{"title":"Extending MapReduce framework with locality keys","authors":"Yifeng Chen, Bei Wang, Xiaolin Wang","doi":"10.1145/3437801.3441607","DOIUrl":null,"url":null,"abstract":"This paper extends the existing MapReduce framework to allow the user programmer to control data locality and reduce communication costs of the shuffle operations in iterative in-memory computation. The programming extension is fully consistent with the style of MapReduce and allows straightforward fast implementation.","PeriodicalId":124852,"journal":{"name":"Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3437801.3441607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper extends the existing MapReduce framework to allow the user programmer to control data locality and reduce communication costs of the shuffle operations in iterative in-memory computation. The programming extension is fully consistent with the style of MapReduce and allows straightforward fast implementation.