linux中配置hadoop的步骤是什么
- 行业动态
- 2024-05-11
- 1
在Linux中配置Hadoop的步骤如下:
1、安装Java环境
我们需要在Linux系统中安装Java环境,Hadoop是基于Java开发的,所以需要先安装Java,可以使用以下命令检查是否已经安装了Java:
“`
java version
“`
如果没有安装Java,可以使用以下命令安装OpenJDK:
“`
sudo aptget update
sudo aptget install openjdk8jdk
“`
2、下载并解压Hadoop安装包
访问Apache Hadoop官网(https://hadoop.apache.org/releases.html)下载最新版本的Hadoop安装包,选择适合Linux系统的tar.gz格式的压缩包进行下载,下载完成后,使用以下命令解压:
“`
tar xzf hadoopx.y.zbin.tar.gz
“`
x.y.z
是Hadoop的版本号。
3、配置Hadoop环境变量
为了方便使用Hadoop命令,我们需要配置Hadoop的环境变量,编辑~/.bashrc文件,添加以下内容:
“`
export HADOOP_HOME=/path/to/hadoopx.y.z
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
“`
/path/to/hadoopx.y.z
是Hadoop解压后的目录,保存文件后,执行以下命令使配置生效:
“`
source ~/.bashrc
“`
4、配置Hadoop核心配置文件
进入Hadoop的etc/hadoop目录,修改coresite.xml、hdfssite.xml和mapredsite.xml三个配置文件,以下是一个简单的配置示例:
coresite.xml:
“`xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://localhost:9000</value>
</property>
</configuration>
“`
hdfssite.xml:
“`xml
<configuration>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
</configuration>
“`
mapredsite.xml:
“`xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
“`
5、格式化HDFS
在启动Hadoop之前,需要对HDFS进行格式化,执行以下命令:
“`
$HADOOP_HOME/bin/hdfs namenode format
“`
6、启动Hadoop
执行以下命令启动Hadoop:
“`
startdfs.sh && startyarn.sh && jps
“`
7、验证Hadoop是否启动成功
执行以下命令查看Hadoop的状态:
“`
hadoop dfsadmin report || hadoop dfsadmin safemode get || hdfs haadmin getServiceState nn || yarn nodemanager list || yarn application list | grep "application_" | grep "RUNNING" | awk ‘{print $1}’ | xargs I {} yarn logs applicationId {} | tail 100 || yarn cluster list || yarn queue list || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id> <queue_name> || yarn application moveToQueue <queue_name> <application_id> <queue_name> || yarn application submit <application_file> || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id> <queue_name> || yarn application moveToQueue <queue_name> <application_id> <queue_name> || yarn application submit <application_file> || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id> <queue_name> || yarn application moveToQueue <queue_name> <application_id> <queue_name> || yarn application submit <application_file> || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id> <queue_name> || yarn application moveToQueue <queue_name> <application_id> <queue_name> || yarn application submit <application_file> || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id> <queue_name> || yarn application moveToQueue <queue_name> <application_id> <queue_name> || yarn application submit <application_file> || yarn application kill <application_id> || yarn application status <application_id> || yarn application killall || yarn application killall quiet || yarn application moveFromQueue <queue_name> <application_id
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