Intra-Query Runtime Elasticity for Cloud-Native Data Analysis

TL;DR

This paper introduces Intra-Query Runtime Elasticity (IQRE), enabling cloud-native data analysis engines to dynamically adjust query parallelism during execution for better resource efficiency and cost savings.

Contribution

It presents Accordion, the first IQRE query engine that adjusts parallelism on-the-fly without pausing, with a user interface and auto-tuner for latency-based DOP adjustments.

Findings

Accordion effectively reduces resource consumption.

It allows real-time DOP adjustments during query execution.

Users can meet latency constraints while optimizing costs.

Abstract

We propose the concept of Intra-Query Runtime Elasticity (IQRE) for cloud-native data analysis. IQRE enables a cloud-native OLAP engine to dynamically adjust a query's Degree of Parallelism (DOP) during execution. This capability allows users to utilize cloud computing resources more cost-effectively. We present Accordion, the first IQRE query engine. Accordion can adjust the parallelism of a query at any point during query execution without pausing data processing. It features a user-friendly interface and an auto-tuner backed by a "what-if" service to allow users to adjust the DOP according to their query latency constraints. The design of Accordion follows the execution model in Presto, an open-source distributed SQL query engine developed at Meta. We present the implementation of Accordion and demonstrate its ease of use, showcasing how it enables users to minimize compute resource consumption while meeting their query time constraints.