Prairie:用于查询优化器的规则规范框架

Dinesh Das, D. Batory
{"title":"Prairie:用于查询优化器的规则规范框架","authors":"Dinesh Das, D. Batory","doi":"10.1109/ICDE.1995.380391","DOIUrl":null,"url":null,"abstract":"From our experience, current rule-based query optimizers do not provide a very intuitive and well-defined framework to define rules and actions. To remedy this situation, we propose an extensible and structured algebraic framework called Prairie for specifying rules. Prairie facilitates rule-writing by enabling a user to write rules and actions more quickly, correctly and in an easy-to-understand and easy-to-debug manner. Query optimizers consist of three major parts: a search space, a cost model and a search strategy. The approach we take is only to develop the algebra which defines the search space and the cost model and use the Volcano optimizer-generator as our search engine. Using Prairie as a front-end we translate Prairie rules to Volcano to validate our claim that Prairie makes it easier to write rules. We describe our algebra and present experimental results which show that using a high-level framework like Prairie to design large-scale optimizers does not sacrifice efficiency.<<ETX>>","PeriodicalId":184415,"journal":{"name":"Proceedings of the Eleventh International Conference on Data Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Prairie: A rule specification framework for query optimizers\",\"authors\":\"Dinesh Das, D. Batory\",\"doi\":\"10.1109/ICDE.1995.380391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"From our experience, current rule-based query optimizers do not provide a very intuitive and well-defined framework to define rules and actions. To remedy this situation, we propose an extensible and structured algebraic framework called Prairie for specifying rules. Prairie facilitates rule-writing by enabling a user to write rules and actions more quickly, correctly and in an easy-to-understand and easy-to-debug manner. Query optimizers consist of three major parts: a search space, a cost model and a search strategy. The approach we take is only to develop the algebra which defines the search space and the cost model and use the Volcano optimizer-generator as our search engine. Using Prairie as a front-end we translate Prairie rules to Volcano to validate our claim that Prairie makes it easier to write rules. We describe our algebra and present experimental results which show that using a high-level framework like Prairie to design large-scale optimizers does not sacrifice efficiency.<<ETX>>\",\"PeriodicalId\":184415,\"journal\":{\"name\":\"Proceedings of the Eleventh International Conference on Data Engineering\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eleventh International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1995.380391\",\"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 Eleventh International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1995.380391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

摘要

根据我们的经验,当前基于规则的查询优化器没有提供非常直观和定义良好的框架来定义规则和操作。为了纠正这种情况,我们提出了一个可扩展的结构化代数框架,称为Prairie,用于指定规则。Prairie通过使用户能够以易于理解和易于调试的方式更快、更正确地编写规则和操作,从而简化了规则编写。查询优化器由三个主要部分组成:搜索空间、成本模型和搜索策略。我们采用的方法只是开发定义搜索空间和成本模型的代数,并使用Volcano优化生成器作为我们的搜索引擎。使用Prairie作为前端,我们将Prairie规则转换为Volcano,以验证我们的说法,即Prairie使编写规则更容易。我们描述了我们的代数并给出了实验结果,这些结果表明使用像Prairie这样的高级框架来设计大规模优化器并不会牺牲效率
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Prairie: A rule specification framework for query optimizers
From our experience, current rule-based query optimizers do not provide a very intuitive and well-defined framework to define rules and actions. To remedy this situation, we propose an extensible and structured algebraic framework called Prairie for specifying rules. Prairie facilitates rule-writing by enabling a user to write rules and actions more quickly, correctly and in an easy-to-understand and easy-to-debug manner. Query optimizers consist of three major parts: a search space, a cost model and a search strategy. The approach we take is only to develop the algebra which defines the search space and the cost model and use the Volcano optimizer-generator as our search engine. Using Prairie as a front-end we translate Prairie rules to Volcano to validate our claim that Prairie makes it easier to write rules. We describe our algebra and present experimental results which show that using a high-level framework like Prairie to design large-scale optimizers does not sacrifice efficiency.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Translation of object-oriented queries to relational queries A transaction transformation approach to active rule processing Design, implementation and evaluation of SCORE (a system for content based retrieval of pictures) A structure based schema integration methodology An evaluation of sampling-based size estimation methods for selections in database systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1