最近一直在折腾使用docker一键部署全分布式hadoop集群,虽然一键部署的脚本写好了并且可以成功运行出各个节点，但在运行一个wordcount实例时出现了错误，错误如下：
java.io.IOException: org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid resource request, requested memory < 0, or requested memory > max configured, requestedMemory=1536, maxMemory=1024
at
org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.validateResourceRequest(SchedulerUtils.java:272)
at
org.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndValidateRequest(SchedulerUtils.java:228)
atorg.apache.hadoop.yarn.server.resourcemanager.scheduler.SchedulerUtils.normalizeAndValidateRequest(SchedulerUtils.java:236)
at org.apache.hadoop.yarn.server.resourcemanager.RMAppManager.validateAndCreateResourceRequest(RMAppManager.java:385)
at org.apache.hadoop.yarn.server.resourcemanager.RMAppManager.createAndPopulateNewRMApp(RMAppManager.java:330)
at org.apache.hadoop.yarn.server.resourcemanager.RMAppManager.submitApplication(RMAppManager.java:282)
at org.apache.hadoop.yarn.server.resourcemanager.ClientRMService.submitApplication(ClientRMService.java:580)
at org.apache.hadoop.yarn.api.impl.pb.service.ApplicationClientProtocolPBServiceImpl.submitApplication(ApplicationClientProtocolPBServiceImpl.java:218)
at org.apache.hadoop.yarn.proto.ApplicationClientProtocol$ApplicationClientProtocolService$2.callBlockingMethod(ApplicationClientProtocol.java:419)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:982)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2217)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2213)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1746)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2213)
at org.apache.hadoop.mapred.YARNRunner.submitJob(YARNRunner.java:316)
at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:240)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1290)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1287)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1746)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287)
at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1308)
at org.apache.hadoop.examples.WordCount.main(WordCount.java:87)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:71)
at org.apache.hadoop.util.ProgramDriver.run(ProgramDriver.java:144)
at org.apache.hadoop.examples.ExampleDriver.main(ExampleDriver.java:74)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
问题：请求内存是1536M，而最大内存只有1024M，这个最大内存指的是运行MapReduce程序使用的最大内存，NodeManager运行MapReduce程序默认最大内存只有1024M，因此出现了错误。
解决办法（这两步所有节点都需要修改）：第一步，修改yarn的配置文件yarn-site.xml，改动两个地方：
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>2000</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>2000</value>
</property>
第二步，由于NodeManager运行MapReduce程序使用的内存是由其上的docker容器分配的，而docker容器是在虚拟机上创建的，那么你在创建虚拟机时，就需要分配较大的内存才行，因为在虚拟机上创建的所有docker容器都会共用虚拟机的内存，如果虚拟机设置的内存过小，比如1G，那么创建的docker容器最大也只有1G内存，运行MapReduce程序肯定会报错，因此在创建虚拟机时尽可能分配较大的内存，我这里给虚拟机分配了4G。而在创建docker容器时需要使用docker命令对容器使用的资源进行限制，我在利用docker搭建hadoop集群时，分别创建了1个Master和3个Slave，命令如下：
docker run -dit --name hadoop-master -m 2G --net shadownet --ip 172.18.0.10 -h hadoop-master -P -p 50070:50070 -p 8088:8088 lijinze9456yy000/ubuntu14-hadoop:base
docker run -dit --name hadoop-slave1 -m 2G --net shadownet --ip 172.18.0.11 -h hadoop-slave1 lijinze9456yy000/ubuntu14-hadoop:base
docker run -dit --name hadoop-slave2 -m 2G --net shadownet --ip 172.18.0.12 -h hadoop-slave2 lijinze9456yy000/ubuntu14-hadoop:base
docker run -dit --name hadoop-slave3 -m 2G --net shadownet --ip 172.18.0.13 -h hadoop-slave3 lijinze9456yy000/ubuntu14-hadoop:base
我这里设置的4个docker容器内存均为2G，swap分区大小默认与内存相同，因此也为2G。
经过这两个步骤以后，我的wordcount实例完美的运行了！
