{"title":"Fast approximate query answering using precomputed statistics","authors":"V. Poosala, Venkatesh Ganti","doi":"10.1109/ICDE.1999.754932","DOIUrl":null,"url":null,"abstract":"Summary form only given. The last few years have witnessed a significant increase in the use of databases for complex data analysis (OLAP) applications. These applications often require very quick responses from the DBMS. However, they also involve complex queries on large volumes of data. Despite significant improvement in database support for OLAP over the last few years, most DBMSs still fall short of providing quick enough responses. We present a novel solution to this problem: we use small amounts of precomputed summary statistics of the data to answer the queries quickly, albeit approximately. Our hypothesis is that many OLAP applications can tolerate approximations in query results in return for huge response time reductions. The work is part of our efforts to build an efficient data analysis system called AQUA. We describe some of the technical problems addressed in this effort.","PeriodicalId":236128,"journal":{"name":"Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1999.754932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 39
Abstract
Summary form only given. The last few years have witnessed a significant increase in the use of databases for complex data analysis (OLAP) applications. These applications often require very quick responses from the DBMS. However, they also involve complex queries on large volumes of data. Despite significant improvement in database support for OLAP over the last few years, most DBMSs still fall short of providing quick enough responses. We present a novel solution to this problem: we use small amounts of precomputed summary statistics of the data to answer the queries quickly, albeit approximately. Our hypothesis is that many OLAP applications can tolerate approximations in query results in return for huge response time reductions. The work is part of our efforts to build an efficient data analysis system called AQUA. We describe some of the technical problems addressed in this effort.