centos 7搭建hadoop环境及踩到的坑

一、修改主机名称

1.vi /etc/hostname

这个文件的内容便是主机名称，将其内容修改为你需要的主机名称

2.vi /etc/hosts

用于网络DNS解析，将127.0.0.1和::1对应的行修改为你需要的主机名称

3.hostnamectl

查看static hostname值是否为你需要的主机名称

二、静态IP解析

若域内没有DNS服务器，那么需要对每个主机设置静态IP解析，只需要修改/etc/hosts内容即可，在/etc/hosts添加IP映射，每一行为一个记录（IP地址+空格+主机名）

三、进行Linux无密码登录设置

($HOMEDIR)表示家目录，例如，/root ，/home/hadoop

hostnameA表示A的主机名称

username表示登录主机用的用户名

1.在每个计算机上生成公钥和私钥，命令为ssh-keygen -t rsa，需要提前安装了ssh

2.使用ssh_COPY_ID -i ($HOMEDIR)/.ssh/id_rsa.pub (username)@(hostnameA)将公钥集中到某个主机上

3.在hostnameA上使用命令 ssh-copy-id -i ($HOMEDIR)/.ssh/id_rsa.pub root@localhost

4.将hostnameA上的($HOMEDIR)/.ssh/authorized_keys复制至其他主机上scp ($HOMEDIR)/.ssh/authorized_keys(username)@(hostnameB):/root/.ssh/

5.使用ssh命令测试连接是否正常

四、首先需要理解hadoop的基本架构，下面两幅图分别为HDFS和YARN的基本结构图

五、进行hadoop配置

配置文件位于hadoop解压后的目录下的etc/hadoop目录，我的集群中包含了bigdata-senior01.chybinmy.com，bigdata-senior02.chybinmy.com，bigdata-senior03.chybinmy.com，bigdata-senior04.chybinmy.com四台机器，将bigdata-senior01.chybinmy.com设置为namenode，其余为datanode，将bigdata-senior02.chybinmy.com设置为resourceManager，其余为NodeManager。在某一台机器上配置，所有文件均包含了xml头

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

core-site.xml文件

<name>fs.defaultFS</name>

<value>hdfs://bigdata-senior01.chybinmy.com:9000</value>

</property>

<name>io.file.buffer.size</name>

</property>

</configuration>

hdfs-site.xml文件

<name>dfs.namenode.name.dir</name>

<value>/usr/local/hadoop/tmp/namenode</value>

<description>Path on the local filesystem where the NameNode stores the namespace and transactions logs persistently.</description>

</property>

<name>dfs.namenode.hosts</name>

<value>bigdata-senior02.chybinmy.com，bigdata-senior03.chybinmy.com，bigdata-senior04.chybinmy.com</value>

<description>List of permitted/excluded DataNodes</description>

</property>

<name>dfs.blocksize</name>

</property>

<name>dfs.namenode.handler.count</name>

<description>More NameNode server threads to handle RPCs from large number of DataNodes</description>

</property>

<name>dfs.datanode.data.dir</name>

<value>/usr/local/hadoop-3.0.3/tmp/datanode</value>

</property>

</configuration>

yarn-site.xml文件

<name>yarn.resourcemanager.address</name>

<value>bigdata-senior02.chybinmy.com:8081</value>

<description> ResourceManager host:port for clients to submit jobs</description>

</property>

<name>yarn.resourcemanager.scheduler.address</name>

<value>bigdata-senior02.chybinmy.com:8082</value>

<description>ResourceManager host:port for ApplicationMasters to talk to Scheduler to obtain resources</description>

</property>

<name>yarn.resourcemanager.resource-tracker.address</name>

<value>bigdata-senior02.chybinmy.com:8083</value>

<description>ResourceManager host:port for NodeManagers</description>

</property>

<name>yarn.resourcemanager.admin.address</name>

<value>bigdata-senior02.chybinmy.com:8084</value>

<description>ResourceManager host:port for administrative commands</description>

</property>

<name>yarn.resourcemanager.webapp.address</name>

<value>bigdata-senior02.chybinmy.com:8085</value>

<description>ResourceManager web-ui host:port</description>

</property>

<name>yarn.resourcemanager.hostname</name>

<value>bigdata-senior02.chybinmy.com</value>

<description>ResourceManager host:host Single hostname that can be set in place of setting all yarn.resourcemanager*address resources. Results in default ports for ResourceManager components.</description>

</property>

<name>yarn.resourcemanager.scheduler.class</name>

<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairSchedule</value>

<description>ResourceManager Scheduler class:CapacityScheduler (recommended), FairScheduler (also recommended), or FifoScheduler. Use a fully qualified class name, e.g., org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler.</description>

</property>

<name>yarn.scheduler.minimum-allocation-mb</name>

<description>Minimum limit of memory to allocate to each container request at the Resource Manager</description>

</property>

<name>yarn.scheduler.maximum-allocation-mb</name>

<description>Maximum limit of memory to allocate to each container request at the Resource Manager</description>

</property>

<name>yarn.resourcemanager.nodes.include-path</name>

<value>bigdata-senior01.chybinmy.com,bigdata-senior03.chybinmy.com,bigdata-senior04.chybinmy.com</value>

<description>List of permitted NodeManager</description>

</property>

<name>yarn.nodemanager.resource.memory-mb</name>

<description>Resource i.e. available physical memory, in MB, for given NodeManager</description>

</property>

<name>yarn.nodemanager.vmem-pmem-ratio</name>

<description>Maximum ratio by which virtual memory usage of tasks may exceed physical memory</description>

</property>

<name>yarn.nodemanager.local-dirs</name>

<value>/usr/local/hadoop/tmp/nodemanager</value>

<description>Comma-separated list of paths on the local filesystem where intermediate data is written</description>

</property>

<name>yarn.nodemanager.log-dirs</name>

<value>/usr/local/hadoop/tmp/nodemanager/logs</value>

<description>Comma-separated list of paths on the local filesystem where logs are written.</description>

</property>

<name>yarn.nodemanager.log.retain-seconds</name>

<description>seconds</description>

</property>

<name>yarn.nodemanager.remote-app-log-dir</name>

<description>HDFS directory where the application logs are moved on application completion. Need to set appropriate permissions. Only applicable if log-aggregation is enabled.</description>

</property>

<name>yarn.nodemanager.remote-app-log-dir-suffix</name>

<description>Suffix appended to the remote log dir. Logs will be aggregated to ${yarn.nodemanager.remote-app-log-dir}/${user}/${thisParam} Only applicable if log-aggregation is enabled</description>

</property>

<name>yarn.nodemanager.aux-services</name>

<value>mapreduce-shuffle</value>

<description>Shuffle service that needs to be set for Map Reduce applications</description>

</property>

</configuration>

mapred-site.xml文件

<name> mapreduce.framework.name</name>

<description>Execution framework set to Hadoop YARN</description>

</property>

<name>mapreduce.map.memory.mb</name>

<description>Larger resource limit for maps</description>

</property>

<name>mapreduce.map.java.opts</name>

<description>Larger heap-size for child jvms of maps</description>

</property>

<name>mapreduce.reduce.memory.mb</name>

<description>Larger resource limit for reduces</description>

</property>

<name>mapreduce.reduce.java.opts</name>

<description>Larger heap-size for child jvms of reduces</description>

</property>

<name>mapreduce.task.io.sort</name>

<description>Higher memory-limit while sorting data for efficiency</description>

</property>

<name>mapreduce.task.io.sort.factor</name>

<description>More streams merged at once while sorting files.</description>

</property>

<name>mapreduce.reduce.shuffle.parallelcopies</name>

<description>Higher number of parallel copies run by reduces to fetch outputs from very large number of maps</description>

</property>

<name> mapreduce.jobhistory.address</name>

<value>bigdata-senior01.chybinmy.com:10200</value>

</property>

<name>mapreduce.jobhistory.webapp.address</name>

<value>bigdata-senior01.chybinmy.com:19888</value>

</property>

<name>mapreduce.jobhistory.intermediate-done-dir</name>

<value>/usr/local/hadoop/mrhistory/tmp</value>

<description>Directory where history files are written by MapReduce jobs</description>

</property>

<name>mapreduce.jobhistory.done-dir</name>

<value>/usr/local/hadoop/mrhistory/done</value>

<description>Directory where history files are managed by the MR JobHistory Server</description>

</property>

</configuration>

workers文件

bigdata-senior01.chybinmy.com

bigdata-senior02.chybinmy.com

bigdata-senior03.chybinmy.com

bigdata-senior04.chybinmy.com

hadoop-env文件增加一行

export JAVA_HOME=/usr/local/jdk-10.0.2

格式化hdfs本地系统

$HADOOP_HOME/bin/hdfs namenode -format <cluster_name>

若是出现INFO common.Storage: Storage directory /usr/local/hadoop/tmp/namenode has been successfully formatted字样，表示格式化成功。

分发六个配置文件至其他主机。我使用SCP命令来分发的

在datanode节点开启datanode服务

$HADOOP_HOME/bin/hdfs --daemon start datanode

在NameNode节点开启NameNode服务

$HADOOP_HOME/bin/hdfs --daemon start namenode

出现错误：

ERROR: Attempting to operate on hdfs namenode as root

ERROR: but there is no HDFS_NAMENODE_USER defined. Aborting operation.

Starting datanodes

ERROR: Attempting to operate on hdfs datanode as root

ERROR: but there is no HDFS_DATANODE_USER defined. Aborting operation.

Starting secondary namenodes [bigdata-senior01.chybinmy.com]

ERROR: Attempting to operate on hdfs secondarynamenode as root

ERROR: but there is no HDFS_SECONDARYNAMENODE_USER defined. Aborting operation.

先暂停 hdfs服务：$HADOOP_HOME/sbin/stop-dfs.sh

编辑所有主机的/etc/hadoop下的hadoop-env.sh文件，

增加四行如下：

export HDFS_DATANODE_USER=root

export HDFS_NAMENODE_USER=root

export HDFS_SECONDARYNAMENODE_USER=root

export HDFS_DATANODE_SECURE_USER=root

这四行的作用是指定可执行hdfs命令的用户

重新执行一下sh ./hadoop-env.sh

在resourceManager节点上开启resourceManager服务，运行命令$HADOOP_HOME/bin/yarn --daemon start resourcemanager

在nodeManager上起开nodeManager服务，运行命令$HADOOP_HOME/bin/yarn --daemon start nodemanager

在nodeManager上运行命令$HADOOP_HOME/sbin/start-yarn.sh ，出现错误

Starting resourcemanager

ERROR: Attempting to operate on yarn resourcemanager as root

ERROR: but there is no YARN_RESOURCEMANAGER_USER defined. Aborting operation.

Starting nodemanagers

ERROR: Attempting to operate on yarn nodemanager as root

ERROR: but there is no YARN_NODEMANAGER_USER defined. Aborting operation.

在nodeManager的hadoop-env.sh中，增加两行：

export YARN_RESOURCEMANAGER_USER=root

export YARN_NODEMANAGER_USER=root

再次运行$HADOOP_HOME/bin/yarn --daemon start nodemanager

在ResourceManager上运行$HADOOP_HOME/bin/mapred --daemon start historyserver

Use --illegal-access=warn

当hadoop启动命令执行结束后，可以通过查看webUI来检查hadoop运行状况：

namenode查看网址为172.168.0.5:9870

错误：

stopping yarn daemons

no resourcemanager to stop

bigdata-senior04.localdomain: no nodemanager to stop

bigdata-senior02.localdomain: no nodemanager to stop

bigdata-senior03.localdomain: no nodemanager to stop

bigdata-senior01.localdomain: no nodemanager to stop

原因：

<name>yarn.nodemanager.aux-services</name>

<value>mapreduce_shuffle</value>

</property>

中，将下划线"_"写成了横杠"-"

错误：

INFO client.RMProxy: Connecting to ResourceManager at bigdata-senior02.localdomain/172.168.0.6:8081

INFO ipc.Client: Retrying connect to server: bigdata-senior02.localdomain/172.168.0.6:8081

同时jps命令下有nodeManager，无resourceManger，说明resourceManger没有启动起来，通过查看日志/usr/local/hadoop-2.8.4/logs/yarn-root-resourcemanager-bigdata-senior02.chybinmy.com.log发现不能初始化FairScheduler

我将 <property>

<name>yarn.resourcemanager.scheduler.class</name>

<value>FairScheduler</value>

</property>

注释掉之后就没事儿了，后来发现应该把value值写为org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler，连官网都不能信啊

错误：使用hadoop fs -put命令上传文件

WARN ipc.Client: Failed to connect to server: bigdata-senior01.localdomain/172.168.0.5:8020:

命令应该为 hadoop fs -put ./shakespeare.txt hdfs://172.168.0.5:9000/或者hadoop fs -put ./shakespeare.txt /

错误：status=ERROR, status message , ack with firstBadLink as 172.168.0.8:50010

原因：172.168.0.8防火墙未关闭

错误：

java.io.IOException: org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid resource request, requested memory < 0, or requested memory > max configured, requestedMemory=1536, maxMemory=256

原因：

程序申请的内存资源超出了yarn的设置。在程序中添加两行代码：

修改etc/hadoop/yarn-site.xml里面yarn.nodemanager.resource.memory-mb的值，使其大于mapreduce.map.memory.mb和mapreduce.reduce.memory.mb的值即可

错误：PipeMapRed.waitOutputThreads(): subprocess failed with code 2

原因：从window系统向linux系统传送文件时，当以binary方式传送就会出现错误，修改为text传送，即正确，当然传送之后需要设置可执行权限。根本上是文件格式出了问题

错误：PipeMapRed.waitOutputThreads(): subprocess failed with code 1

原因：程序内部问题，本地就是失败的，出现了异常

centos 7搭建hadoop环境及踩到的坑

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