HOPE: Iterative and interactive database partitioning for OLTP workloads

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 partitio...

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Bibliographic Details
Published in2014 IEEE 30th International Conference on Data Engineering pp. 1274 - 1277
Main Authors Yu Cao, Xiaoyan Guo, Baoyao Zhou, Todd, Stephen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2014
Subjects
Computer architecture
Database systems
Distributed databases
Partitioning algorithms
Scalability
Throughput
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Summary: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.
ISSN:1063-6382
2375-026X
DOI:10.1109/ICDE.2014.6816759