Non-Blocking Raft for High Throughput IoT Data

The Raft consensus protocol naturally fits time series databases, owing to the resemblance between its continuous log and the time series data. While the serialization of appending entries reduces the state space for ease design and implementation, it blocks the subsequent requests and thus limits the parallelism and throughput of Raft. Intuitively, once an entry arrives the follower, we may notice the leader and the client to unblock the subsequent as early, rather than waiting for its appending and committing. In this way, more requests can be processed in parallel, and thus the throughput increases, essential for IoT applications often with vast sensors and fast data ingestion. Of course, with higher parallelism, the risk of persistence for in-processing entries increases. It is a worthwhile trade-off in the IoT scenario since tiny data loss during leader failure is more acceptable than shutting out most data due to a low throughput. Our Non-Blocking Raft (NB-Raft) is implemented as the consensus protocol of Apache IoTDB, a commodity time series database management system, supporting various applications in Alibaba Cloud. Extensive evaluation shows that the throughput is improved by about 30% using our NB-Raft compared to the original Raft, a considerable amount of further data saved.