{"title":"使用弱节点集群的能量比例查询执行","authors":"D. Schall, T. Härder","doi":"10.1145/2485278.2485279","DOIUrl":null,"url":null,"abstract":"Because energy use of single-server systems is far from being energy proportional, we explore whether or not better energy efficiency may be achieved by a cluster of nodes whose size is dynamically adjusted to the current workload demand. As data-intensive workloads, we submit specific TPC-H queries against a distributed shared-nothing DBMS, where time and energy use are captured by specific monitoring and measurement devices. We configure various static clusters of varying sizes and show their influence on energy efficiency and performance. Further, using an EnergyController and a load-aware scheduler, we verify the hypothesis that energy proportionality can be well approximated by dynamic clusters.","PeriodicalId":298901,"journal":{"name":"International Workshop on Data Management on New Hardware","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Energy-proportional query execution using a cluster of wimpy nodes\",\"authors\":\"D. Schall, T. Härder\",\"doi\":\"10.1145/2485278.2485279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Because energy use of single-server systems is far from being energy proportional, we explore whether or not better energy efficiency may be achieved by a cluster of nodes whose size is dynamically adjusted to the current workload demand. As data-intensive workloads, we submit specific TPC-H queries against a distributed shared-nothing DBMS, where time and energy use are captured by specific monitoring and measurement devices. We configure various static clusters of varying sizes and show their influence on energy efficiency and performance. Further, using an EnergyController and a load-aware scheduler, we verify the hypothesis that energy proportionality can be well approximated by dynamic clusters.\",\"PeriodicalId\":298901,\"journal\":{\"name\":\"International Workshop on Data Management on New Hardware\",\"volume\":\"2011 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Data Management on New Hardware\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2485278.2485279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Data Management on New Hardware","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2485278.2485279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy-proportional query execution using a cluster of wimpy nodes
Because energy use of single-server systems is far from being energy proportional, we explore whether or not better energy efficiency may be achieved by a cluster of nodes whose size is dynamically adjusted to the current workload demand. As data-intensive workloads, we submit specific TPC-H queries against a distributed shared-nothing DBMS, where time and energy use are captured by specific monitoring and measurement devices. We configure various static clusters of varying sizes and show their influence on energy efficiency and performance. Further, using an EnergyController and a load-aware scheduler, we verify the hypothesis that energy proportionality can be well approximated by dynamic clusters.