Big data has emerged as a strategic property of nations and organizations. There are driving needs to generate values from big data. However, the sheer volume of big data requires significant storage capacity, transmission bandwidth, computations, and power consumption. It is expected that systems with unprecedented scales can resolve the problems caused by varieties of big data with daunting volumes. Nevertheless, without big data benchmarks, it is very difficult for big data owners to make choice on which system is best for meeting with their specific requirements. They also face challenges on how to optimize the systems and their solutions for specific or even comprehensive workloads. Meanwhile, researchers are also working on innovative data management systems, hardware architectures, operating systems, and programming systems to improve performance in dealing with big data. This workshop, the seventh its series, focuses on architecture and system support for big data systems, aiming at bringing researchers and practitioners from data management, architecture, and systems research communities together to discuss the research issues at the intersection of these areas.