Serverless Query Processing with Flexible Performance SLAs and Prices

TL;DR

This paper introduces PixelsDB, a serverless query engine that offers flexible performance SLAs and pricing, significantly reducing costs while maintaining performance guarantees for cloud data workloads.

Contribution

It presents PixelsDB, an innovative serverless query system with architectural designs supporting multiple service levels and cost-efficient performance guarantees.

Findings

Reduces resource costs by 65.5% on benchmark workloads.

Supports multiple service levels with dedicated architectural designs.

Maintains performance guarantees while lowering costs.

Abstract

Serverless query processing has become increasingly popular due to its auto-scaling, high elasticity, and pay-as-you-go pricing. It allows cloud data warehouse (or lakehouse) users to focus on data analysis without the burden of managing systems and resources. Accordingly, in serverless query services, users become more concerned about cost-efficiency under acceptable performance than performance under fixed resources. This poses new challenges for serverless query engine design in providing flexible performance service-level agreements (SLAs) and cost-efficiency (i.e., prices). In this paper, we first define the problem of flexible performance SLAs and prices in serverless query processing and discuss its significance. Then, we envision the challenges and solutions for solving this problem and the opportunities it raises for other database research. Finally, we present PixelsDB, an open-source prototype with three service levels supported by dedicated architectural designs. Evaluations show that PixelsDB reduces resource costs by 65.5\% for near-real-world workloads generated by Cloud Analytics Benchmark (CAB) while not violating the pending time guarantees.