Dependency Preserved Raft for Transactions

Modern databases are commonly deployed on multiple commercial machines with quorum-based replication to provide high availability and guarantee strong consistency. A widely adopted consensus protocol is Raft because it is easy to understand and implement. However, Raft’s strict serialization limits the concurrency of the system, making it unable to reflect the capability of high concurrent transaction processing brought by new hardware and concurrency control technologies. Upon realizing this, the work targets on improving the parallelism of replication. We propose a variant of Raft protocol named DP-Raft to support parallel replication of database logs so that it can match the speed of transaction execution. Our key contributions are: (1) we define the rules for using log dependencies to commit and apply logs out of order; (2) DP-Raft is proposed for replicating logs in parallel. DP-Raft preserves log dependencies to ensure the safety of parallel replication and with some data structures to reduce the cost of state maintenance; (3) experiments on YCSB benchmark show that our method can improve throughput and reduce latency of transaction processing in database systems than existing Raft-based solutions.