TurboSream: Towards Low-Latency Data Stream Processing

Abstract : Data Stream Processing (DSP) applications are often modelled as a directed acyclic graph: operators with data streams among them. Inter-operator communications can have a significant impact on the latency of DSP applications, accounting for 86% of the total latency. Despite their impact, there has been relatively little work on optimizing inter-operator communications, focusing on reducing inter-node traffic but not considering inter-process communication (IPC) inside a node, which often generates high latency due to the multiple memory-copy operations. This paper describes the design and implementation of TurboStream, a new DSP system designed specifically to address the high latency caused by inter-operator communications. To achieve this goal, we introduce (1) an improved IPC framework with OSRBuffer, a DSP-oriented buffer, to reduce memory-copy operations and waiting time of each single message when transmitting messages between the operators inside one node, and (2) a coarse-grained scheduler that consolidates operator instances and assigns them to nodes to diminish the inter-node IPC traffic. Using a prototype implementation, we show that our improved IPC framework reduces the end-to-end latency of intra-node IPC by 45.64% to 99.30%. Moreover, TurboStream reduces the latency of DSP by 83.23% compared to JStorm.
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Song Wu, Mi Liu, Shadi Ibrahim, Hai Jin, Lin Gu, et al.. TurboSream: Towards Low-Latency Data Stream Processing. ICDCS 2018 - 38th IEEE International Conference on Distributed Computing Systems, Jul 2018, Vienna, Austria. pp.1-11, ⟨10.1109/ICDCS.2018.00099⟩. ⟨hal-01807302⟩

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