S. Sakr, T. Rabl, Martin Hirzel, Paris Carbone, M. Strohbach
{"title":"Dagstuhl Seminar on Big Stream Processing","authors":"S. Sakr, T. Rabl, Martin Hirzel, Paris Carbone, M. Strohbach","doi":"10.1145/3316416.3316426","DOIUrl":null,"url":null,"abstract":"Stream processing can generate insights from big data in real time as it is being produced. This paper reports findings from a 2017 seminar on big stream processing, focusing on applications, systems, and languages.","PeriodicalId":21740,"journal":{"name":"SIGMOD Rec.","volume":"126 1","pages":"36-39"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGMOD Rec.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3316416.3316426","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Stream processing can generate insights from big data in real time as it is being produced. This paper reports findings from a 2017 seminar on big stream processing, focusing on applications, systems, and languages.