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