优化器论文列表
发布日期：2024-04-22 14:43浏览次数：
过去一年间，对优化器相关论文做了个系统性的学习，把过程中阅读的论文笔记记录在这里，和大家分享，欢迎大家和我一起讨论，纠错补差，共同进步 ~
阅读路线基本遵照了pingcap github上的一个Awesome Database Learning的资料，这个资料非常棒，包含了一些基本的课程 + 书籍，还按照内核中不同模块的不同方面做了分类，非常系统化，尤其是SQL层面非常详尽，正好符合需求，因此阅读基本也是按其中的paper来，并扩展到一些没有涉及的内容，总体目录如下（优化器部分），由于内容较多，主要挑选其中影响力较大的或者最有参考意义的。
https://zhuanlan.zhihu.com/p/364303913https://zhuanlan.zhihu.com/p/364619893https://zhuanlan.zhihu.com/p/365085770https://zhuanlan.zhihu.com/p/365496273https://zhuanlan.zhihu.com/p/365744405https://zhuanlan.zhihu.com/p/365621518https://zhuanlan.zhihu.com/p/542619719https://zhuanlan.zhihu.com/p/372710924https://zhuanlan.zhihu.com/p/372430733https://zhuanlan.zhihu.com/p/372784778https://zhuanlan.zhihu.com/p/367490874https://zhuanlan.zhihu.com/p/369046631https://zhuanlan.zhihu.com/p/369388811https://zhuanlan.zhihu.com/p/369267836https://zhuanlan.zhihu.com/p/369771981https://zhuanlan.zhihu.com/p/369898082https://zhuanlan.zhihu.com/p/370205445Histogram
- 1984, Accurate Estimation of the Number of Tuples Satisfying a Condition, SIGMOD
- 1993, Optimal Histograms for Limiting Worst-Case Error Propagation in the Size of Join Results, ACM Trans. on Database Systems
- 1993, Universality of Serial Histograms, VLDB
- 1995, Balancing Histogram Optimality and Practicality for Query Result Size Estimation, SIGMOD
- 1996, Improved Histograms for Selectivity Estimation of Range Predicates, SIGMOD
- 1997, SEEKing the truth about ad hoc join costs, VLDB
- 2003, The History of Histograms, VLDB
- 2009, Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors, VLDB
- 2010, Histograms Reloaded: The Merits of Bucket Diversity, SIGMOD
- 2014, Exploiting Ordered Dictionaries to Efficiently Construct Histograms with Q-Error Guarantees in SAP HANA, SIGMOD
- 2015, How Good Are Query Optimizers, Really?, VLDB
Probabilistic Counting
- 2000, Towards Estimation Error Guarantees for Distinct Values, SIGMOD/PODS
- 2001, Distinct Sampling for Highly-Accurate Answers to Distinct Values Queries and Event Reports, VLDB
- 2005, An Improved Data Stream Summary:The Count-Min Sketch and its Applications Journal of Algorithms
- 2007, New Estimation Algorithms for Streaming Data: Count-min Can Do More
- 2013, HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm, ACM
- 2019,Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates, CIDR
https://zhuanlan.zhihu.com/p/483848185Others
- 2002, Exploiting Statistics on Query Expressions for Optimization, ACM
- 2017, Adaptive Statistics in Oracle 12c, VLDB
- 2017, Statisticum: Data Statistics Management in SAP HANA, VLDB
- 2019, Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities, SIGMOD
- 2019, Deep Unsupervised Cardinality Estimation, VLDB
- 2020, NeuroCard: One Cardinality Estimator for All Tables, VLDB
- 2001, LEO – DB2’s LEarning Optimizer, VLDB
- 2004, Robust Query Processing through Progressive Optimization, SIGMOD
- 2004, Automated Statistics Collection in DB2 UDB, VLDB
- 2008, Optimizer plan change management: improved stability and performance in Oracle 11g, VLDB
- 2015, Adaptive Query Processing in the Looking Glass, CIDR
https://zhuanlan.zhihu.com/p/375852049https://zhuanlan.zhihu.com/p/366434087https://zhuanlan.zhihu.com/p/366735936https://zhuanlan.zhihu.com/p/367068030https://zhuanlan.zhihu.com/p/369455226https://zhuanlan.zhihu.com/p/369619142
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