{"title":"An interval join optimized for modern hardware","authors":"Danila Piatov, S. Helmer, Anton Dignös","doi":"10.1109/ICDE.2016.7498316","DOIUrl":null,"url":null,"abstract":"We develop an algorithm for efficiently joining relations on interval-based attributes with overlap predicates, which, for example, are commonly found in temporal databases. Using a new data structure and a lazy evaluation technique, we are able to achieve impressive performance gains by optimizing memory accesses exploiting features of modern CPU architectures. In an experimental evaluation with real-world datasets our algorithm is able to outperform the state-of-the-art by an order of magnitude.","PeriodicalId":6883,"journal":{"name":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","volume":"140 1","pages":"1098-1109"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2016.7498316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 51
Abstract
We develop an algorithm for efficiently joining relations on interval-based attributes with overlap predicates, which, for example, are commonly found in temporal databases. Using a new data structure and a lazy evaluation technique, we are able to achieve impressive performance gains by optimizing memory accesses exploiting features of modern CPU architectures. In an experimental evaluation with real-world datasets our algorithm is able to outperform the state-of-the-art by an order of magnitude.