized view selection.

Findings

Maintaining materialized views improves performance and cost-efficiency.

The proposed models effectively balance query response time and monetary cost.

Experimental results validate the advantages of materialized views in cloud environments.

Abstract

Data warehouse performance is usually achieved through physical data structures such as indexes or materialized views. In this context, cost models can help select a relevant set ofsuch performance optimization structures. Nevertheless, selection becomes more complex in the cloud. The criterion to optimize is indeed at least two-dimensional, with monetary cost balancing overall query response time. This paper introduces new cost models that fit into the pay-as-you-go paradigm of cloud computing. Based on these cost models, an optimization problem is defined to discover, among candidate views, those to be materialized to minimize both the overall cost of using and maintaining the database in a public cloud and the total response time ofa given query workload. We experimentally show that maintaining materialized views is always advantageous, both in terms of performance and cost.