CentOS 安装 Hadoop Local (Standalone) Mode 单机模式

CentOS 安装 Hadoop Local (Standalone) Mode 单机模式

Hadoop Local (Standalone) Mode 单机模式

1. 修改yum源 并升级内核和软件

curl -o /etc/yum.repos.d/CentOS-Base.repo https://mirrors.aliyun.com/repo/Centos-7.repo

yum clean all

yum makecache

yum -y update

2. 安装常用软件

yum -y install gcc gcc-c++ autoconf automake cmake make \zlib zlib-devel openssl openssl-devel pcre-devel \rsync openssh-server vim man zip unzip net-tools tcpdump lrzsz tar wget

3. 关闭防火墙

sed -i 's/SELINUX=enforcing/SELINUX=disabled/g' /etc/selinux/config
setenforce 0

systemctl stop firewalld
systemctl disable firewalld

4. 修改主机名和IP地址

hostnamectl set-hostname hadoop

vim /etc/sysconfig/network-scripts/ifcfg-ens32

参考如下：

TYPE="Ethernet"
PROXY_METHOD="none"
BROWSER_ONLY="no"
BOOTPROTO="none"
DEFROUTE="yes"
IPV4_FAILURE_FATAL="no"
IPV6INIT="yes"
IPV6_AUTOCONF="yes"
IPV6_DEFROUTE="yes"
IPV6_FAILURE_FATAL="no"
IPV6_ADDR_GEN_MODE="stable-privacy"
NAME="ens32"
UUID="61b382ca-cdf2-47dc-b9b4-01ea57c805d7"
DEVICE="ens32"
ONBOOT="yes"
IPADDR="192.168.171.10"
PREFIX="24"
GATEWAY="192.168.171.2"
DNS1="192.168.171.2"
IPV6_PRIVACY="no"

5. 修改hosts配置文件

vim /etc/hosts

修改内容如下：

192.168.171.10	hadoop

重启系统

reboot

6. 下载安装JDK和Hadoop并配置环境变量

创建软件目录

mkdir -p /opt/soft 

进入软件目录

cd /opt/soft

下载 JDK

wget https://download.oracle.com/otn/java/jdk/8u391-b13/b291ca3e0c8548b5a51d5a5f50063037/jdk-8u391-linux-x64.tar.gz?AuthParam=1698206552_11c0bb831efdf87adfd187b0e4ccf970

下载 hadoop

wget https://dlcdn.apache.org/hadoop/common/hadoop-3.3.5/hadoop-3.3.5.tar.gz

解压 JDK 修改名称

tar -zxvf jdk-8u391-linux-x64.tar.gz -C /opt/soft/

mv jdk1.8.0_391/ jdk-8

解压 hadoop 修改名称

tar -zxvf hadoop-3.3.5.tar.gz -C /opt/soft/

mv hadoop-3.3.5/ hadoop-3

配置环境变量

vim /etc/profile.d/my_env.sh

编写以下内容：

export JAVA_HOME=/opt/soft/jdk-8
export set JAVA_OPTS="--add-opens java.base/java.lang=ALL-UNNAMED"export HDFS_NAMENODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_ZKFC_USER=root
export HDFS_JOURNALNODE_USER=rootexport YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=rootexport HADOOP_HOME=/opt/soft/hadoop-3export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

生成新的环境变量

source /etc/profile

7. 配置ssh免密钥登录

创建本地秘钥并将公共秘钥写入认证文件

ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa

ssh-copy-id root@hadoop

# 远程登录自己
ssh hadoop
# Are you sure you want to continue connecting (yes/no)? 此处输入yes
# 登录成功后exit或者logout返回
exit

8. 修改配置文件

hadoop-env.sh

core-site.xml

hdfs-site.xml

workers

mapred-site.xml

yarn-site.xml

hadoop-env.sh

hadoop-env.sh 文件末尾追加

export JAVA_HOME=/opt/soft/jdk-8
export set JAVA_OPTS="--add-opens java.base/java.lang=ALL-UNNAMED"export HDFS_NAMENODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_ZKFC_USER=root
export HDFS_JOURNALNODE_USER=rootexport YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root

core-site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration><property><name>fs.defaultFS</name><value>hdfs://hadoop:9000</value></property><property><name>hadoop.tmp.dir</name><value>/home/hadoop_data</value></property><property><name>hadoop.http.staticuser.user</name><value>root</value></property><property><name>dfs.permissions.enabled</name><value>false</value></property><property><name>hadoop.proxyuser.root.hosts</name><value>*</value></property><property><name>hadoop.proxyuser.root.groups</name><value>*</value></property>
</configuration>

hdfs.site.xml

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration><property><name>dfs.replication</name><value>1</value></property><property><name>dfs.namenode.secondary.http-address</name><value>hadoop:50090</value></property>
</configuration>

workers

注意：

​ hadoop2.x中该文件名为slaves

​ hadoop3.x中该文件名为workers

hadoop

mapred-site.xml

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration><property><name>mapreduce.framework.name</name><value>yarn</value></property><property><name>mapreduce.application.classpath</name><value>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*:$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*</value></property>
</configuration>

yarn-site.xml

<?xml version="1.0"?>
<configuration><property><name>yarn.nodemanager.aux-services</name><value>mapreduce_shuffle</value></property><property><name>yarn.nodemanager.env-whitelist</name><value>JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE,HADOOP_YARN_HOME,HADOOP_HOME,PATH,LANG,TZ,HADOOP_MAPRED_HOME</value></property>
</configuration>

9. 初始化集群

# 格式化文件系统
hdfs namenode -format
# 启动 NameNode SecondaryNameNode DataNode 
start-dfs.sh
# 查看启动进程
jps
# 看到 DataNode SecondaryNameNode NameNode 三个进程代表启动成功

# 启动 ResourceManager daemon 和 NodeManager
start-yarn.sh
# 看到 DataNode NodeManager SecondaryNameNode NameNode ResourceManager 五个进程代表启动成功

重点提示：

# 关机之前 依关闭服务
stop-yarn.sh
stop-dfs.sh
# 开机后 依次开启服务
start-dfs.sh
start-yarn.sh

或者

# 关机之前关闭服务
stop-all.sh
# 开机后开启服务
start-all.sh

#jps 检查进程正常后开启胡哦关闭在再做其它操作

10. 修改windows下hosts文件

C:\Windows\System32\drivers\etc\hosts

追加以下内容：

192.168.171.10	hadoop
192.168.171.11	spark01
192.168.171.12	spark02
192.168.171.13	spark03

Windows11 注意 修改权限

11. 测试

浏览器访问: http://hadoop:9870

浏览器访问:http://hadoop:50090/

浏览器访问:http://hadoop:8088

11.1 测试 hdfs

本地文件系统创建 测试文件 wcdata.txt

vim wcdata.txt

Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive
FlinkHBase Flink
Hive StormHive Flink HadoopHBase
HiveHadoop Spark HBase StormHBase
Hadoop Hive FlinkHBase Flink Hive StormHive
Flink HadoopHBase Hive
Spark HBaseHive Flink
Storm Hadoop HBase SparkFlinkHBase
StormHBase Hadoop Hive

在 HDFS 上创建目录 /wordcount/input

hdfs dfs -mkdir -p /wordcount/input

查看 HDFS 目录结构

hdfs dfs -ls /

hdfs dfs -ls /wordcount

hdfs dfs -ls /wordcount/input

上传本地测试文件 wcdata.txt 到 HDFS 上 /wordcount/input

hdfs dfs -put wcdata.txt /wordcount/input

检查文件是否上传成功

hdfs dfs -ls /wordcount/input

hdfs dfs -cat /wordcount/input/wcdata.txt

11.2 测试 mapreduce

计算 PI 的值

hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.3.5.jar pi 10 10

单词统计

hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.3.5.jar wordcount /wordcount/input/wcdata.txt /wordcount/result

hdfs dfs -ls /wordcount/result

hdfs dfs -cat /wordcount/result/part-r-00000