YARN

本文介绍了Hadoop 0.23版本引入的新架构YARN(MapReduce NextGen),它将资源管理和作业生命周期管理分离,分别由ResourceManager和ApplicationMaster负责。ResourceManager进行全局资源分配,而ApplicationMaster负责任务调度和协调。此外,还详细讲解了YARN的各种组件及其功能。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

MapReduce NextGen aka YARN aka MRv2

The new architecture introduced in hadoop-0.23, divides the two major functions of the JobTracker: resource management and job life-cycle management into separate components.

The new ResourceManager manages the global assignment of compute resources to applications and the per-application ApplicationMaster manages the application’s scheduling and coordination.

An application is either a single job in the sense of classic MapReduce jobs or a DAG of such jobs.

The ResourceManager and per-machine NodeManager daemon, which manages the user processes on that machine, form the computation fabric.

The per-application ApplicationMaster is, in effect, a framework specific library and is tasked with negotiating resources from the ResourceManager and working with the NodeManager(s) to execute and monitor the tasks.

More details are available in the Architecture document.

Documentation Index

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值