S. Karthik, J. Haritsa, Sreyash Kenkre, Vinayaka Pandit
{"title":"独立于平台的健壮查询处理","authors":"S. Karthik, J. Haritsa, Sreyash Kenkre, Vinayaka Pandit","doi":"10.1109/ICDE.2016.7498251","DOIUrl":null,"url":null,"abstract":"To address the classical selectivity estimation problem in databases, a radically different approach called PlanBouquet was recently proposed in [3], wherein the estimation process is completely abandoned and replaced with a calibrated discovery mechanism. The beneficial outcome of this new construction is that, for the first time, provable guarantees are obtained on worst-case performance, thereby facilitating robust query processing.","PeriodicalId":6883,"journal":{"name":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","volume":"4 1","pages":"325-336"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Platform-independent robust query processing\",\"authors\":\"S. Karthik, J. Haritsa, Sreyash Kenkre, Vinayaka Pandit\",\"doi\":\"10.1109/ICDE.2016.7498251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To address the classical selectivity estimation problem in databases, a radically different approach called PlanBouquet was recently proposed in [3], wherein the estimation process is completely abandoned and replaced with a calibrated discovery mechanism. The beneficial outcome of this new construction is that, for the first time, provable guarantees are obtained on worst-case performance, thereby facilitating robust query processing.\",\"PeriodicalId\":6883,\"journal\":{\"name\":\"2016 IEEE 32nd International Conference on Data Engineering (ICDE)\",\"volume\":\"4 1\",\"pages\":\"325-336\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 32nd International Conference on Data Engineering (ICDE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2016.7498251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 32nd International Conference on Data Engineering (ICDE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2016.7498251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To address the classical selectivity estimation problem in databases, a radically different approach called PlanBouquet was recently proposed in [3], wherein the estimation process is completely abandoned and replaced with a calibrated discovery mechanism. The beneficial outcome of this new construction is that, for the first time, provable guarantees are obtained on worst-case performance, thereby facilitating robust query processing.
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