hadoop2.6.4 安装和编译

2016-07-25 777

hadoop集群搭建

tools：

SecureCRT8.0
VMware12
RHEL 6.6 x64

网络规划：

hadoop0 192.168.248.150
hadoop1 192.168.248.151
hadoop2 192.168.248.152
hadoop3 192.168.248.153

设置静态ip：

sudo vim /etc/sysconfig/network-scripts/ifcfg-eth0
IPADDR=192.168.248.15?

如果网络不行（由于虚拟机克隆）
检查/etc/udev/rule.d/70-persistent-net.rules
ifcfg-eth0中的HWADDR

设置hostname：
vim /etc/sysconfig/network
HOSTNAME=hadoop?

关闭防火墙

service iptables stop

vim /etc/selinux/config
SELINUX=disabled

setenforce 0

创建用户：

useradd hadoop
passwd hadoop #hadoop

配置主机映射：

vim /etc/hosts
192.168.248.150 hadoop0
192.168.248.151 hadoop1
192.168.248.152 hadoop2
192.168.248.153 hadoop3

开启ssh免密登录（NameNode登录其他DataNode）

生成非对称秘钥
su - hadoop
ssh-keygen -t rsa

拷贝NameNode公钥到其他节点上
[hadoop@hadoop0 ~]$
cp id_rsa.pub authorized_keys
scp ~/.ssh/id_rsa.pub hadoop1:~/.ssh/authorized_keys
scp ~/.ssh/id_rsa.pub hadoop2:~/.ssh/authorized_keys
scp ~/.ssh/id_rsa.pub hadoop3:~/.ssh/authorized_keys

如果不能ssh免密登录，则其它节点上
chmod 600 authorized_keys

安装java

sftp上传
sftp> ls
sftp> lcd D:\归档\软件\笔记本\linux
sftp> lls
jdk-8u40-linux-x64.tar.gz web
sftp> put jdk-8u40-linux-x64.tar.gz

scp jdk-8u40-linux-x64.tar.gz hadoop?:~/

tar zxf jdk-8u40-linux-x64.tar.gz

su - root
mv /home/hadoop/jdk1.8.0_40/ /opt/

配置环境变量：

vim /etc/profile
export JAVA_HOME=/opt/jdk1.8.0_40
export JRE_HOME=/opt/jdk1.8.0_40/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib:$CLASSPATH
export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH

配置生效：
source /etc/profile

验证：
java -version

安装hadoop

先配置一个节点（master，再复制到其它slave中）
sftp> put hadoop-2.6.4.tar.gz

[hadoop@hadoop0 ~]$ tar zxf hadoop-2.6.4.tar.gz

配置环境变量

vim /etc/profile
export HADOOP_HOME=/home/hadoop/hadoop-2.6.4
export PATH=$HADOOP_HOME/bin:$PATH

Hadoop配置

配置文件放在$HADOOP_HOME/etc/hadoop/下
修改一下配置：
vim hadoop-env.sh
export JAVA_HOME=/opt/jdk1.8.0_40

vim yarn-env.sh
export JAVA_HOME=/opt/jdk1.8.0_40

vim slaves (这里没有了master配置文件)
hadoop1
hadoop2
hadoop3

vim core-site.xml

<configuration>
        <property>
                <name>hadoop.tmp.dir</name>
                <value>/home/hadoop/hadoop/tmp</value>
                <description>A base for other temporary directories.</description>
        </property>
        <property>
                <name>fs.defaultFS</name>
                <value>hdfs://hadoop0:9000</value>
        </property>
        <property>
                <name>io.file.buffer.size</name>
                <value>4096</value>
        </property>
</configuration>

vim hdfs-site.xml

<configuration>
        <property>
                <name>dfs.namenode.name.dir</name>
                <value>/home/hadoop/hadoop/name</value>
        </property>
        <property>
                <name>dfs.datanode.data.dir</name>
                <value>/home/hadoop/hadoop/data</value>
        </property>
        <property>
                <name>dfs.replication</name>
                <value>2</value>
        </property>
        <property>
                <name>dfs.nameservices</name>
                <value>hadoop0</value>
        </property>
        <property>
                <name>dfs.namenode.secondary.http-address</name>
                <value>hadoop0:50090</value>
        </property>
        <property>
                <name>dfs.webhdfs.enabled</name>
                <value>true</value>
        </property>
        <property>
                <name>dfs.permissions</name>
                <value>false</value>
        </property>
</configuration>

cp mapred-site.xml.template mapred-site.xml

vim mapred-site.xml

<configuration>
        <property>
                <name>mapreduce.framework.name</name>
                <value>yarn</value>
                <final>true</final>
        </property>
        <property>
                <name>mapreduce.jobtracker.http.address</name>
                <value>hadoop0:50030</value>
        </property>
        <property>
                <name>mapreduce.jobhistory.address</name>
                <value>hadoop0:10020</value>
        </property>
        <property>
                <name>mapreduce.jobhistory.webapp.address</name>
                <value>hadoop0:19888</value>
        </property>
        <property>
                <name>mapred.job.tracker</name>
                <value>hadoop0:9001</value>
        </property>
</configuration>

vim yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
        <property>
                <name>yarn.resourcemanager.hostname</name>
                <value>hadoop0</value>
        </property>
        <property>
                <name>yarn.nodemanager.aux-services</name>
                <value>mapreduce_shuffle</value>
        </property>
        <property>
                <name>yarn.resourcemanager.address</name>
                <value>hadoop0:8032</value>
        </property>
        <property>
                <name>yarn.resourcemanager.scheduler.address</name>
                <value>hadoop0:8030</value>
        </property>
        <property>
                <name>yarn.resourcemanager.resource-tracker.address</name>
                <value>hadoop0:8031</value>
        </property>
        <property>
                <name>yarn.resourcemanager.admin.address</name>
                <value>hadoop0:8033</value>
        </property>
        <property>
                <name>yarn.resourcemanager.webapp.address</name>
                <value>hadoop0:8088</value>
        </property>
        <property>
                <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
                <value>org.apache.hadoop.mapred.ShuffleHandler</value>
        </property>
</configuration>

复制到其它节点中
[hadoop@hadoop0 ~]$ scp -r hadoop-2.6.4 hadoop?:~/

格式化文件系统
namenode格式化文件系统
$hadoop namenode -format
hadoop命令在~/hadoop-2.6.2/bin中

验证安装

启动进程
[hadoop@hadoop0 hadoop-2.6.4]$ sbin/hadoop-daemon.sh start namenode

[hadoop@hadoop0 hadoop-2.6.4]$ sbin/hadoop-daemon.sh start datanode

或者一次性启动
[hadoop@hadoop0 hadoop-2.6.4]$ sbin/start-all.sh

检查节点配置情况
hadoop dfsadmin -report
错误情况：
可能配置tag错误；
拒绝连接，关闭防火墙

[hadoop@hadoop0 hadoop-2.6.4]$ jps
4272 ResourceManager
4032 NameNode
4534 Jps

关闭
[hadoop@hadoop0 hadoop-2.6.4]$ sbin/stop-all.sh

网页节点管理
http://192.168.248.150:8088/cluster

网页资源管理
http://192.168.248.150:50070/dfshealth.html#tab-overview

编译安装Hadoop

参考：
http://blog.csdn.net/yaoxtao/article/details/49488181
http://www.cnblogs.com/hanganglin/p/4349919.html

问题

Apache官网上提供的Hadoop本地库是32位的，如果我们的Linux服务器是64位的话，就会现问题。

我们在64位服务器执行Hadoop命令时，则会报以下错误：

WARNutil.NativeCodeLoader: Unable to load native-hadoop library for yourplatform... using builtin-Java classes where applicable

为了解决上述问题，我们就需要自己编译一个64位的hadoop版本。

编译hadoop2.6.1需要的软件

yum install gcc
yum install cmake
yum install gcc-c++

安装maven

wget http://www-eu.apache.org/dist/maven/maven-3/3.3.9/binaries/apache-maven-3.3.9-bin.tar.gz
安装maven：
参考： http://www.blogjava.net/caojianhua/archive/2011/04/02/347559.html

tar xvf apache-maven-3.3.9-bin.tar.gz
mv apache-maven-3.3.9/ /usr/local/
vim /etc/profile
export MAVEN_HOME=/usr/local/apache-maven-3.3.9
export PATH=$PATH:$MAVEN_HOME/bin

source /etc/profile

[root@hadoop0 hadoop]# mvn -v
Apache Maven 3.3.9 (bb52d8502b132ec0a5a3f4c09453c07478323dc5; 2015-11-11T00:41:47+08:00)
Maven home: /usr/local/apache-maven-3.3.9
Java version: 1.8.0_40, vendor: Oracle Corporation
Java home: /opt/jdk1.8.0_40/jre
Default locale: zh_CN, platform encoding: UTF-8
OS name: "linux", version: "2.6.32-504.el6.x86_64", arch: "amd64", family: "unix"

安装protobuf

要求版本protobuf-2.5.0
wget https://github.com/google/protobuf/releases/download/v2.5.0/protobuf-2.5.0.tar.gz

cd protobuf-2.5.0/
./configure -prefix=/usr/local/protobuf-2.5.0
make && make install

vim /etc/profile
export PROTOBUF=/usr/local/protobuf-2.5.0
export PATH=PROTOBUF/bin:PATH

protoc –version

安装ant

wget http://www-eu.apache.org/dist//ant/binaries/apache-ant-1.9.7-bin.tar.gz

tar zxf apache-ant-1.9.7-bin.tar.gz
mv apache-ant-1.9.7/ /usr/local/
vim /etc/profile
export ANT_HOME=/usr/local/apache-ant-1.9.7
export PATH=$PATH:$ANT_HOME/bin

 source /etc/profile

yum install autoconf automake libtool
yum install openssl-devel

安装findbugs
http://findbugs.sourceforge.net/downloads.html
vim /etc/profile

export FINDBUGS_HOME=/usr/local/findbugs-3.0.1/
export PATH=$FINDBUGS_HOME/bin:$PATH

编译安装hadoop

wget http://www.apache.org/dyn/closer.cgi/hadoop/common/hadoop-2.6.4/hadoop-2.6.4-src.tar.gz

tar zxf hadoop-2.6.4-src.tar.gz
cd hadoop-2.6.4-src/

more BUILDING.txt
查看如何编译安装

mvn package -DskipTests -Pdist,native,docs，其中docs根据需要添加。
or
mvn clean package -Pdist,native -DskipTests -Dtar
编译过程中，需要下载很多包，等待时间比较长。当看到hadoop各个项目都编译成功,即出现一系列的SUCCESS之后，即为编译成功。

编译大概需要二三十分钟，看到一堆的SUCCESS，说明编译成功，编译后的项目在hadoop-2.6.0-src/hadoop-dist/target/hadoop-2.6.0中。

　只需要将编译后项目中的/hadoop-dist/lib/native文件夹覆盖至之前32位的项目中即可（当然整个项目覆盖也可以），并在配置文件$HADOOP_HOME/etc/hadoop/hadoop-env.sh末尾添加：export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib:$HADOOP_HOME/lib/native"。

编译过程中需要下载安装包，有时候可能由于网络的原因，导致安装包下载不完整，而出现编译错误。

可能错误

错误1：

Remote host closed connection during handshake: SSL peer shut down incorrectly.......

解决方案:需要重新新多编译几次即可通过。

mvn package -Pdist,native -DskipTests -Dtar

错误2：

[ERROR] Failed to execute goal org.apache.maven.plugins:maven-javadoc-plugin:2.8.1:jar (module-javadocs) on project hadoop-annotations: MavenReportException: Error while creating archive:
[ERROR] Exit code: 1 - /home/hadoop/hadoop-2.6.4-src/hadoop-common-project/hadoop-annotations/src/main/java/org/apache/hadoop/classification/InterfaceStability.java:27: 错误: 意外的结束标记:
[ERROR] *
[ERROR] ^
[ERROR]
[ERROR] Command line was: /opt/jdk1.8.0_40/jre/../bin/javadoc @options @packages
[ERROR]
[ERROR] Refer to the generated Javadoc files in ‘/home/hadoop/hadoop-2.6.4-src/hadoop-common-project/hadoop-annotations/target’ dir.
[ERROR] -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoExecutionException
[ERROR]
[ERROR] After correcting the problems, you can resume the build with the command
[ERROR] mvn -rf :hadoop-annotations

更换jdk1.7
http://www.oracle.com/technetwork/java/javase/downloads/java-archive-downloads-javase7-521261.html#jdk-7u80-oth-JPR
tar zxf jdk-7u80-linux-x64.gz
mv jdk1.7.0_80/ /opt/
vim /etc/profile

错误3：

[ERROR] Failed to execute goal org.apache.hadoop:hadoop-maven-plugins:2.6.4:protoc (compile-protoc) on project hadoop-common: org.apache.maven.plugin.MojoExecutionException: protoc version is ‘libprotoc 2.6.1’, expected version is ‘2.5.0’ -

protocbuf版本不对，下2.5.0
wget http://pan.baidu.com/s/1pJlZubT
cd protobuf-2.5.0
./configure –prefix=/usr/local/protobuf-2.5.0/
make
make install
vim /etc/profile
export PATH=$PATH:/usr/local/protobuf-2.5.0/bin

错误4：

[ERROR] Failed to execute goal org.codehaus.mojo.jspc:jspc-maven-plugin:2.0-alpha-3:compile (hdfs) on project hadoop-hdfs: Execution hdfs of goal org.codehaus.mojo.jspc:jspc-maven-plugin:2.0-alpha-3:compile failed: Plugin org.codehaus.mojo.jspc:jspc-maven-plugin:2.0-alpha-3 or one of its dependencies could not be resolved: The following artifacts could not be resolved: tomcat:jasper-compiler-jdt:jar:5.5.15, org.eclipse.jdt:core:jar:3.1.1: Could not transfer artifact tomcat:jasper-compiler-jdt:jar:5.5.15 from/to central (https://repo.maven.apache.org/maven2): GET request of: tomcat/jasper-compiler-jdt/5.5.15/jasper-compiler-jdt-5.5.15.jar from central failed: Connection reset -> [Help 1]

mvn包缺少，可以自己到https://repo.maven.apache.org/maven2/tomcat/jasper-compiler-jdt/5.5.15/
下载，放入~/.m2/指定目录

mvn package -Pdist,native -DskipTests -Dtar -e -X

编译完成

[INFO] hadoop-yarn-server-nodemanager ..................... SUCCESS [04:57 min]
[INFO] hadoop-yarn-server-web-proxy ....................... SUCCESS [  7.926 s]
[INFO] hadoop-yarn-server-applicationhistoryservice ....... SUCCESS [ 11.552 s]
[INFO] hadoop-yarn-server-resourcemanager ................. SUCCESS [ 37.191 s]
[INFO] hadoop-yarn-server-tests ........................... SUCCESS [ 11.227 s]
[INFO] hadoop-yarn-client ................................. SUCCESS [ 11.344 s]
[INFO] hadoop-yarn-applications ........................... SUCCESS [  0.236 s]
[INFO] hadoop-yarn-applications-distributedshell .......... SUCCESS [  6.616 s]
[INFO] hadoop-yarn-applications-unmanaged-am-launcher ..... SUCCESS [  3.877 s]
[INFO] hadoop-yarn-site ................................... SUCCESS [  0.171 s]
[INFO] hadoop-yarn-registry ............................... SUCCESS [ 10.513 s]
[INFO] hadoop-yarn-project ................................ SUCCESS [ 10.549 s]
[INFO] hadoop-mapreduce-client ............................ SUCCESS [  0.274 s]
[INFO] hadoop-mapreduce-client-core ....................... SUCCESS [ 37.510 s]
[INFO] hadoop-mapreduce-client-common ..................... SUCCESS [ 26.697 s]
[INFO] hadoop-mapreduce-client-shuffle .................... SUCCESS [  8.445 s]
[INFO] hadoop-mapreduce-client-app ........................ SUCCESS [ 16.746 s]
[INFO] hadoop-mapreduce-client-hs ......................... SUCCESS [ 14.682 s]
[INFO] hadoop-mapreduce-client-jobclient .................. SUCCESS [02:22 min]
[INFO] hadoop-mapreduce-client-hs-plugins ................. SUCCESS [  4.852 s]
[INFO] Apache Hadoop MapReduce Examples ................... SUCCESS [  9.098 s]
[INFO] hadoop-mapreduce ................................... SUCCESS [  8.473 s]
[INFO] Apache Hadoop MapReduce Streaming .................. SUCCESS [ 44.417 s]
[INFO] Apache Hadoop Distributed Copy ..................... SUCCESS [ 56.786 s]
[INFO] Apache Hadoop Archives ............................. SUCCESS [  5.743 s]
[INFO] Apache Hadoop Rumen ................................ SUCCESS [  9.956 s]
[INFO] Apache Hadoop Gridmix .............................. SUCCESS [  8.721 s]
[INFO] Apache Hadoop Data Join ............................ SUCCESS [  6.602 s]
[INFO] Apache Hadoop Ant Tasks ............................ SUCCESS [  4.001 s]
[INFO] Apache Hadoop Extras ............................... SUCCESS [  6.550 s]
[INFO] Apache Hadoop Pipes ................................ SUCCESS [ 16.753 s]
[INFO] Apache Hadoop OpenStack support .................... SUCCESS [  9.256 s]
[INFO] Apache Hadoop Amazon Web Services support .......... SUCCESS [06:50 min]
[INFO] Apache Hadoop Client ............................... SUCCESS [ 15.419 s]
[INFO] Apache Hadoop Mini-Cluster ......................... SUCCESS [  0.856 s]
[INFO] Apache Hadoop Scheduler Load Simulator ............. SUCCESS [ 10.593 s]
[INFO] Apache Hadoop Tools Dist ........................... SUCCESS [ 22.169 s]
[INFO] Apache Hadoop Tools ................................ SUCCESS [  0.118 s]
[INFO] Apache Hadoop Distribution ......................... SUCCESS [01:20 min]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 03:01 h
[INFO] Finished at: 2016-07-23T11:25:52+08:00
[INFO] Final Memory: 90M/237M
[INFO] ------------------------------------------------------------------------

在hadoop-dist/target/ 已经生成了可执行文件，再次执行之前的配置hadoop的方法即可
复制之前的配置的时候用nano编辑

[hadoop@hadoop0 hadoop-2.6.4]$ sbin/start-all.sh 
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [hadoop0]
hadoop0: starting namenode, logging to /home/hadoop/hadoop-2.6.4/logs/hadoop-hadoop-namenode-hadoop0.out
hadoop2: starting datanode, logging to /home/hadoop/hadoop-2.6.4/logs/hadoop-hadoop-datanode-hadoop2.out
hadoop1: starting datanode, logging to /home/hadoop/hadoop-2.6.4/logs/hadoop-hadoop-datanode-hadoop1.out
hadoop3: starting datanode, logging to /home/hadoop/hadoop-2.6.4/logs/hadoop-hadoop-datanode-hadoop3.out
starting yarn daemons
starting resourcemanager, logging to /home/hadoop/hadoop-2.6.4/logs/yarn-hadoop-resourcemanager-hadoop0.out
hadoop3: starting nodemanager, logging to /home/hadoop/hadoop-2.6.4/logs/yarn-hadoop-nodemanager-hadoop3.out
hadoop2: starting nodemanager, logging to /home/hadoop/hadoop-2.6.4/logs/yarn-hadoop-nodemanager-hadoop2.out
hadoop1: starting nodemanager, logging to /home/hadoop/hadoop-2.6.4/logs/yarn-hadoop-nodemanager-hadoop1.out

开发

eclipse插件

下载hadoop-eclipse-plugin-2.6.4.jar
放入hadoop/plugins/

解压缩hadoop-2.6.4.tar.gz到D:\develop\hadoop-2.6.4，在eclipse的Windows->Preferences的Hadoop Map/Reduce中设置安装目录。

打开Windows->Open Perspective中的Map/Reduce，在此perspective下进行hadoop程序开发。

打开Windows->Show View中的Map/Reduce Locations，选择New Hadoop location…新建hadoop连接。
Map/Reduce(V2)Master和DFS Master的Host、Port分别为：
mapred-site.xml和core-site.xml中配置的地址及端口

配置Advanced parameters
设置参数hadoop.tmp.dir为core-site.xml中的配置

连接出现错误

An internal error occurred during: “Map/Reduce location status updater”.
java.lang.NullPointerException

“NullPointerException” is just Because you don’t have any directory in your hdfs.
Try that to build a directory:

hdfs dfs -mkdir -p input

测试：

hadoop fs -put ./myTest*.txt input

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马里奥是站在游戏界顶峰的超人气多面角色。马里奥靠吃蘑菇成长，特征是大鼻子、头戴帽子、身穿背带裤，还留着胡子。与他的双胞胎兄弟路易基一起，长年担任任天堂的招牌角色。

Nacos

Nacos /nɑ:kəʊs/ 是 Dynamic Naming and Configuration Service 的首字母简称，一个易于构建 AI Agent 应用的动态服务发现、配置管理和AI智能体管理平台。Nacos 致力于帮助您发现、配置和管理微服务及AI智能体应用。Nacos 提供了一组简单易用的特性集，帮助您快速实现动态服务发现、服务配置、服务元数据、流量管理。Nacos 帮助您更敏捷和容易地构建、交付和管理微服务平台。

Rocky Linux

Rocky Linux（中文名：洛基）是由Gregory Kurtzer于2020年12月发起的企业级Linux发行版，作为CentOS稳定版停止维护后与RHEL（Red Hat Enterprise Linux）完全兼容的开源替代方案，由社区拥有并管理，支持x86_64、aarch64等架构。其通过重新编译RHEL源代码提供长期稳定性，采用模块化包装和SELinux安全架构，默认包含GNOME桌面环境及XFS文件系统，支持十年生命周期更新。

Sublime Text

Sublime Text具有漂亮的用户界面和强大的功能，例如代码缩略图，Python的插件，代码段等。还可自定义键绑定，菜单和工具栏。Sublime Text 的主要功能包括：拼写检查，书签，完整的 Python API ， Goto 功能，即时项目切换，多选择，多窗口等等。Sublime Text 是一个跨平台的编辑器，同时支持Windows、Linux、Mac OS X等操作系统。