Serverless Query Processing with Flexible Performance SLAs and Prices

arXiv - CS - Databases Pub Date : 2024-09-02 DOI:arxiv-2409.01388

Haoqiong Bian, Dongyang Geng, Yunpeng Chai, Anastasia Ailamaki

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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.

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具有灵活性能 SLA 和价格的无服务器查询处理

无服务器查询处理因其自动扩展、高弹性和即用即付的价格而越来越受欢迎。它允许云数据仓库（或湖库）用户专注于数据分析，而无需承担管理系统和资源的负担。因此，在无服务器查询服务中，用户更关心的是可接受性能下的成本效益，而不是固定资源下的性能。这对无服务器查询引擎的设计提出了新的挑战，即提供灵活的性能服务级别协议（SLA）和成本效益（即价格）。在本文中，我们首先定义了无服务器查询处理中灵活的性能服务级别协议和价格问题，并讨论了其意义。然后，我们展望了解决这一问题的挑战和解决方案，以及它为其他数据库研究带来的机遇。最后，我们介绍了像素数据库（PixelsDB），这是一个开源原型，通过专用架构设计支持三种服务级别。评估结果表明，在云分析基准（CAB）生成的接近真实世界的工作负载中，PixelsDB降低了65.5%的资源成本，同时没有违反待处理时间保证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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arXiv - CS - Databases

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