{"title":"在谷歌重塑后端子集","authors":"Peter Ward, Paul Wankadia, Kavita Guliani","doi":"10.1145/3570937","DOIUrl":null,"url":null,"abstract":"Backend subsetting is useful for reducing costs and may even be necessary for operating within the system limits. For more than a decade, Google used deterministic subsetting as its default backend subsetting algorithm, but although this algorithm balances the number of connections per backend task, deterministic subsetting has a high level of connection churn. Our goal at Google was to design an algorithm with reduced connection churn that could replace deterministic subsetting as the default backend subsetting algorithm.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"33 - 57"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reinventing Backend Subsetting at Google\",\"authors\":\"Peter Ward, Paul Wankadia, Kavita Guliani\",\"doi\":\"10.1145/3570937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Backend subsetting is useful for reducing costs and may even be necessary for operating within the system limits. For more than a decade, Google used deterministic subsetting as its default backend subsetting algorithm, but although this algorithm balances the number of connections per backend task, deterministic subsetting has a high level of connection churn. Our goal at Google was to design an algorithm with reduced connection churn that could replace deterministic subsetting as the default backend subsetting algorithm.\",\"PeriodicalId\":39042,\"journal\":{\"name\":\"Queue\",\"volume\":\"20 1\",\"pages\":\"33 - 57\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Queue\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3570937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Queue","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3570937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Backend subsetting is useful for reducing costs and may even be necessary for operating within the system limits. For more than a decade, Google used deterministic subsetting as its default backend subsetting algorithm, but although this algorithm balances the number of connections per backend task, deterministic subsetting has a high level of connection churn. Our goal at Google was to design an algorithm with reduced connection churn that could replace deterministic subsetting as the default backend subsetting algorithm.