DPconv:超快连接排序

Mihail Stoian, Andreas Kipf
{"title":"DPconv:超快连接排序","authors":"Mihail Stoian, Andreas Kipf","doi":"arxiv-2409.08013","DOIUrl":null,"url":null,"abstract":"We revisit the join ordering problem in query optimization. The standard\nexact algorithm, DPccp, has a worst-case running time of $O(3^n)$. This is\nprohibitively expensive for large queries, which are not that uncommon anymore.\nWe develop a new algorithmic framework based on subset convolution. DPconv\nachieves a super-polynomial speedup over DPccp, breaking the $O(3^n)$\ntime-barrier for the first time. We show that the instantiation of our\nframework for the $C_\\max$ cost function is up to 30x faster than DPccp for\nlarge clique queries.","PeriodicalId":501123,"journal":{"name":"arXiv - CS - Databases","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DPconv: Super-Polynomially Faster Join Ordering\",\"authors\":\"Mihail Stoian, Andreas Kipf\",\"doi\":\"arxiv-2409.08013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We revisit the join ordering problem in query optimization. The standard\\nexact algorithm, DPccp, has a worst-case running time of $O(3^n)$. This is\\nprohibitively expensive for large queries, which are not that uncommon anymore.\\nWe develop a new algorithmic framework based on subset convolution. DPconv\\nachieves a super-polynomial speedup over DPccp, breaking the $O(3^n)$\\ntime-barrier for the first time. We show that the instantiation of our\\nframework for the $C_\\\\max$ cost function is up to 30x faster than DPccp for\\nlarge clique queries.\",\"PeriodicalId\":501123,\"journal\":{\"name\":\"arXiv - CS - Databases\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Databases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Databases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

我们重温了查询优化中的连接排序问题。标准精确算法 DPccp 的最坏运行时间为 $O(3^n)$。这对于大型查询来说昂贵得令人望而却步,而大型查询已不再罕见。我们开发了一种基于子集卷积的新算法框架。我们开发了基于子集卷积的新算法框架。与 DPccp 相比,DPconv 实现了超多项式提速,首次突破了 $O(3^n)$ 时间障碍。我们展示了我们的框架在$C_\max$成本函数上的实例化,在大型clique查询上比DPccp快了30倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DPconv: Super-Polynomially Faster Join Ordering
We revisit the join ordering problem in query optimization. The standard exact algorithm, DPccp, has a worst-case running time of $O(3^n)$. This is prohibitively expensive for large queries, which are not that uncommon anymore. We develop a new algorithmic framework based on subset convolution. DPconv achieves a super-polynomial speedup over DPccp, breaking the $O(3^n)$ time-barrier for the first time. We show that the instantiation of our framework for the $C_\max$ cost function is up to 30x faster than DPccp for large clique queries.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信