Benchmarking database systems has a long and successful history in making industrial database systems comparable, and is also a cornerstone of quantifiable experimental data systems research. Creating good benchmarks has been described as something of an art [3]. One can inspire dataset and workload design from"representative" use cases queries, typically informed by domain experts; but also exploit technical insights from database architects in what features, operations, and data distributions should come together in order to invoke a particularly challenging task1.

中文翻译：

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技术视角 DIAMetrics

基准数据库系统在使工业数据库系统具有可比性方面有着悠久而成功的历史，也是可量化实验数据系统研究的基石。创建良好的基准已被描述为一种艺术 [3]。可以从“代表性”用例查询中激发数据集和工作负载设计，通常由领域专家提供信息；还可以利用数据库架构师的技术洞察力，了解哪些特性、操作和数据分布应该结合在一起才能调用一个特别具有挑战性的任务1。