Differentiated Performance in NoSQL Database Access for Hybrid Cloud-HPC Workloads

In recent years, the demand for cloud-based high-performance computing applications and services has grown in order to sustain the computational and statistical challenges of big-data analytics scenarios. In this context, there is a growing need for reliable large-scale NoSQL data stores capable of efficiently serving mixed high-performance and interactive cloud workloads. This paper deals with the problem of designing such NoSQL database service: to this purpose, a set of modifications to the popular MongoDB software are presented. The modified MongoDB lets clients submit individual requests or even carry out whole sessions at different priority levels, so that the higher-priority requests are served with shorter response times that exhibit less variance, with respect to lower-priority requests. Experimental results carried out on two big multi-core servers using synthetic workload scenarios demonstrate the effectiveness of the proposed approach in providing differentiated performance levels, highlighting what trade-offs are available between maximum achievable throughput for the platform, and the response-time reduction for higher-priority requests.