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首页> 外文会议>2018 IEEE Intl Conf on Parallel amp; Distributed Processing with Applications, Ubiquitous Computing amp; Communications, Big Data amp; Cloud Computing, Social Computing amp; Networking, Sustainable Computing amp; Communications >Proportion Scheduler to Improve the Mismatched Locality in YARN
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Proportion Scheduler to Improve the Mismatched Locality in YARN

机译：比例调度程序可改善YARN中的位置不匹配

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摘要

YARN is a prevailing central resource management architecture, which allocates a group of resources to each application. The resource group is consistent with locality requests of tasks in applications. But each application allocates the resources in the resource group to each task according to locality capacities of resources. Different rules in two levels of resource allocations lead to mismatched localities for tasks, which hurts performances of applications. There is a lack of researches about mismatched localities for tasks in YARN. This paper designs a Proportion scheduler to improve mismatched localities without dragging applications. The locality capacities of resources becomes unified allocation rule. Resources are classified by the locality requests of tasks, so that resources in the same category are versatile for tasks with the same level of locality request. This classification decreases the mismatched probability. In addition, the improvement of mismatched localities makes compromises between different applications. Every application is assigned with proportional resources in different locality scales for improved performances. Compared to baseline schedulers, there are 2 times data-local tasks and more than 30% rack-local tasks. The Proportion decreases makespan of applications by a maximum 66.7% and network traffic by an utmost 80%.
机译：YARN是一种流行的中央资源管理体系结构，它为每个应用程序分配一组资源。资源组与应用程序中任务的位置要求一致。但是每个应用程序都会根据资源的本地容量将资源组中的资源分配给每个任务。两级资源分配中的不同规则导致任务的位置不匹配，从而损害了应用程序的性能。缺乏关于YARN中任务的不匹配地点的研究。本文设计了一个比例调度程序，以改进不匹配的位置，而不会拖累应用程序。资源的局部容量成为统一的分配规则。资源按任务的位置请求分类，因此，同一类别的资源可用于具有相同位置请求级别的任务。这种分类降低了不匹配的可能性。另外，不匹配位置的改善使不同应用程序之间折衷。每个应用程序都分配有不同位置比例的比例资源，以提高性能。与基准计划程序相比，数据本地任务的数量是其两倍，而机架本地任务的数量则超过30％。该比例最多可将应用程序的生成时间减少66.7％，而网络流量最多减少80％。

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