Elasticutor: Rapid Elasticity for Realtime Stateful Stream Processing

Abstract

Elasticity is highly desirable for stream systems to guarantee low latency against workload dynamics, such as surges in arrival rate and fluctuations in data distribution. Existing systems achieve elasticity using a resource-centric approach that repartitions keys across the parallel instances, i.e., executors, to balance the workload and scale operators. However, such operator-level repartitioning requires global synchronization and prohibits rapid elasticity. We propose an executor-centric approach that avoids operator-level key repartitioning and implements executors as the building blocks of elasticity. By this new approach, we design the Elasticutor framework with two level of optimizations: i) a novel implementation of executors, i.e., elastic executors, that perform elastic multi-core execution via efficient intra-executor load balancing and executor scaling and ii) a global model-based scheduler that dynamically allocates CPU cores to executors based on the instantaneous workloads. We implemented a prototype of Elasticutor and conducted extensive experiments. We show that Elasticutor doubles the throughput and achieves up to two orders of magnitude lower latency than previous methods for dynamic workloads of real-world applications.