0目录
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| 1.Hadoop 入门 2.linux 安装hadoop |
1.Hadoop入门
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| 定义 Hadoop 是一个由Apache基金会所开发的分布式系统基础架构。用户可以在不了解分布式底层细节的情况下，开发分布式程序。充分利用集群的威力进行高速运算和存储。 |
| 优势 高可靠性：Hadoop底层维护多个数据副本，所以即使hadoop某个计算元素或存储出现故障,也不会导致数据的丢失 高扩展性：在集群间分配任务数据，可方便的扩展以千计的节点 高效性：在MapReduce的思想下，Hadoop是并行工作的，以加快任何处理速度 高容错性:能够自动将失败的任务重新分配 |
| Hadoop 1.x;2.x 和3.x的区别 
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| HDFS 概述 Hadoop Distributed File System 简称HDFS，是一个分布式文件系统 HDFS 架构概述 NameNode （nn）:存储文件的元数据，如文件名，文件目录结构，文件属性 DataNode （dn）:在本地文件系统存储文件块数据，以及块数据的校验和 Secondary NameNode （2nn）: 每隔一段时间对NameNode元数据备份 
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| YARN 概述 YetAnother Resource Negotiator 简称YARN，另一种资源协调者,是Hadoop的资源管理器 YARN 架构概述 ResourceManager （RM）：整个集群资源（内存、cpu等）的老大 NodeManager ：单个节点服务器资源老大 ApplicationMaster ：单个任务运行的老大 Container ：容器，相当于一台独立的服务器，里面封装了任务运行所需的资源，如内存、cpu、磁盘、网络等 |
| MapReduce 架构概述 MapReduce 将计算过程分成2个阶段，map和reduce map 阶段并行处理输入数据 Reudce 阶段对map结果进行汇总 |
| 补充hadoop生态圈 
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2.Linux安装hadoop
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| 1.1 安装jDK：略 |
| 1.2 下载安装Hadoop 解压至opt/soft目录下，改名为hadoop313 
更改所属用户为root 
配置环境变量：vim /etc/profilre；配置完成后source /etc/profile # HADOOP_HOME export HADOOP_HOME=/opt/soft/hadoop313 export PATH=PATH:HADOOP_HOME/bin:HADOOP_HOME/sbin:HADOOP_HOME/lib export HDFS_NAMENODE_USER=root export HDFS_DATANODE_USER=root export HDFS_SECONDARYNAMENODE=root export HDFS_JOURNALNODE_USER=root export HDFS_ZKFC_USER=root export YARN_RESOURCEMANAGER_USER=root export YARN_NODEMANAGER_USER=root export HADOOP_MAPRED_HOME=HADOOP_HOME** **export HADOOP_COMMON_HOME=HADOOP_HOME export HADOOP_HDFS_HOME=HADOOP_HOME** **export HADOOP_YARN_HOME=HADOOP_HOME export HADOOP_INSTALL=HADOOP_HOME** **export HADOOP_COMMON_LIB_NATIVE_DIR=HADOOP_HOME/lib/native export HADOOP_LIBEXEC_DIR=HADOOP_HOME/libexec** **export JAVA_LIBRARY_PATH=HADOOP_HOME/lib/native export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop 
创建数据目录data 
切换至hadoop目录，查看目录下文件，准备进行配置 cd /opt/soft/hadoop313/etc/hadoop 
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| 1.3 配置单机Hadoop （1）配置core-site.xml <configuration> <!-- 指定NameNode的地址 --> <property> <name>fs.defaultFS</name> <value>hdfs://kb129:9000</value> </property> <!-- 指定hadoop数据的存储目录 --> <property> <name>hadoop.tmp.dir</name> <value>/opt/soft/hadoop313/data</value> </property> <!-- 配置HDFS网页登录使用的静态用户为root --> <property> <name>hadoop.http.staticuser.user</name> <value>root</value> </property> <property> <name>io.file.buffer.size</name> <value>131072</value> </property> <property> <name>hadoop.proxyuser.root.hosts</name> <value>*</value> </property> <property> <name>hadoop.proxyuser.root.groups</name> <value>*</value> </property> </configuration> 
1. 配置hdfs-site.xml <property> <name>dfs.replication</name> <value>1</value> </property> <property> <name>dfs.namenode.name.dir</name> <value>/opt/soft/hadoop313/data/dfs/name</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>/opt/soft/hadoop313/data/dfs/data</value> </property> <property> <name>dfs.permissions.enabled</name> <value>false</value> </property> 
（3）编辑hadoop-env.sh: 
> （4）配置yarn-site.xml <configuration> <!-- Site specific YARN configuration properties --> <!-- 每隔20s测试连接 --> <property> <name>yarn.resourcemanager.connect.retry-interval.ms</name> <value>20000</value> </property> <property> <name>yarn.resourcemanager.scheduler.class</name> <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value> </property> <property> <name>yarn.nodemanager.localizer.address</name> <value>kb129:8040</value> </property> <property> <name>yarn.nodemanager.address</name> <value>kb129:8050</value> </property> <property> <name>yarn.nodemanager.webapp.address</name> <value>kb129:8042</value> </property> <!-- 指定MapReduce走shuffle --> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.nodemanager.local-dirs</name> <value>/opt/soft/hadoop313/yarndata/yarn</value> </property> <property> <name>yarn.nodemanager.log-dirs</name> <value>/opt/soft/hadoop313/yarndata/log</value> </property> <property> <name>yarn.nodemanager.vmem-check-enabled</name> <value>false</value> </property> </configuration> 
更改workers内容为kb129 
（4）配置mapred-site.xml <configuration> <!-- 指定MapReduce程序运行在Yarn上 --> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>kb129:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>kb129:19888</value> </property> <property> <name>mapreduce.map.memory.mb</name> <value>2048</value> </property> <property> <name>mapreduce.reduce.memory.mb</name> <value>2048</value> </property> <property> <name>mapreduce.application.classpath</name> <value>/opt/soft/hadoop313/etc/hadoop:/opt/soft/hadoop313/share/hadoop/common/lib/*:/opt/soft/hadoop313/share/hadoop/common/*:/opt/soft/hadoop313/share/hadoop/hdfs/*:/opt/soft/hadoop313/share/hadoop/hdfs/lib/*:/opt/soft/hadoop313/share/hadoop/mapreduce/*:/opt/soft/hadoop313/share/hadoop/mapreduce/lib/*:/opt/soft/hadoop313/share/hadoop/yarn/*:/opt/soft/hadoop313/share/hadoop/yarn/lib/*</value> </property> </configuration> 
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| 1.4 启动测试hadoop （1）设置免密登录 回到根目录下配置kb129免密登录：ssh-keygen -t rsa -P "" 将本地主机的公钥文件（~/.ssh/id_rsa.pub）拷贝到远程主机 kb128 的 root 用户的 .ssh/authorized_keys 文件中，通过 SSH 连接到远程主机时可以使用公钥进行身份验证：cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys 
将本地主机的公钥添加到远程主机的授权密钥列表中，以便实现通过 SSH 公钥身份验证来连接远程主机：ssh-copy-id -i ~/.ssh/id_rsa.pub -p22 root@kb128 检测登录 
（2）bin目录下初始化集群hadoop namenode -format 
开始 
检查是否都开启 
关闭 
1. 网页测试：浏览器中输入网址： http://192.168.142.129:9870/ 
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