Work

A Runtime System for Interruptible Query Processing: When Incremental Computing Meets Fine-Grained Parallelism

Year: 2024

Type: article

Abstract: Online data services have stringent performance requirement and must tolerate workload fluctuation. This paper introduces P it S top , a new query language runtime design built on the idea of interruptible query processing : the time-consuming task of data inspection for processing each query or update may be interrupted and resumed later at the boundary of fine-grained data partitions. This counter-intuitive idea enables a novel form of fine-grained concurrency while preserving sequential consistency . We build P it S top through modifying the language runtime of Cypher, the query language of a state-of-the-art graph database, Neo4j. Our evaluation on the Google Cloud shows that P it S top can outperform unmodified Neo4j during workload fluctuation, with reduced latency and increased throughput.

Source: Proceedings of the ACM on Programming Languages

DOI: 10.1145/3689772

Authors: Jeff Eymer, Philip Dexter, Joseph Raskind, Yu David Liu

Institution: Binghamton University

Language: English

Topic: Advanced Database Systems and Queries

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: National Science Foundation

Award: SHF: Small: Lazy Data Structures for Data-Intensive Applications