16-hadoop的架构
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17-hadoop的安装-准备工作
利用NodePad++的FtpNpp插件更改下面6个配置文件:
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18-hadoop的安装-配置文件修改
core-site.xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://node01:8020</value>
</property>
<!-- 临时文件存储目录 -->
<property>
<name>hadoop.tmp.dir</name>
<value>/export/servers/hadoop-3.1.1/datas/tmp</value>
</property>
<!-- 缓冲区大小,实际工作中根据服务器性能动态调整 -->
<property>
<name>io.file.buffer.size</name>
<value>8192</value>
</property>
<!-- 开启hdfs的垃圾桶机制,删除掉的数据可以从垃圾桶中回收,单位分钟 -->
<property>
<name>fs.trash.interval</name>
<value>10080</value>
</property>
</configuration>
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hadoop-env.sh
export JAVA_HOME=/export/servers/jdk1.8.0_141
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hdfs-site.xml
<configuration>
<!-- 配置namenode元数据的存放路径 -->
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///export/servers/hadoop-3.1.1/datas/namenode/namenodedatas</value>
</property>
<!-- 设置文件分块的大小:BLOCK -->
<property>
<name>dfs.blocksize</name>
<value>134217728</value>
</property>
<property>
<name>dfs.namenode.handler.count</name>
<value>10</value>
</property>
<!-- datanode数据存放目录 -->
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///export/servers/hadoop-3.1.1/datas/datanode/datanodeDatas</value>
</property>
<!-- 通过浏览器访问hdfs的端口数据存放目录 -->
<property>
<name>dfs.namenode.http-address</name>
<value>node01:50070</value>
</property>
<!-- 设置文件的副本数 -->
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<!-- 设置HDFS的权限访问 -->
<property>
<name>dfs.permissions.enabled</name>
<value>false</value>
</property>
<property>
<name>dfs.namenode.checkpoint.edits.dir</name>
<value>file:///export/servers/hadoop-3.1.1/datas/dfs/nn/snn/edits</value>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>node01.hadoop.com:50090</value>
</property>
<!--设置HDFS日志文件的存放路径 -->
<property>
<name>dfs.namenode.edits.dir</name>
<value>file:///export/servers/hadoop-3.1.1/datas/dfs/nn/edits</value>
</property>
<property>
<name>dfs.namenode.checkpoint.dir</name>
<value>file:///export/servers/hadoop-3.1.1/datas/dfs/snn/name</value>
</property>
</configuration>
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mapred-site.xml
<configuration>
<!-- 指定MapReduce的执行框架:yarn集群 -->
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.map.memory.mb</name>
<value>1024</value>
</property>
<property>
<name>mapreduce.map.java.opts</name>
<value>-Xmx512M</value>
</property>
<property>
<name>mapreduce.reduce.memory.mb</name>
<value>1024</value>
</property>
<property>
<name>mapreduce.reduce.java.opts</name>
<value>-Xmx512M</value>
</property>
<property>
<name>mapreduce.task.io.sort.mb</name>
<value>256</value>
</property>
<property>
<name>mapreduce.task.io.sort.factor</name>
<value>100</value>
</property>
<property>
<name>mapreduce.reduce.shuffle.parallelcopies</name>
<value>25</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>node01.hadoop.com:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>node01.hadoop.com:19888</value>
</property>
<property>
<name>mapreduce.jobhistory.intermediate-done-dir</name>
<value>/export/servers/hadoop-3.1.1/datas/jobhsitory/intermediateDoneDatas</value>
</property>
<property>
<name>mapreduce.jobhistory.done-dir</name>
<value>/export/servers/hadoop-3.1.1/datas/jobhsitory/DoneDatas</value>
</property>
<property>
<name>yarn.app.mapreduce.am.env</name>
<value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1</value>
</property>
<property>
<name>mapreduce.map.env</name>
<value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1/</value>
</property>
<property>
<name>mapreduce.reduce.env</name>
<value>HADOOP_MAPRED_HOME=/export/servers/hadoop-3.1.1</value>
</property>
</configuration>
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yarn-site.xml(主要是来配置yarn集群的)
<configuration>
<property>
<name>dfs.namenode.handler.count</name>
<value>100</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>node01:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>node01:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>node01:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>node01:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>node01:8088</value>
</property>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>node01</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>1024</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>2.1</value>
</property>
<!-- 设置不检查虚拟内存的值,不然内存不够会报错 -->
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>1024</value>
</property>
<property>
<name>yarn.nodemanager.resource.detect-hardware-capabilities</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>file:///export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerDatas</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>file:///export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerLogs</value>
</property>
<property>
<name>yarn.nodemanager.log.retain-seconds</name>
<value>10800</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>/export/servers/hadoop-3.1.1/datas/remoteAppLog/remoteAppLogs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir-suffix</name>
<value>logs</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>18144000</value>
</property>
<property>
<name>yarn.log-aggregation.retain-check-interval-seconds</name>
<value>86400</value>
</property>
<!-- yarn上面运行一个任务,最少需要1.5G内存,虚拟机没有这么大的内存就调小这个值,不然会报错 -->
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>1024</value>
</property>
</configuration>
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works(主要是设置从机的有3个)
node01
node02
node03
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#### 3. 创建数据和临时文件夹
```shell
mkdir -p /export/servers/hadoop-3.1.1/datas/tmp
mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/nn/snn/edits
mkdir -p /export/servers/hadoop-3.1.1/datas/namenode/namenodedatas
mkdir -p /export/servers/hadoop-3.1.1/datas/datanode/datanodeDatas
mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/nn/edits
mkdir -p /export/servers/hadoop-3.1.1/datas/dfs/snn/name
mkdir -p /export/servers/hadoop-3.1.1/datas/jobhsitory/intermediateDoneDatas
mkdir -p /export/servers/hadoop-3.1.1/datas/jobhsitory/DoneDatas
mkdir -p /export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerDatas
mkdir -p /export/servers/hadoop-3.1.1/datas/nodemanager/nodemanagerLogs
mkdir -p /export/servers/hadoop-3.1.1/datas/remoteAppLog/remoteAppLogs
#### 4. 分发安装包到其它机器
```shell
cd /export/servers
scp -r hadoop-3.1.1/ node02:$PWD
scp -r hadoop-3.1.1/ node03:$PWD
#### 5. 在每个节点配置环境变量
```shell
vi /etc/profile
```
```shell
export HADOOP_HOME=/export/servers/hadoop-3.1.1/
export PATH=:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
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19-hadoop的安装-启动集群
#### 6. 格式化HDFS(格式化 的时候会创建一些中间文件)
- 为什么要格式化HDFS
- HDFS需要一个格式化的过程来创建存放元数据(image, editlog)的目录
```shell
bin/hdfs namenode -format
```
#### 7. 启动集群
```shell
# 会登录进所有的worker启动相关进行, 也可以手动进行, 但是没必要
//HDFS启动成功
/export/servers/hadoop-3.1.1/sbin/start-dfs.sh
//启动yarn集群
/export/servers/hadoop-3.1.1/sbin/start-yarn.sh
mapred --daemon start historyserver
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(1).启动HDFS
//HDFS启动成功
报错:设置hadoop-env.sh
~~~shell
export HDFS_NAMENODE_USER="root"
export HDFS_DATANODE_USER="root"
export HDFS_SECONDARYNAMENODE_USER="root"
export YARN_RESOURCEMANAGER_USER="root"
export YARN_NODEMANAGER_USER="root"
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(2).启动yarn集群
//启动yarn集群
/export/servers/hadoop-3.1.1/sbin/start-yarn.sh