Thanks yangyu for launching this discussion. I really like this proposal. We ever found this scene frequently that some long tail tasks to delay the total batch job execution time in production. We also have some thoughts for bringing this mechanism. Looking forward to your detail design doc, then we can discussion further.
Best, Zhijiang ------------------------------------------------------------------ 发件人：Tao Yangyu <ryantao...@gmail.com> 发送时间：2018年11月6日(星期二) 11:01 收件人：dev <dev@flink.apache.org> 主 题：[DISCUSS] Task speculative execution for Flink batch Hi everyone, We propose task speculative execution for Flink batch in this message as follows. In the batch mode, the job is usually divided into multiple parallel tasks executed cross many nodes in the cluster. It is common to encounter the performance degradation on some nodes due to hardware problems or accident I/O busy and high CPU load. This kind of degradation can probably cause the running tasks on the node to be quite slow that is so called long tail tasks. Although the long tail tasks will not fail, they can severely affect the total job running time. Flink task scheduler does not take this long tail problem into account currently. Here we propose the speculative execution strategy to handle the problem. The basic idea is to run a copy of task on another node when the original task is identified to be long tail. In more details, the speculative task will be triggered when the scheduler detects that the data processing throughput of a task is much slower than others. The speculative task is executed in parallel with the original one and share the same failure retry mechanism. Once either task complete, the scheduler admits its output as the final result and cancel the other running one. The preliminary experiments has demonstrated the effectiveness. The detailed design doc will be ready soon. Your reviews and comments will be much appreciated. Thanks! Ryan
