Abstract: Aiming at the big data workloads with off-line analysis and interactive queries,first we analyzed some common features of these workloads,extracted the common set of operations and arranged the workloads in groups.Then,we tested the big data workloads on the BigDataBench platform and got the micro-architecture characteristics using PCA and SimpleKMeans algorithm for dimensionality reduction and clustering analysis.Our study revealed that big data workloads share a common set of operations such as the Join and Cross Production.We also observed that some of the big data workloads have many similar features.For example,the Difference and Projection operations share micro-architectural characteristics.The result of our experiment has a guiding significance for the design of hardware platforms like processors and the optimization of applications.Meanwhile,it also provides valuable insights into the implementation of the big data benchmark platform.

Key words: Big data,Big data workloads,Architecture characteristic