Domino: An incremental computing framework In cloud with eventual synchronization

Dong Dai, Yong Chen, Dries Kimpe, Rob Ross, Xuehai Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

In recent years, more and more applications in cloud have needed to process large-scale on-line data sets that evolve over time as entries are added or modified. Several programming frameworks, such as Percolator and Oolong, are proposed for such incremental data processing and can achieve efficient updates with an event-driven abstraction. However, these frameworks are inherently asynchronous, leaving the heavy burden of managing synchronization to applications developers. Such a limitation significantly restricts their usability. In this paper, we introduce a trigger-based incremental computing framework, called Domino, with a flexible synchronization mechanism and runtime optimizations to coordinate parallel triggers efficiently. With this new framework, both synchronous and asynchronous applications can be seamlessly developed. Use cases and current evaluation results confirm that the new Domino programming model delivers sufficient performance and is easy to use in large-scale distributed computing.

Original languageEnglish
Title of host publicationHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery
Pages291-294
Number of pages4
ISBN (Print)9781450327480
DOIs
StatePublished - 2014
Event23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014 - Vancouver, BC, Canada
Duration: Jun 23 2014Jun 27 2014

Publication series

NameHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing

Conference

Conference23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014
Country/TerritoryCanada
CityVancouver, BC
Period06/23/1406/27/14

Keywords

  • Cloud computing
  • Incremental computing
  • Mapreduce

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