Request-aware cooperative I/O scheduling for scale-out database applications

Interactive data center applications suffer from the tail latency problem. Since most modern data center applications take the sharded architecture to serve scale-out services, a request comprises multiple sub-requests handled in individual back-end nodes. Depending on the state of each back-end node, a node may issue multiple I/Os for a single sub-request. Since traditional I/O scheduling operates in an application-agnostic manner, it sometimes causes a long latency gap between the responses of sub-requests, thereby delaying the response to end-users. In this paper, we propose a request-aware cooperative I/O scheduling scheme to reduce the tail latency of a database application. Our proposed scheme captures request arrival order at the front-end of an application and exploits it to make a decision for I/O scheduling in individual back-end nodes. We implemented a prototype based on MongoDB and the Linux kernel and evaluated it with a read-intensive scan workload. Experimental results show that our proposed scheme effectively reduces the latency gap between sub-requests, thereby reducing the tail latency.