hadoop yarn running beyond physical memory used

老是报物理内存越界,kill container,然后把yarn.scheduler.minimum-allocation-mb设成2048就好了跟这个yarn.nodemanager.pmem-check-enabled参数应该也有关系在这篇文章中得到启发:http://dongxicheng.org/mapreduce-nextgen/hadoop-yarn-memory-cpu-scheduling/ 调度和隔离 Hadoop YARN同时支持内存和CPU两种资源的调度(默认只支持内存…

运行hadoop的时候提示物理内存或虚拟内存溢出的解决方案running beyond physical memory或者beyond vitual memory limits

当运行中出现Container is running beyond physical memory这个问题出现主要是因为物理内存不足导致的,在执行mapreduce的时候,每个map和reduce都有自己分配到内存的最大值,当map函数需要的内存大于这个值就会报这个错误,解决方法: 在mapreduc-site.xml配置里面设置mapreduce的内存分配大小 <property> <name>mapreduce.map.memory.mb</name> <va…

spark运行任务报错：Container [...] is running beyond physical memory limits. Current usage: 3.0 GB of 3 GB physical memory used; 5.0 GB of 6.3 GB virtual memory used. Killing container.

spark版本:1.6.0 scala版本:2.10 报错日志: Application application_1562341921664_2123 failed 2 times due to AM Container for appattempt_1562341921664_2123_000002 exited with exitCode: -104 For more detailed output, check the application tracking page: http://w…

is running beyond physical memory limits. Current usage: 2.0 GB of 2 GB physical memory used; 2.6 GB of 40 GB virtual memory used

昨天使用hadoop跑五一的数据,发现报错: Container [pid=,containerID=container_1453101066555_4130018_01_000067] GB physical memory used; GB virtual memory used. Killing container. 发现是内存溢出了,遇到这种问题首先要判断是map阶段溢出还是reduce阶段溢出,然后分别设置其内存的大小,比如: 在运行hive sql前加上 : (map) 或者 (red…

hadoop is running beyond virtual memory limits问题解决

单机搭建了2.6.5的伪分布式集群,写了一个tf-idf计算程序,分词用的是结巴分词,使用standalone模式运行没有任何问题,切换到伪分布式模式运行一直报错: hadoop is running beyond virtual memory limits 大概意思就是使用虚拟内存超出了限制. 网上参考了好几篇博客,几乎都是再说更改hadoop-env和mapred-site.xml hadoop-env直接更改堆大小 export HADOOP_HEAPSIZE=1000 mapred-si…

【hadoop】 running beyond virtual memory错误原因及解决办法

问题描述: 在hadoop中运行应用,出现了running beyond virtual memory错误.提示如下: Container [pid=28920,containerID=container_1389136889967_0001_01_000121] is running beyond virtual memory limits. Current usage: 1.2 GB of 1 GB physical memory used; 2.2 GB of 2.1 GB virtual…

[hadoop] - Container [xxxx] is running beyond physical/virtual memory limits.

当运行mapreduce的时候,有时候会出现异常信息,提示物理内存或者虚拟内存超出限制,默认情况下:虚拟内存是物理内存的2.1倍.异常信息类似如下: Container [pid=13026,containerID=container_1449820132317_0013_01_000012] is running beyond physical memory limits. Current usage: 1.0 GB of 1 GB physical memory used; 1.7 GB o…

Hadoop YARN中内存的设置

在YARN中,资源管理由ResourceManager和NodeManager共同完成,其中,ResourceManager中的调度器负责资源的分配,而NodeManager则负责资源的供给和隔离.ResourceManager将某个NodeManager上资源分配给任务(这就是所谓的“资源调度”)后,NodeManager需按照要求为任务提供相应的资源,甚至保证这些资源应具有独占性,为任务运行提供基础的保证,这就是所谓的资源隔离. 基于以上考虑,YARN允许用户配置每个节点上可用的物理内存资源…

hive： insert数据时Error during job, obtaining debugging information 以及beyond physical memory limits

insert overwrite table canal_amt1...... 2014-10-09 10:40:27,368 Stage-1 map = 100%, reduce = 32%, Cumulative CPU 2772.48 sec 2014-10-09 10:40:28,426 Stage-1 map = 100%, reduce = 32%, Cumulative CPU 2772.48 sec 2014-10-09 10:40:29,481 Stage-1 map = 10…

hadoop的job执行在yarn中内存分配调节————Container [pid=108284,containerID=container_e19_1533108188813_12125_01_000002] is running beyond virtual memory limits. Current usage: 653.1 MB of 2 GB physical memory used

实际遇到的真实问题,解决方法: 1.调整虚拟内存率yarn.nodemanager.vmem-pmem-ratio (这个hadoop默认是2.1) 2.调整map与reduce的在AM中的大小大于yarn里RM可分配的最小值yarn.scheduler.minimum-allocation-mb 大小因为在Container中计算使用的虚拟内存来自 map虚拟内大小=max(yarn.scheduler.minimum-allocation-mb,mapreduce.map.memory.mb…

Hive-Container killed by YARN for exceeding memory limits. 9.2 GB of 9 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.

Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task times, most recent failure: Lost task , hadoop7, executor ): ExecutorLostFailure (executor exited caused by one of the running tasks) Reason: Container killed by YARN…

Kafka：ZK+Kafka+Spark Streaming集群环境搭建（十三）kafka+spark streaming打包好的程序提交时提示虚拟内存不足（Container is running beyond virtual memory limits. Current usage: 119.5 MB of 1 GB physical memory used; 2.2 GB of 2.1 G）

异常问题:Container is running beyond virtual memory limits. Current usage: 119.5 MB of 1 GB physical memory used; 2.2 GB of 2.1 GB virtual memory used. Killing container. spark-submit提交脚本: [spark@master work]$ more submit.sh #! /bin/bash jars="" for…

Hadoop Yarn配置项 yarn.nodemanager.resource.local-dirs探讨

1. What is the recommended value for "yarn.nodemanager.resource.local-dirs"? We only have one value (directory) configured for the above property, which has a size of 200GB. Our hive jobs' map/reduce fill this folder up, and yarn places this nod…

Container [pid=6263,containerID=container_1494900155967_0001_02_000001] is running beyond virtual memory limits

以Spark-Client模式运行,Spark-Submit时出现了下面的错误: User: hadoop Name: Spark Pi Application Type: SPARK Application Tags: YarnApplicationState: FAILED FinalStatus Reported by AM: FAILED Started: 16-五月-2017 10:03:02 Elapsed: 14sec Tracking URL: History Diagnosti…

troubleshooting-Container 'PHYSICAL' memory limit

原因分析 CDH 集群环境没有对 Container分配足够的运行环境(内存) 解决办法需要修改的配置文件,将具体的配置项修改匹配集群环境资源.如下: 配置文件配置设置解释计算值(参考) yarn-site.xml yarn.nodemanager.resource.memory-mb 分配给容器的物理内存数量 = 52 * 2 =104 G yarn-site.xml yarn.scheduler.minimum-allocation-mb 容器可以请求的最小物理内存量(以 MiB 为…

Hadoop Yarn内存资源隔离实现原理——基于线程监控的内存隔离方案

注:本文以hadoop-2.5.0-cdh5.3.2为例进行说明. Hadoop Yarn的资源隔离是指为运行着不同任务的“Container”提供可独立使用的计算资源,以避免它们之间相互干扰.目前支持两种类型的资源隔离:CPU和内存,对于这两种类型的资源,Yarn使用了不同的资源隔离方案. 对于CPU而言,它是一种“弹性”资源,使用量大小不会直接影响到应用程序的存亡,因此CPU的资源隔离方案采用了Linux Kernel提供的轻量级资源隔离技术Cgroup:对于内存而言,它是一种“限制…

Hadoop Yarn Capacity Scheduler

Capacity 调度器配置 <property> <name>yarn.resourcemanager.scheduler.class<name> <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value> </property> 加载配置文件 $yarn rmadmin -refreshQueue…

Virtualizing physical memory in a virtual machine system

A processor including a virtualization system of the processor with a memory virtualization support system to map a reference to guest-physical memory made by guest software executable on a virtual machine which in turn is executable on a host machin…

Extended paging tables to map guest physical memory addresses from virtual memory page tables to host physical memory addresses in a virtual machine system

Hadoop YARN：调度性能优化实践(转)

https://tech.meituan.com/2019/08/01/hadoop-yarn-scheduling-performance-optimization-practice.html 文章对性能优化的思路,如果评测性能,找到性能瓶颈,优化,优化效果评估,上线部署给出了很好的教科书式的案例,值得一看!! 背景 YARN作为Hadoop的资源管理系统,负责Hadoop集群上计算资源的管理和作业调度. 美团的YARN以社区2.7.1版本为基础构建分支.目前在YARN上支撑离线业务.实时业务…

Hadoop YARN 100-1知识点

0 YARN中实体资源管理者(resource manager, RM) 长时间运行的守护进程,负责管理集群上资源的使用节点管理者(node manager, NM) 长时间运行的守护进程,在集群的所有节点上运行,负责监视容器容器(container) 在受限的资源集合(内存.CPU等)下执行应用相关的进程 1 YARN应用 1.1 运行 (1) 客户端联系RM,请求运行应用master(application master, AM)进程. (2) RM定位可用NM,并在NM上启动容器并在…

Hadoop YARN配置参数剖析—RM与NM相关参数

注意,配置这些参数前,应充分理解这几个参数的含义,以防止误配给集群带来的隐患.另外,这些参数均需要在yarn-site.xml中配置. 1. ResourceManager相关配置参数 (1) yarn.resourcemanager.address 参数解释:ResourceManager 对客户端暴露的地址.客户端通过该地址向RM提交应用程序,杀死应用程序等. 默认值:${yarn.resourcemanager.hostname}:8032 (2) yarn.resourcemana…

hadoop错误org.apache.hadoop.yarn.exceptions.YarnException Unauthorized request to start container

错误: 14/04/29 02:45:07 INFO mapreduce.Job: Job job_1398704073313_0021 failed with state FAILED due to: Application application_1398704073313_0021 failed 2 times due to Error launching appattempt_1398704073313_0021_000002. Got exception: org.apache…

hadoop Yarn 编程API

客户端编程库: 所在jar包: org.apache.hadoop.yarn.client.YarnClient 使用方法: 1 定义一个YarnClient实例: private YarnClient client: 2 构造一个Yarn客户端句柄并初始化 this.client = YarnClient.createYarnClient(); client.ini(conf)3 启动Yarn yarnClient.start()4 获取一个新的application id YarnClien…