{"title":"Technical Perspective","authors":"R. Pagh","doi":"10.1145/3542700.3542716","DOIUrl":null,"url":null,"abstract":"The paper Relative Error Streaming Quantiles, by Graham Cormode, Zohar Karnin, Edo Liberty, Justin Thaler and Pavel Vesel´y studies a fundamental question in data stream processing, namely how to maintain information about the distribution of data in the form of quantiles. More precisely, given a stream S of elements from some ordered universe U we wish to maintain a compact summary data structure that allows us to estimate the number of elements in the stream that are smaller than a given query element y 2 U, i.e., estimate the rank of y. Solutions to this problem have numerous applications in large-scale data analysis and can potentially be used for range query selectivity estimation in database engines.","PeriodicalId":346332,"journal":{"name":"ACM SIGMOD Record","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGMOD Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3542700.3542716","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
The paper Relative Error Streaming Quantiles, by Graham Cormode, Zohar Karnin, Edo Liberty, Justin Thaler and Pavel Vesel´y studies a fundamental question in data stream processing, namely how to maintain information about the distribution of data in the form of quantiles. More precisely, given a stream S of elements from some ordered universe U we wish to maintain a compact summary data structure that allows us to estimate the number of elements in the stream that are smaller than a given query element y 2 U, i.e., estimate the rank of y. Solutions to this problem have numerous applications in large-scale data analysis and can potentially be used for range query selectivity estimation in database engines.
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