Oracle中的自动SQL错误缓解

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the Vldb Endowment Pub Date : 2023-08-01 DOI:10.14778/3611540.3611568
Krishna Kantikiran Pasupuleti, Jiakun Li, Hong Su, Mohamed Ziauddin
{"title":"Oracle中的自动SQL错误缓解","authors":"Krishna Kantikiran Pasupuleti, Jiakun Li, Hong Su, Mohamed Ziauddin","doi":"10.14778/3611540.3611568","DOIUrl":null,"url":null,"abstract":"Despite best coding practices, software bugs are inevitable in a large codebase. In traditional databases, when errors occur during query processing, they disrupt user workflow until workarounds are found and applied. Manual identification of workarounds often relies on a trial-and-error method. The process is not only time-consuming but also requires domain expertise that users are often lacking. In this paper, we propose a framework to automatically mitigate errors that occur during query compilation (including optimization and code generation) without any user intervention. An error is intercepted by the database internally, a workaround is identified for it, and the query is recompiled using the workaround. The entire process remains transparent to the user with the query being executed seamlessly. The proposed technique handles SQL errors during query compilation and provides three types of mitigation strategies - i) quickly failover to one of the readily-available historical plans for the statement ii) apply targeted error-correcting directives (hints) identified from the optimizer context at the time of the error iii) modify the global configuration of the optimizer using hints. This feature has been implemented and will be released in an upcoming version of Oracle Autonomous Database.","PeriodicalId":54220,"journal":{"name":"Proceedings of the Vldb Endowment","volume":"18 1","pages":"0"},"PeriodicalIF":2.6000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic SQL Error Mitigation in Oracle\",\"authors\":\"Krishna Kantikiran Pasupuleti, Jiakun Li, Hong Su, Mohamed Ziauddin\",\"doi\":\"10.14778/3611540.3611568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite best coding practices, software bugs are inevitable in a large codebase. In traditional databases, when errors occur during query processing, they disrupt user workflow until workarounds are found and applied. Manual identification of workarounds often relies on a trial-and-error method. The process is not only time-consuming but also requires domain expertise that users are often lacking. In this paper, we propose a framework to automatically mitigate errors that occur during query compilation (including optimization and code generation) without any user intervention. An error is intercepted by the database internally, a workaround is identified for it, and the query is recompiled using the workaround. The entire process remains transparent to the user with the query being executed seamlessly. The proposed technique handles SQL errors during query compilation and provides three types of mitigation strategies - i) quickly failover to one of the readily-available historical plans for the statement ii) apply targeted error-correcting directives (hints) identified from the optimizer context at the time of the error iii) modify the global configuration of the optimizer using hints. This feature has been implemented and will be released in an upcoming version of Oracle Autonomous Database.\",\"PeriodicalId\":54220,\"journal\":{\"name\":\"Proceedings of the Vldb Endowment\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Vldb Endowment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14778/3611540.3611568\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Vldb Endowment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14778/3611540.3611568","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

尽管有最佳的编码实践,但在大型代码库中,软件bug是不可避免的。在传统数据库中,当查询处理过程中出现错误时,它们会中断用户的工作流程,直到找到并应用解决方案。手动识别变通方法通常依赖于试错法。这个过程不仅耗时,而且需要用户通常缺乏的领域专业知识。在本文中,我们提出了一个框架来自动减轻查询编译(包括优化和代码生成)过程中发生的错误,而无需任何用户干预。数据库在内部拦截错误,为其识别一个解决方案,并使用该解决方案重新编译查询。整个过程对用户保持透明,查询被无缝地执行。所提议的技术处理查询编译期间的SQL错误,并提供三种类型的缓解策略——i)快速故障转移到语句的一个现成的历史计划;ii)应用在错误发生时从优化器上下文中确定的有针对性的错误纠正指令(提示);iii)使用提示修改优化器的全局配置。这个特性已经实现,并将在Oracle自治数据库的下一个版本中发布。
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
Automatic SQL Error Mitigation in Oracle
Despite best coding practices, software bugs are inevitable in a large codebase. In traditional databases, when errors occur during query processing, they disrupt user workflow until workarounds are found and applied. Manual identification of workarounds often relies on a trial-and-error method. The process is not only time-consuming but also requires domain expertise that users are often lacking. In this paper, we propose a framework to automatically mitigate errors that occur during query compilation (including optimization and code generation) without any user intervention. An error is intercepted by the database internally, a workaround is identified for it, and the query is recompiled using the workaround. The entire process remains transparent to the user with the query being executed seamlessly. The proposed technique handles SQL errors during query compilation and provides three types of mitigation strategies - i) quickly failover to one of the readily-available historical plans for the statement ii) apply targeted error-correcting directives (hints) identified from the optimizer context at the time of the error iii) modify the global configuration of the optimizer using hints. This feature has been implemented and will be released in an upcoming version of Oracle Autonomous Database.
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
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
期刊最新文献
Auditory Brainstem Response in a Child with Mitochondrial Disorder-Leigh Syndrome. Breathing New Life into an Old Tree: Resolving Logging Dilemma of B + -tree on Modern Computational Storage Drives QO-Insight: Inspecting Steered Query Optimizers A Learned Query Rewrite System Demonstrating ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Joins via Reinforcement Learning
×
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