半自动索引调优：让DBA保持在循环中
Semi-Automatic Index Tuning: Keeping DBAs in the Loop
摘要：
为了获得良好的系统性能，DBA必须选择一组适合于工作负载的索引。系统可以通过提供索引配置建议来帮助完成这一具有挑战性的任务。我们提出了一个新的索引推荐技术，称为半自动调整，保持DBA“在循环中”，通过生成建议，使用反馈DBA的喜好。该技术还可以在线工作，避免了商业工具的限制，因为商业工具需要提前知道工作量。我们的方法的基础是功函数算法，它可以解决各种各样的在线优化问题，具有很强的竞争力的保证。我们提出了一个实验分析，验证了在各种条件下的半自动调谐的好处。
英文摘要：
To obtain good system performance, a DBA must choose a set of indices that is appropriate for the workload. The system can aid in this challenging task by providing recommendations for the index configuration. We propose a new index recommendation technique, termed semi-automatic tuning, that keeps the DBA "in the loop" by generating recommendations that use feedback about the DBA's preferences. The technique also works online, which avoids the limitations of commercial tools that require the workload to be known in advance. The foundation of our approach is the Work Function Algorithm, which can solve a wide variety of online optimization problems with strong competitive guarantees. We present an experimental analysis that validates the benefits of semi-automatic tuning in a wide variety of conditions.
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