TY - GEN
T1 - Wave
T2 - 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2014
AU - Lu, Kun
AU - Sun, Mingming
AU - Li, Changlong
AU - Zhuang, Hang
AU - Zhou, Jinhong
AU - Zhou, Xuehai
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - incremental computing
KW - synchronized data process
KW - trigger based system
UR - https://www.scopus.com/pages/publications/84904576121
U2 - 10.1109/CCGrid.2014.124
DO - 10.1109/CCGrid.2014.124
M3 - 会议稿件
AN - SCOPUS:84904576121
SN - 9781479927838
T3 - Proceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014
SP - 540
EP - 541
BT - Proceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014
PB - IEEE Computer Society
Y2 - 26 May 2014 through 29 May 2014
ER -