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Received:July 18, 2021 Revised:August 18, 2021
Received:July 18, 2021 Revised:August 18, 2021
中文摘要: 流计算应用中由于上下游数据流入流出速率不匹配常常导致数据缓冲区容量不足或溢出的反压(backpressure)问题, 轻则导致数据丢失、重则导致系统崩溃, 亟需好的解决方法或方案. 不同于向上游传递压力以解决下游反压的已有方法, 本文提出了一种基于数据迁移策略的反压问题解决方法, 通过其他分支的轻载节点分散处理来解决反压问题. 我们构建了基于NS-3的反压问题仿真平台, 实验测试结果表明, 本文方法在完成通量占比和延迟两个指标上均比Flink框架的Credit反压机制有明显改善.
Abstract:In the application of stream computing, the mismatch of upstream and downstream data inflow and outflow speed often leads to the problem of insufficient data buffer capacity or overflow backpressure, and data loss and system crash are the possible consequences. A good solution is in urgent need. The existing methods address the downstream backpressure problem by transferring pressure upstream, but in this paper, a backpressure solution based on data migration strategy is proposed to solve the backpressure problem by dispersing the pressure to light-loaded nodes of other branches. The experiments on the NS-3 network simulation platform show that the proposed method has significantly improved the throughput proportion and latency in contrast to the Credit backpressure mechanism of the Flink framework.
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基金项目:国家自然科学基金面上项目(61672480)
引用文本:
孙一佳,丁箐,徐云.基于数据迁移策略的反压问题解决方法.计算机系统应用,2022,31(5):262-268
Sun Yi-Jia,Ding Qing,Xu Yun.Solution to Backpressure Problem Based on Data Migration Strategy.COMPUTER SYSTEMS APPLICATIONS,2022,31(5):262-268
孙一佳,丁箐,徐云.基于数据迁移策略的反压问题解决方法.计算机系统应用,2022,31(5):262-268
Sun Yi-Jia,Ding Qing,Xu Yun.Solution to Backpressure Problem Based on Data Migration Strategy.COMPUTER SYSTEMS APPLICATIONS,2022,31(5):262-268