{"title":"使用非等价用户定义的聚合函数共享查询","authors":"Chao Zhang, Farouk Toumani","doi":"10.1145/3649133","DOIUrl":null,"url":null,"abstract":"<p>This paper presents <sans-serif>SUDAF</sans-serif>, a declarative framework that allows users to write UDAF (User-Defined Aggregate Function) as mathematical expressions and use them in SQL statements. <sans-serif>SUDAF</sans-serif> rewrites partial aggregates of UDAFs using built-in aggregate functions and supports efficient dynamic caching and reusing of partial aggregates. Our experiments show that rewriting UDAFs using built-in functions can significantly speed up queries with UDAFs, and the proposed sharing approach can yield up to two orders of magnitude improvement in query execution time. The paper studies also an extension of <sans-serif>SUDAF</sans-serif> to support sharing partial results between arbitrary queries with UDAFs. We show a connection with the problem of query rewriting using views and introduce a new class of rewritings, called <sans-serif>SUDAF</sans-serif> rewritings, which enables to use views that have aggregate functions different from the ones used in the input query. We investigate the underlying rewriting-checking and rewriting-existing problem. Our main technical result is a reduction of these problems to respectively rewriting-checking and rewriting-existing of the so-called <i>aggregate candidates</i>, a class of rewritings that has been deeply investigated in the literature.</p>","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"170 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sharing Queries with Nonequivalent User-Defined Aggregate Functions\",\"authors\":\"Chao Zhang, Farouk Toumani\",\"doi\":\"10.1145/3649133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper presents <sans-serif>SUDAF</sans-serif>, a declarative framework that allows users to write UDAF (User-Defined Aggregate Function) as mathematical expressions and use them in SQL statements. <sans-serif>SUDAF</sans-serif> rewrites partial aggregates of UDAFs using built-in aggregate functions and supports efficient dynamic caching and reusing of partial aggregates. Our experiments show that rewriting UDAFs using built-in functions can significantly speed up queries with UDAFs, and the proposed sharing approach can yield up to two orders of magnitude improvement in query execution time. The paper studies also an extension of <sans-serif>SUDAF</sans-serif> to support sharing partial results between arbitrary queries with UDAFs. We show a connection with the problem of query rewriting using views and introduce a new class of rewritings, called <sans-serif>SUDAF</sans-serif> rewritings, which enables to use views that have aggregate functions different from the ones used in the input query. We investigate the underlying rewriting-checking and rewriting-existing problem. Our main technical result is a reduction of these problems to respectively rewriting-checking and rewriting-existing of the so-called <i>aggregate candidates</i>, a class of rewritings that has been deeply investigated in the literature.</p>\",\"PeriodicalId\":50915,\"journal\":{\"name\":\"ACM Transactions on Database Systems\",\"volume\":\"170 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Database Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3649133\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Database Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3649133","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Sharing Queries with Nonequivalent User-Defined Aggregate Functions
This paper presents SUDAF, a declarative framework that allows users to write UDAF (User-Defined Aggregate Function) as mathematical expressions and use them in SQL statements. SUDAF rewrites partial aggregates of UDAFs using built-in aggregate functions and supports efficient dynamic caching and reusing of partial aggregates. Our experiments show that rewriting UDAFs using built-in functions can significantly speed up queries with UDAFs, and the proposed sharing approach can yield up to two orders of magnitude improvement in query execution time. The paper studies also an extension of SUDAF to support sharing partial results between arbitrary queries with UDAFs. We show a connection with the problem of query rewriting using views and introduce a new class of rewritings, called SUDAF rewritings, which enables to use views that have aggregate functions different from the ones used in the input query. We investigate the underlying rewriting-checking and rewriting-existing problem. Our main technical result is a reduction of these problems to respectively rewriting-checking and rewriting-existing of the so-called aggregate candidates, a class of rewritings that has been deeply investigated in the literature.
期刊介绍:
Heavily used in both academic and corporate R&D settings, ACM Transactions on Database Systems (TODS) is a key publication for computer scientists working in data abstraction, data modeling, and designing data management systems. Topics include storage and retrieval, transaction management, distributed and federated databases, semantics of data, intelligent databases, and operations and algorithms relating to these areas. In this rapidly changing field, TODS provides insights into the thoughts of the best minds in database R&D.