Paper Info
Title
Wave: Trigger Based Synchronous Data Process System
Abstract
With the rapid development of cloud computing, more and more applications need to process large amount of data on clusters. Different types of data processing frameworks in cloud have appeared, such as MapReduce, Spark and Percolator. These frameworks are used to a certain type of data processing. In this paper, we provide processing framework called Wave, which is designed for bulk data processing, incremental computing and iterative processing with a uniform application interface. Wave is an event driven data process model for semi-structured data of distributed systems. Programmers use events and trigger reactions to process the data. Wave provides simplified API for users to implements parallel programs on cluster. Programs running in Wave are automatically parallelized and executed on cluster synchronously. Wave uses an implicit mechanism to synchronize the parallel program's execution without any user specification.
Year
DOI
Venue
2014
10.1109/CCGrid.2014.124
CCGrid
Keywords
Field
DocType
percolator,parallel program,mapreduce,iterative processing,pattern clustering,application program interfaces,bulk data processing,parallel programming,trigger based synchronous data process system,synchronized data process,incremental computing,rapid development,event driven data process model,trigger based system,data processing framework,spark,user specification,api,cloud computing,distributed system,application interface,semistructured data,data models,data processing,generators,synchronization,computational modeling,programming,distributed databases
Data modeling,Synchronization,Data processing,Data-intensive computing,Computer science,Real-time computing,Distributed database,Distributed computing
Conference
ISSN
Citations 
PageRank 
2376-4414
1
0.36
References 
Authors
1
6
Name
Order
Citations
PageRank
Kun Lu1213.75
Mingming Sun2324.87
Changlong Li3266.88
Hang Zhuang4266.54
Jinhong Zhou593.40
Xuehai Zhou655177.54