A. Bonifati, Stefania Dumbrava, G. Fletcher, J. Hidders, Matthias Hofer, W. Martens, Filip Murlak, Joshua Shinavier, S. Staworko, Dominik Tomaszuk
{"title":"阈值查询","authors":"A. Bonifati, Stefania Dumbrava, G. Fletcher, J. Hidders, Matthias Hofer, W. Martens, Filip Murlak, Joshua Shinavier, S. Staworko, Dominik Tomaszuk","doi":"10.1145/3604437.3604452","DOIUrl":null,"url":null,"abstract":"Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. We explore how such queries appear in practice and present a method that can be used to significantly improve the asymptotic bounds of their state-of-the-art evaluation algorithms. Our experimental evaluation of these methods shows order-of-magnitude performance improvements.","PeriodicalId":346332,"journal":{"name":"ACM SIGMOD Record","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Threshold Queries\",\"authors\":\"A. Bonifati, Stefania Dumbrava, G. Fletcher, J. Hidders, Matthias Hofer, W. Martens, Filip Murlak, Joshua Shinavier, S. Staworko, Dominik Tomaszuk\",\"doi\":\"10.1145/3604437.3604452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. We explore how such queries appear in practice and present a method that can be used to significantly improve the asymptotic bounds of their state-of-the-art evaluation algorithms. Our experimental evaluation of these methods shows order-of-magnitude performance improvements.\",\"PeriodicalId\":346332,\"journal\":{\"name\":\"ACM SIGMOD Record\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-07\",\"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/10.1145/3604437.3604452\",\"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/10.1145/3604437.3604452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Threshold queries are an important class of queries that only require computing or counting answers up to a specified threshold value. To the best of our knowledge, threshold queries have been largely disregarded in the research literature, which is surprising considering how common they are in practice. We explore how such queries appear in practice and present a method that can be used to significantly improve the asymptotic bounds of their state-of-the-art evaluation algorithms. Our experimental evaluation of these methods shows order-of-magnitude performance improvements.