UpSizeR: Synthetically scaling an empirical relational database
作者：
Highlights：
• Data generation for benchmarks: replacing domain-specific TPC with application-specific UpSizeR.
• Given an empirical database D and scale factor s, generate a synthetic D′ similar to D but s times its size.
• Experiments with Flickr show results that match crawled data and predict throughput degradation.
• Issue raised: How do social interactions affect attribute correlation in a database?
• Research program proposal: application-specific benchmarking of data-centric systems.
摘要
•Data generation for benchmarks: replacing domain-specific TPC with application-specific UpSizeR.•Given an empirical database D and scale factor s, generate a synthetic D′ similar to D but s times its size.•Experiments with Flickr show results that match crawled data and predict throughput degradation.•Issue raised: How do social interactions affect attribute correlation in a database?•Research program proposal: application-specific benchmarking of data-centric systems.
论文关键词：Application-specific benchmarking,Synthetic data generation,Scale factor,Empirical dataset,Attribute value correlation,Social networks
论文评审过程：Received 5 February 2011, Revised 30 June 2013, Accepted 15 July 2013, Available online 20 July 2013.
论文官网地址：https://doi.org/10.1016/j.is.2013.07.004
