CAJ | 학술논문

针对目前 Hadoop 作业调度方法服务水平不高、资源利用率低的问题，提出了一种改进的 Hadoop 多用户作业调度算法。分析了 Hadoop 现行调度算法存在的不足，提出了基于服务质量（QoS）的作业选择量化和基于遗传算法的任务选择均衡化的方法，最后采用 Hadoop 平台对算法进行了仿真。仿真结果表明，该资源调度方法提高了作业的服务质量，实现了资源的合理调度。
침대목전 Hadoop 작업조도방법복무수평불고、자원이용솔저적문제，제출료일충개진적 Hadoop 다용호작업조도산법。분석료 Hadoop 현행조도산법존재적불족，제출료기우복무질량（QoS）적작업선택양화화기우유전산법적임무선택균형화적방법，최후채용 Hadoop 평태대산법진행료방진。방진결과표명，해자원조도방법제고료작업적복무질량，실현료자원적합리조도。
Aiming at the job scheduling method of Hadoop operation service level is not high,and the low utilization rate of resources problem,this paper proposed an improved Hadoop multiuser scheduling algorithm.Firstly,it analyzed the shortcom-ings existed in Hadoop scheduling algorithm.Then put forward a job selection method based on the quality of service,and a task selection equalization method based on genetic algorithm.Finally,it simulated the algorithm by using the Hadoop plat-form.The simulation results show that,the resource scheduling method improves the operation quality of service,to achieve a reasonable scheduling of resources.