Cost-Intelligent Data Analytics in the Cloud

TL;DR

This paper advocates for integrating cost-awareness into cloud data warehouse optimization, proposing a new architecture focused on automatic resource deployment and cost-based auto-tuning to enhance efficiency and reduce expenses.

Contribution

It introduces the concept of cost intelligence and outlines a novel architecture for cloud data warehouses emphasizing cost-aware optimization components.

Findings

Proposes a new architecture for cost-aware cloud data warehouses.

Identifies key challenges in automatic resource deployment and auto-tuning.

Highlights research opportunities in cost intelligence for cloud analytics.

Abstract

For decades, database research has focused on optimizing performance under fixed resources. As more and more database applications move to the public cloud, we argue that it is time to make cost a first-class citizen when solving database optimization problems. In this paper, we introduce the concept of cost intelligence and envision the architecture of a cloud data warehouse designed for that. We investigate two critical challenges to achieving cost intelligence in an analytical system: automatic resource deployment and cost-oriented auto-tuning. We describe our system architecture with an emphasis on the components that are missing in today's cloud data warehouses. Each of these new components represents unique research opportunities in this much-needed research area.