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A Hadoop Job Scheduling Model Based on Uncategorized Slot

机译:基于未分类时隙的Hadoop作业调度模型

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摘要

As Job scheduling is becoming an important part of Hadoop framework at present, a job scheduling model based on uncategorized slot was researched on this paper. It could eliminate the limitation of Job Task type and didn't distinguish between Map slot and Reduce slot any more, however there was only one type of slot left which could be assigned to execute the Map tasks and to run the Reduce tasks. By adopting Reduce dynamic partitioning, it can realize switching smoothly the slot between two types of tasks, meanwhile, compared with the FIFO algorithm which need distinguish the type of slot, the experimental result shows that the model not only improves the resources utilization and betters load balancing, but also enhances the parallelism of tasks and shortens the execution time of the Job Tasks.
机译:随着作业调度成为当前Hadoop框架的重要组成部分,本文研究了一种基于未分类时隙的作业调度模型。它可以消除作业任务类型的限制,并且不再区分Map插槽和Reduce插槽,但是只剩下一种类型的插槽可以分配给执行Map任务和运行Reduce任务。通过采用Reduce动态分区,可以实现两种任务之间的平滑切换,同时,与需要区分时隙类型的FIFO算法相比,实验结果表明该模型不仅提高了资源利用率,而且提高了负载。平衡,还可以增强任务的并行性,并缩短作业任务的执行时间。

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