{"title":"计算或不计算:大空间数据分析的计算挑战","authors":"E. Tanin, Hairuo Xie","doi":"10.1145/2809948.2809954","DOIUrl":null,"url":null,"abstract":"Counts of objects are important for big data analytics. However, spatial objects do not work well with counts. We present the latest developments on distinct counting problem. In particular, we explain Euler Histograms, which are a category of spatial data structures that address the distinct counting challenges. Euler histograms support traditional counting queries as well as other query types.","PeriodicalId":142249,"journal":{"name":"Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Count or Not to Count: Counting Challenges for Big Spatial Data Analytics\",\"authors\":\"E. Tanin, Hairuo Xie\",\"doi\":\"10.1145/2809948.2809954\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Counts of objects are important for big data analytics. However, spatial objects do not work well with counts. We present the latest developments on distinct counting problem. In particular, we explain Euler Histograms, which are a category of spatial data structures that address the distinct counting challenges. Euler histograms support traditional counting queries as well as other query types.\",\"PeriodicalId\":142249,\"journal\":{\"name\":\"Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2809948.2809954\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2809948.2809954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Count or Not to Count: Counting Challenges for Big Spatial Data Analytics
Counts of objects are important for big data analytics. However, spatial objects do not work well with counts. We present the latest developments on distinct counting problem. In particular, we explain Euler Histograms, which are a category of spatial data structures that address the distinct counting challenges. Euler histograms support traditional counting queries as well as other query types.
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