计算机科学
查询优化
查询扩展
Web搜索查询
情报检索
萨尔盖博
Web查询分类
查询语言
在线聚合
数据挖掘
搜索引擎
作者
Christoph Anneser,Mario Petruccelli,Nesime Tatbul,David Cohen,Zhenggang Xu,P. Pandian P. Pandian,Nikolay Laptev,Ryan Marcus,Alfons Kemper
标识
DOI:10.14778/3611540.3611586
摘要
Steered query optimizers address the planning mistakes of traditional query optimizers by providing them with hints on a per-query basis, thereby guiding them in the right direction. This paper introduces QO-Insight, a visual tool designed for exploring query execution traces of such steered query optimizers. Although steered query optimizers are typically perceived as black boxes, QO-Insight empowers database administrators and experts to gain qualitative insights and enhance their performance through visual inspection and analysis.
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