精品文档---下载后可任意编辑Hadoop 平台的作业调度算法讨论与改进的开题报告【摘要】Hadoop 平台的作业调度算法是 Hadoop 生态系统中的一个重要讨论领域。本文通过对 Hadoop 平台和其作业调度算法的讨论，分析了当前主流的 Hadoop 作业调度算法的优缺点，并针对其中的不足之处，提出了一种新的作业调度算法。首先，本文分析了 Hadoop 平台的概念，架构和主要组件。然后，对 Hadoop 平台的作业调度算法进行了综述和分类，包括传统的FIFO、Fair 和 Capacity 算法以及最新的基于资源感知的 YARN-Federation 和 ML-based 算法。在此基础上，本文提出了一种基于任务优先级和资源负载的作业调度算法。该算法通过分析每个任务的优先级和资源需求，选择最优的节点进行调度，以优化整个集群的资源利用效率和作业执行效率。最后，本文结合实际案例，使用 Hadoop 平台上的实验数据进行了验证，分析了该算法的性能和效果。结果表明，该算法可以更好地满足不同类型任务的需求，提高了 Hadoop 平台集群的资源利用效率和作业执行效率。【关键词】Hadoop 平台; 作业调度算法; 任务优先级; 资源负载; 集群资源利用效率【Abstract】The job scheduling algorithm on Hadoop platform is a significant research field in the Hadoop ecosystem. This paper analyzes the advantages and disadvantages of the current mainstream Hadoop job scheduling algorithms by studying the Hadoop platform and its scheduling algorithms and proposes a new job scheduling algorithm to overcome the shortcomings of these algorithms.Firstly, this paper describes the concept, architecture and main components of Hadoop platform. Then, it reviews and classifies the existing job scheduling algorithms on Hadoop platform, including the traditional FIFO, Fair and Capacity algorithms and the latest YARN-Federation and ML-based algorithms.On this basis, this paper proposes a new job scheduling algorithm based on task priority and resource load. By 精品文档---下载后可任意编辑analyzing the priority and resource requirements of each task, the algorithm selects the optimal node for scheduling to optimize the resource utilization and job execution efficiency of the whole cluster.Finally, using experimental data on the Hadoop platform, this paper verifies the performance and effectiveness of the proposed algorithm. The results show that the proposed algorithm can better meet the needs of different types of tasks and improve the resource utilization and job execution efficiency of the Hadoop cluster.【Keywords】Hadoop platform; job scheduling algorithm; task priority; resource load; resource utilization efficiency of cluster
