{"title":"HOPE:用于OLTP工作负载的迭代和交互式数据库分区","authors":"Yu Cao, X. Guo, Baoyao Zhou, S. Todd","doi":"10.1109/ICDE.2014.6816759","DOIUrl":null,"url":null,"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.","PeriodicalId":159130,"journal":{"name":"2014 IEEE 30th International Conference on Data Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"HOPE: Iterative and interactive database partitioning for OLTP workloads\",\"authors\":\"Yu Cao, X. Guo, Baoyao Zhou, S. Todd\",\"doi\":\"10.1109/ICDE.2014.6816759\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":159130,\"journal\":{\"name\":\"2014 IEEE 30th International Conference on Data Engineering\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 30th International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2014.6816759\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 30th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2014.6816759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.