Write Skew and Zipf Distribution: Evidence and Implications

Understanding workload characteristics is essential to storage systems design and performance optimization. With the emergence of flash memory as a new viable storage medium, the new design concern of flash endurance arises, necessitating a revisit of workload characteristics, in particular, of the write behavior. Inspired by Web caching studies where a Zipf-like access pattern is commonly found, we hypothesize that write count distribution at the block level may also follow Zipf’s Law. To validate this hypothesis, we study 48 block I/O traces collected from a wide variety of real and benchmark applications. Through extensive analysis, we demonstrate that the Zipf-like pattern indeed widely exists in write traffic provided its disguises are removed by statistical processing. This finding implies that write skew in a large class of applications could be analytically expressed and, thus, facilitates design tradeoff explorations adaptive to workload characteristics.