CoPhy：一个可扩展、可移植和交互式的大型工作负载索引顾问
CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads
摘要：
索引调整，即，选择适合于工作负载的索引是数据库系统调优中的关键问题。在本文中，我们解决了实践中常见的大型问题实例的索引调优，例如，工作负载中的数千个查询、数千个候选索引以及若干硬约束和软约束。我们的工作是第一次揭示，索引调整问题有一个结构良好的空间的解决方案，这个空间可以有效地探索与众所周知的技术，从线性优化。实验结果表明，我们的方法优于国家的最先进的商业和研究技术的显着利润率（高达一个数量级）。
英文摘要：
Index tuning, i.e., selecting the indexes appropriate for a workload, is a crucial problem in database system tuning. In this paper, we solve index tuning for large problem instances that are common in practice, e.g., thousands of queries in the workload, thousands of candidate indexes and several hard and soft constraints. Our work is the first to reveal that the index tuning problem has a well structured space of solutions, and this space can be explored efficiently with well known techniques from linear optimization. Experimental results demonstrate that our approach outperforms state-of-the-art commercial and research techniques by a significant margin (up to an order of magnitude).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
