1-hadoop-1.03单节点的安装

1）确认安装了JDK,没有如下安装

[root@primary ~]# cd /home

[root@primary home]# cp jdk-6u31-linux-i586-rpm.bin /usr/local/

[root@primary home]# cd /usr/local/

[root@primary local]# chmod +x jdk-6u31-linux-i586-rpm.bin

[root@primary local]# ./jdk-6u31-linux-i586-rpm.bin

Press Enter to continue.....

[root@primary local]#

[root@primary local]# chmod +x jdk-6u31-linux-i586.rpm

[root@primary local]# rpm -ivh jdk-6u31-linux-i586.rpm

[root@primary ~]# vi /etc/profile

export JAVA_HOME=/usr/java/jdk1.6.0_31

export PATH=$JAVA_HOME/bin:$PATH

export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

source /etc/profile

[root@primary ~]# java -version

java version "1.6.0_31"

Java(TM) SE Runtime Environment (build 1.6.0_31-b04)

Java HotSpot(TM) Client VM (build 20.6-b01, mixed mode, sharing)

我用来安装的用户为hadoop

2、建立ssh无密码登录

删除了机器上所有的认证文件

[hadoop@primary ~]$ rm ~/.ssh/*

[hadoop@primary ~]$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa

Generating public/private dsa key pair.

Your identification has been saved in /home/hadoop/.ssh/id_dsa.

Your public key has been saved in /home/hadoop/.ssh/id_dsa.pub.

The key fingerprint is:

8b:db:12:21:57:1c:25:32:d9:4d:4d:16:98:6b:66:88 hadoop@primary

[hadoop@primary ~]$ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys

ssh对文件的权限要求

[hadoop@primary ~]$ chmod 644 ~/.ssh/authorized_keys

[hadoop@primary ~]$

[hadoop@primary ~]$ ssh localhost

rsync 默认安装了

[hadoop@primary ~]$ rsync --version

rsync version 2.6.3 protocol version 28

<http://rsync.samba.org/>

Capabilities: 64-bit files, socketpairs, hard links, symlinks, batchfiles,

inplace, IPv6, 64-bit system inums, 64-bit internal inums

rsync comes with ABSOLUTELY NO WARRANTY. This is free software, and you

are welcome to redistribute it under certain conditions. See the GNU

General Public Licence for details

4）安装HADOOP

[root@primary home]# chmod 777 hadoop-1.0.4-bin.tar.gz

[hadoop@primary home]$ tar xzvf hadoop-1.0.4-bin.tar.gz

进入HADOOP解压的目录

[hadoop@primary home]$ cd hadoop

查看JAVA—HOME

[hadoop@primary ~]$ env |grep JAVA

JAVA_HOME=/usr/java/jdk1.6.0_31

我在根目录下创建了一个文件。如下操作的

chown -R hadoop:root /hadoop

-bash-3.00$ id

uid=503(hadoop) gid=505(hadoop) groups=0(root),505(hadoop)

-bash-3.00$ tar xzvf hadoop-1.0.4-bin.tar.gz

-bash-3.00$ pwd

/hadoop/hadoop-1.0.4

-bash-3.00$ vi conf/hadoop-env.sh

在 conf/hadoop-env.sh 中配置 Java 环境

配置conf/core-site.xml HDFS 地址和端口

hadoop@station1 hadoop-1.0.3]$ cat conf/core-site.xml

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<name>fs.default.name</name>

<value>hdfs://station1:9000</value>

</property>

<value>/hadoop/web/data/</value>

</property>

<value>/hadoop/web/tem/</value>

</property>

<value>/hadoop/web/name/</value>

</property>

</configuration>

配置hdfs-site.xml replication

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<name>dfs.replication</name>

</property>

<value>/hadoop/web/data/</value>

</property>

<value>/hadoop/web/tem/</value>

</property>

<value>/hadoop/web/name/</value>

</property>

</configuration>

配置 conf/mapred-site.xml

[hadoop@station1 hadoop-1.0.3]$ cat conf/mapred-site.xml

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<name>mapred.job.tracker</name>

<value>localhost:9001</value>

</property>

</configuration>

mapred-queue-acls.xml mapred-site.xml masters

[cloud@station1 conf]$ vi mapred-site.xml

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<name>mapred.job.tracker</name>

<value>station1:9001</value>

</property>

</configuration>

运行hadoop，进入bin

（1）格式化文件系统

hadoop namenode – format

-bash-3.00$ ./bin/hadoop - format

Unrecognized option: -

Could not create the Java virtual machine.

报错了。命令错了。

[hadoop@primary hadoop-1.0.4]$ ./bin/hadoop namenode -format

12/10/25 16:53:38 INFO namenode.NameNode: STARTUP_MSG:

/************************************************************

STARTUP_MSG: Starting NameNode

STARTUP_MSG: host = primary/192.168.26.83

STARTUP_MSG: args = [-format]

STARTUP_MSG: version = 1.0.4

STARTUP_MSG: build = https://svn.apache.org/repos/asf/hadoop/common/branches/branch-1.0 -r 1393290; compiled by 'hortonfo' on Wed Oct 3 05:13:58 UTC 2012

************************************************************/

12/10/25 16:53:39 INFO util.GSet: VM type = 32-bit

12/10/25 16:53:39 INFO util.GSet: 2% max memory = 19.33375 MB

12/10/25 16:53:39 INFO util.GSet: capacity = 2^22 = 4194304 entries

12/10/25 16:53:39 INFO util.GSet: recommended=4194304, actual=4194304

12/10/25 16:53:39 INFO namenode.FSNamesystem: fsOwner=hadoop

12/10/25 16:53:39 INFO namenode.FSNamesystem: supergroup=supergroup

12/10/25 16:53:39 INFO namenode.FSNamesystem: isPermissionEnabled=true

12/10/25 16:53:39 INFO namenode.FSNamesystem: dfs.block.invalidate.limit=100

12/10/25 16:53:39 INFO namenode.FSNamesystem: isAccessTokenEnabled=false accessKeyUpdateInterval=0 min(s), accessTokenLifetime=0 min(s)

12/10/25 16:53:39 INFO namenode.NameNode: Caching file names occuring more than 10 times

12/10/25 16:53:39 INFO common.Storage: Image file of size 112 saved in 0 seconds.

12/10/25 16:53:39 INFO common.Storage: Storage directory /tmp/hadoop-hadoop/dfs/name has been successfully formatted.

12/10/25 16:53:39 INFO namenode.NameNode: SHUTDOWN_MSG:

/************************************************************

SHUTDOWN_MSG: Shutting down NameNode at primary/192.168.26.83

************************************************************/

（2）启动hadoop

start-all.sh

[hadoop@primary hadoop-1.0.4]$ cd bin

[hadoop@primary bin]$ pwd

/hadoop/hadoop-1.0.4/bin

[hadoop@primary bin]$ ./start-all.sh

namenode running as process 7387. Stop it first.

localhost: starting datanode, logging to /hadoop/hadoop-1.0.4/libexec/../logs/hadoop-hadoop-datanode-primary.out

localhost: starting secondarynamenode, logging to /hadoop/hadoop-1.0.4/libexec/../logs/hadoop-hadoop-secondarynamenode-primary.out

starting jobtracker, logging to /hadoop/hadoop-1.0.4/libexec/../logs/hadoop-hadoop-jobtracker-primary.out

localhost: starting tasktracker, logging to /hadoop/hadoop-1.0.4/libexec/../logs/hadoop-hadoop-tasktracker-primary.out

（3）查看进程

jps

（4）查看集群状态

hadoop dfsadmin -report

web 方式查看：http://localhost:50070 http://localhost:50030

但没想到的是按网上的步骤配置后datanode节点怎么也没办法启动。后来通过分析启动日志后发现fs.data.dir参数设置的目录权限必需为755，要不启动datanode节点启动就会因为权限检测错误而自动关闭。提示信息如下：

WARN org.apache.hadoop.hdfs.server.datanode.DataNode: Invalid directory in dfs.data.dir: Incorrect permission for /data/hadoop/disk, expected: rwxr-xr-x, while actual: rwxrwxrwx
RROR org.apache.hadoop.hdfs.server.datanode.DataNode: All directories in dfs.data.dir are invalid.

源文档 <http://gghandsome.blog.51cto.com/398804/822983>

5）测试向DATANODE 添加文件

[hadoop@primary bin]$ pwd

/hadoop/hadoop-1.0.4/bin

[hadoop@primary bin]$ hadoop fs -put slaves.sh hdfs://localhost:9000/

Warning: $HADOOP_HOME is deprecated.

[hadoop@primary bin]$

6）测试MapReduce

创建目录

[hadoop@primary bin]$ hadoop fs -mkdir hdfs://localhost:9000/input/

放入文件

[hadoop@primary bin]$ hadoop fs -put *.sh /input/

计算这个SH文件里的单词数量（注意这个目录在hadoop 的目录，不在BIN目录）

[hadoop@station1 hadoop-1.0.3]$ bin/hadoop jar hadoop-examples-1.0.3.jar wordcount /input /out

Warning: $HADOOP_HOME is deprecated.

12/10/29 15:00:55 INFO input.FileInputFormat: Total input paths to process : 14

12/10/29 15:00:55 INFO util.NativeCodeLoader: Loaded the native-hadoop library

12/10/29 15:00:55 WARN snappy.LoadSnappy: Snappy native library not loaded

12/10/29 15:00:56 INFO mapred.JobClient: Running job: job_201210291430_0002

12/10/29 15:00:57 INFO mapred.JobClient: map 0% reduce 0%

12/10/29 15:01:10 INFO mapred.JobClient: map 14% reduce 0%

12/10/29 15:01:19 INFO mapred.JobClient: map 28% reduce 0%

12/10/29 15:01:28 INFO mapred.JobClient: map 42% reduce 9%

12/10/29 15:01:34 INFO mapred.JobClient: map 57% reduce 9%

12/10/29 15:01:37 INFO mapred.JobClient: map 57% reduce 14%

12/10/29 15:01:40 INFO mapred.JobClient: map 71% reduce 14%

12/10/29 15:01:43 INFO mapred.JobClient: map 71% reduce 19%

12/10/29 15:01:47 INFO mapred.JobClient: map 85% reduce 19%

12/10/29 15:01:53 INFO mapred.JobClient: map 100% reduce 23%

12/10/29 15:02:00 INFO mapred.JobClient: map 100% reduce 28%

12/10/29 15:02:06 INFO mapred.JobClient: map 100% reduce 100%

12/10/29 15:02:11 INFO mapred.JobClient: Job complete: job_201210291430_0002

12/10/29 15:02:11 INFO mapred.JobClient: Counters: 29

12/10/29 15:02:11 INFO mapred.JobClient: Job Counters

12/10/29 15:02:11 INFO mapred.JobClient: Launched reduce tasks=1

12/10/29 15:02:11 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=87869

12/10/29 15:02:11 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0

12/10/29 15:02:11 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0

12/10/29 15:02:11 INFO mapred.JobClient: Launched map tasks=14

12/10/29 15:02:11 INFO mapred.JobClient: Data-local map tasks=14

12/10/29 15:02:11 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=55240

12/10/29 15:02:11 INFO mapred.JobClient: File Output Format Counters

12/10/29 15:02:11 INFO mapred.JobClient: Bytes Written=6173

12/10/29 15:02:11 INFO mapred.JobClient: FileSystemCounters

12/10/29 15:02:11 INFO mapred.JobClient: FILE_BYTES_READ=28724

12/10/29 15:02:11 INFO mapred.JobClient: HDFS_BYTES_READ=23858

12/10/29 15:02:11 INFO mapred.JobClient: FILE_BYTES_WRITTEN=381199

12/10/29 15:02:11 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=6173

12/10/29 15:02:11 INFO mapred.JobClient: File Input Format Counters

12/10/29 15:02:11 INFO mapred.JobClient: Bytes Read=22341

12/10/29 15:02:11 INFO mapred.JobClient: Map-Reduce Framework

12/10/29 15:02:11 INFO mapred.JobClient: Map output materialized bytes=28802

12/10/29 15:02:11 INFO mapred.JobClient: Map input records=691

12/10/29 15:02:11 INFO mapred.JobClient: Reduce shuffle bytes=28802

12/10/29 15:02:11 INFO mapred.JobClient: Spilled Records=4018

12/10/29 15:02:11 INFO mapred.JobClient: Map output bytes=34161

12/10/29 15:02:11 INFO mapred.JobClient: Total committed heap usage (bytes)=2264064000

12/10/29 15:02:11 INFO mapred.JobClient: CPU time spent (ms)=9340

12/10/29 15:02:11 INFO mapred.JobClient: Combine input records=3137

12/10/29 15:02:11 INFO mapred.JobClient: SPLIT_RAW_BYTES=1517

12/10/29 15:02:11 INFO mapred.JobClient: Reduce input records=2009

12/10/29 15:02:11 INFO mapred.JobClient: Reduce input groups=497

12/10/29 15:02:11 INFO mapred.JobClient: Combine output records=2009

12/10/29 15:02:11 INFO mapred.JobClient: Physical memory (bytes) snapshot=1989103616

12/10/29 15:02:11 INFO mapred.JobClient: Reduce output records=497

12/10/29 15:02:11 INFO mapred.JobClient: Virtual memory (bytes) snapshot=5140561920

12/10/29 15:02:11 INFO mapred.JobClient: Map output records=3137

下面是上传文件文件的统计

[hadoop@station1 bin]$ grep apache *.sh|wc

14 28 915

hadoop 统计结果如下

查看的路径（因为面页太大了。我只显视了一部分）

结果

查看运行任务

集群的安装请参考：http://pftzzg.iteye.com/blog/1910171

hadoop-0.20 请参考：http://pftzzg.iteye.com/admin/blogs/1911023

1.03 请参考：http://pftzzg.iteye.com/admin/blogs/1910153

1-hadoop-1.03单节点的安装

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