{"title":"技术的角度来看","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":"{\"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}","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}
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.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
