DocumentCode :
140990
Title :
HOPE: Iterative and interactive database partitioning for OLTP workloads
Author :
Yu Cao ; Xiaoyan Guo ; Baoyao Zhou ; Todd, Simon
Author_Institution :
EMC Labs., USA
fYear :
2014
fDate :
March 31 2014-April 4 2014
Firstpage :
1274
Lastpage :
1277
Abstract :
This paper demonstrates HOPE, an efficient and effective database partitioning system that is designed for OLTP workloads. HOPE is built on top of a novel tuple-group based database partitioning model, which is able to minimize the number of distributed transactions as well as the extent of partition and workload skews during the workload execution. HOPE conducts the partitioning in an iterative manner in order to achieve better partitioning quality, save the user´s time spent on partitioning design and increase its application scenes. HOPE is also highly interactive, as it provides rich opportunities for the user to help it further improve the partitioning quality by passing expertise and indirect domain knowledge.
Keywords :
transaction processing; HOPE system; OLTP workloads; database partitioning system; distributed transactions; domain knowledge; hypergraph based OLTP database partitioning engine; online transaction processing; partitioning design; partitioning quality; tuple-group based database partitioning model; workload execution; Computer architecture; Database systems; Distributed databases; Partitioning algorithms; Scalability; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2014 IEEE 30th International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/ICDE.2014.6816759
Filename :
6816759
Link To Document :
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