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linux中配置hadoop的步骤是什么

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在Linux中配置Hadoop的步骤如下:

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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

更新时间 2024-05-20 15:27:52