ViewDF: Declarative incremental view maintenance for streaming data. (November 2017)

• Record Type: Journal Article
• Authors: Yang, Yuke; Golab, Lukasz; Tamer Ozsu, M.
• Is Part Of: Information systems. Volume 71(2017)
• Page Start: 55
• Page End: 67
• Publication Date: 2017-11
• Subjects: Data stream management -- View maintenance -- Pattern matching; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2017.07.002
• Languages: English
• ISSNs: 0306-4379

Abstract

Highlights: This paper presents a flexible and declarative framework for incremental view maintenance over streaming data. A system called ViewDF is described, which implements the proposed idea. View update optimizations are evaluated within ViewDF for pattern matching queries and sliding window aggregates. Abstract: We present ViewDF: a flexible and declarative framework for incremental maintenance of materialized views (i.e., results of continuous queries) over streaming data. The main component of the proposed framework is the View Delta Function (ViewDF), which declaratively specifies how to update a materialized view when a new batch of data arrives. We describe and experimentally evaluate a prototype system based on this idea, which allows users to write ViewDFs directly and automatically translates common classes of streaming queries into ViewDFs. Our approach generalizes existing work on incremental view maintenance and enables new optimizations for views that are common in stream analytics, including those with pattern matching and sliding windows.