`
sjsky
  • 浏览: 913516 次
  • 性别: Icon_minigender_1
  • 来自: 上海
社区版块
存档分类
最新评论

Hadoop初试

阅读更多
   blog迁移至 :http://www.micmiu.com

       Hadoop一个分布式系统基础架构,是Apache基金下的一个子项目。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高速运算和存储。Hadoop实现了一个分布式文件系统(Hadoop Distributed File System),简称HDFS。HDFS有着高容错性的特点,并且设计用来部署在低廉的(low-cost)硬件上。而且它提供高传输率(high throughput)来访问应用程序的数据,适合那些有着超大数据集(large data set)的应用程序。HDFS放宽了(relax)POSIX的要求(requirements)这样可以流的形式访问(streaming access)文件系统中的数据。

      Hadoop官网:http://hadoop.apache.org/


    本文详细介绍如何搭建一个Hadoop的测试环境,将分别从单机、伪分布式等逐个讲解,并讲述在不同操作系统(Centos、Ubuntu)搭建过程中可能碰到的问题及解决方法,所有的测试过程本人在Centos、Ubuntu下均全部测试成功,全文的目录结构:
  • 实验环境
  • 准备工作
  • 单机演示
  • 伪分布式演示
一、实验环境:
  • Windows Vista
  • VirtualBox + Ubuntu10.10(OpenSSH 安装并启动)
  • jdk 版本:1.6.0_20;安装路径为:/opt/jdk1.6(Hadoop要求jdk1.6.x)
  • hadoop-0.20.203.0rc1.tar.gz(目前最新的稳定版本)

以Ubuntu中的用户 michael为例:
二、前期准备
首先将hadoop-0.20.203.0rc1.tar.gz解压到/home/michael/下
$tar -zxvf hadoop-0.20.203.0rc1.tar.gz -C /home/michael/
$mv hadoop-0.20.203.0 hadoop

修改hadoop-env.sh中JAVA_HOME的配置,找到如下信息:
引用
# The java implementation to use.  Required.
# export JAVA_HOME=/usr/lib/j2sdk1.5-sun

修改为:
引用
# The java implementation to use.  Required.
#当前系统的JDK的路径
export JAVA_HOME=/opt/jdk1.6


三、单机演示(Standalone Operation)
所涉及的到的操作命令如下:
$ cd /home/michael/hadoop
$ mkdir input 
$ cp conf/*.xml input 
$ bin/hadoop jar hadoop-examples-*.jar grep input output 'dfs[a-z.]+' 
$ cat output/*

详细过程如下:
引用
michael@michael-VirtualBox:~/hadoop$ mkdir input
michael@michael-VirtualBox:~/hadoop$ cp conf/*.xml input
michael@michael-VirtualBox:~/hadoop$ bin/hadoop jar hadoop-examples-0.20.203.0.jar grep input output 'dfs[a-z.]+'
11/07/16 10:06:48 INFO mapred.FileInputFormat: Total input paths to process : 6
11/07/16 10:06:48 INFO mapred.JobClient: Running job: job_local_0001
11/07/16 10:06:48 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:06:48 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:06:49 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:06:49 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:06:49 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:06:49 INFO mapred.JobClient:  map 0% reduce 0%
11/07/16 10:06:49 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
11/07/16 10:06:51 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/capacity-scheduler.xml:0+7457
11/07/16 10:06:51 INFO mapred.Task: Task 'attempt_local_0001_m_000000_0' done.
11/07/16 10:06:51 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:06:51 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:06:51 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:06:51 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:06:51 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:06:52 INFO mapred.MapTask: Finished spill 0
11/07/16 10:06:52 INFO mapred.Task: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
11/07/16 10:06:52 INFO mapred.JobClient:  map 100% reduce 0%
11/07/16 10:06:54 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/hadoop-policy.xml:0+4644
11/07/16 10:06:54 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/hadoop-policy.xml:0+4644
11/07/16 10:06:54 INFO mapred.Task: Task 'attempt_local_0001_m_000001_0' done.
11/07/16 10:06:54 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:06:54 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:06:55 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:06:55 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:06:55 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:06:55 INFO mapred.Task: Task:attempt_local_0001_m_000002_0 is done. And is in the process of commiting
11/07/16 10:06:57 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/mapred-queue-acls.xml:0+2033
11/07/16 10:06:57 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/mapred-queue-acls.xml:0+2033
11/07/16 10:06:57 INFO mapred.Task: Task 'attempt_local_0001_m_000002_0' done.
11/07/16 10:06:57 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:06:57 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:06:58 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:06:58 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:06:58 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:06:58 INFO mapred.Task: Task:attempt_local_0001_m_000003_0 is done. And is in the process of commiting
11/07/16 10:07:00 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/mapred-site.xml:0+178
11/07/16 10:07:00 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/mapred-site.xml:0+178
11/07/16 10:07:00 INFO mapred.Task: Task 'attempt_local_0001_m_000003_0' done.
11/07/16 10:07:00 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:07:00 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:07:01 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:07:01 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:07:01 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:07:01 INFO mapred.Task: Task:attempt_local_0001_m_000004_0 is done. And is in the process of commiting
11/07/16 10:07:04 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/core-site.xml:0+178
11/07/16 10:07:04 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/core-site.xml:0+178
11/07/16 10:07:04 INFO mapred.Task: Task 'attempt_local_0001_m_000004_0' done.
11/07/16 10:07:04 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:07:04 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:07:04 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:07:04 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:07:04 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:07:04 INFO mapred.Task: Task:attempt_local_0001_m_000005_0 is done. And is in the process of commiting
11/07/16 10:07:07 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/input/hdfs-site.xml:0+178
11/07/16 10:07:07 INFO mapred.Task: Task 'attempt_local_0001_m_000005_0' done.
11/07/16 10:07:07 INFO mapred.LocalJobRunner:
11/07/16 10:07:07 INFO mapred.Merger: Merging 6 sorted segments
11/07/16 10:07:07 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 21 bytes
11/07/16 10:07:07 INFO mapred.LocalJobRunner:
11/07/16 10:07:07 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
11/07/16 10:07:07 INFO mapred.LocalJobRunner:
11/07/16 10:07:07 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
11/07/16 10:07:07 INFO mapred.FileOutputCommitter: Saved output of task 'attempt_local_0001_r_000000_0' to file:/home/michael/hadoop/grep-temp-1267281521
11/07/16 10:07:10 INFO mapred.LocalJobRunner: reduce > reduce
11/07/16 10:07:10 INFO mapred.Task: Task 'attempt_local_0001_r_000000_0' done.
11/07/16 10:07:10 INFO mapred.JobClient:  map 100% reduce 100%
11/07/16 10:07:10 INFO mapred.JobClient: Job complete: job_local_0001
11/07/16 10:07:10 INFO mapred.JobClient: Counters: 17
11/07/16 10:07:10 INFO mapred.JobClient:   File Input Format Counters
11/07/16 10:07:10 INFO mapred.JobClient:     Bytes Read=14668
11/07/16 10:07:10 INFO mapred.JobClient:   File Output Format Counters
11/07/16 10:07:10 INFO mapred.JobClient:     Bytes Written=123
11/07/16 10:07:10 INFO mapred.JobClient:   FileSystemCounters
11/07/16 10:07:10 INFO mapred.JobClient:     FILE_BYTES_READ=1106074
11/07/16 10:07:10 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=1231779
11/07/16 10:07:10 INFO mapred.JobClient:   Map-Reduce Framework
11/07/16 10:07:10 INFO mapred.JobClient:     Map output materialized bytes=55
11/07/16 10:07:10 INFO mapred.JobClient:     Map input records=357
11/07/16 10:07:10 INFO mapred.JobClient:     Reduce shuffle bytes=0
11/07/16 10:07:10 INFO mapred.JobClient:     Spilled Records=2
11/07/16 10:07:10 INFO mapred.JobClient:     Map output bytes=17
11/07/16 10:07:10 INFO mapred.JobClient:     Map input bytes=14668
11/07/16 10:07:10 INFO mapred.JobClient:     SPLIT_RAW_BYTES=611
11/07/16 10:07:10 INFO mapred.JobClient:     Combine input records=1
11/07/16 10:07:10 INFO mapred.JobClient:     Reduce input records=1
11/07/16 10:07:10 INFO mapred.JobClient:     Reduce input groups=1
11/07/16 10:07:10 INFO mapred.JobClient:     Combine output records=1
11/07/16 10:07:10 INFO mapred.JobClient:     Reduce output records=1
11/07/16 10:07:10 INFO mapred.JobClient:     Map output records=1
11/07/16 10:07:10 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
11/07/16 10:07:10 INFO mapred.FileInputFormat: Total input paths to process : 1
11/07/16 10:07:10 INFO mapred.JobClient: Running job: job_local_0002
11/07/16 10:07:10 INFO mapred.MapTask: numReduceTasks: 1
11/07/16 10:07:10 INFO mapred.MapTask: io.sort.mb = 100
11/07/16 10:07:11 INFO mapred.MapTask: data buffer = 79691776/99614720
11/07/16 10:07:11 INFO mapred.MapTask: record buffer = 262144/327680
11/07/16 10:07:11 INFO mapred.MapTask: Starting flush of map output
11/07/16 10:07:11 INFO mapred.MapTask: Finished spill 0
11/07/16 10:07:11 INFO mapred.Task: Task:attempt_local_0002_m_000000_0 is done. And is in the process of commiting
11/07/16 10:07:11 INFO mapred.JobClient:  map 0% reduce 0%
11/07/16 10:07:13 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/grep-temp-1267281521/part-00000:0+111
11/07/16 10:07:13 INFO mapred.LocalJobRunner: file:/home/michael/hadoop/grep-temp-1267281521/part-00000:0+111
11/07/16 10:07:13 INFO mapred.Task: Task 'attempt_local_0002_m_000000_0' done.
11/07/16 10:07:13 INFO mapred.LocalJobRunner:
11/07/16 10:07:13 INFO mapred.Merger: Merging 1 sorted segments
11/07/16 10:07:13 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 21 bytes
11/07/16 10:07:13 INFO mapred.LocalJobRunner:
11/07/16 10:07:13 INFO mapred.Task: Task:attempt_local_0002_r_000000_0 is done. And is in the process of commiting
11/07/16 10:07:13 INFO mapred.LocalJobRunner:
11/07/16 10:07:13 INFO mapred.Task: Task attempt_local_0002_r_000000_0 is allowed to commit now
11/07/16 10:07:13 INFO mapred.FileOutputCommitter: Saved output of task 'attempt_local_0002_r_000000_0' to file:/home/michael/hadoop/output
11/07/16 10:07:14 INFO mapred.JobClient:  map 100% reduce 0%
11/07/16 10:07:16 INFO mapred.LocalJobRunner: reduce > reduce
11/07/16 10:07:16 INFO mapred.Task: Task 'attempt_local_0002_r_000000_0' done.
11/07/16 10:07:17 INFO mapred.JobClient:  map 100% reduce 100%
11/07/16 10:07:17 INFO mapred.JobClient: Job complete: job_local_0002
11/07/16 10:07:17 INFO mapred.JobClient: Counters: 17
11/07/16 10:07:17 INFO mapred.JobClient:   File Input Format Counters
11/07/16 10:07:17 INFO mapred.JobClient:     Bytes Read=123
11/07/16 10:07:17 INFO mapred.JobClient:   File Output Format Counters
11/07/16 10:07:17 INFO mapred.JobClient:     Bytes Written=23
11/07/16 10:07:17 INFO mapred.JobClient:   FileSystemCounters
11/07/16 10:07:17 INFO mapred.JobClient:     FILE_BYTES_READ=606737
11/07/16 10:07:17 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=700981
11/07/16 10:07:17 INFO mapred.JobClient:   Map-Reduce Framework
11/07/16 10:07:17 INFO mapred.JobClient:     Map output materialized bytes=25
11/07/16 10:07:17 INFO mapred.JobClient:     Map input records=1
11/07/16 10:07:17 INFO mapred.JobClient:     Reduce shuffle bytes=0
11/07/16 10:07:17 INFO mapred.JobClient:     Spilled Records=2
11/07/16 10:07:17 INFO mapred.JobClient:     Map output bytes=17
11/07/16 10:07:17 INFO mapred.JobClient:     Map input bytes=25
11/07/16 10:07:17 INFO mapred.JobClient:     SPLIT_RAW_BYTES=110
11/07/16 10:07:17 INFO mapred.JobClient:     Combine input records=0
11/07/16 10:07:17 INFO mapred.JobClient:     Reduce input records=1
11/07/16 10:07:17 INFO mapred.JobClient:     Reduce input groups=1
11/07/16 10:07:17 INFO mapred.JobClient:     Combine output records=0
11/07/16 10:07:17 INFO mapred.JobClient:     Reduce output records=1
11/07/16 10:07:17 INFO mapred.JobClient:     Map output records=1
michael@michael-VirtualBox:~/hadoop$

michael@michael-VirtualBox:~/hadoop$ cat output/*
1 dfsadmin
michael@michael-VirtualBox:~/hadoop$

到此单机演示成功。

四、伪分布式演示(Pseudo-Distributed Operation)

1. 修改配置文件:
conf/core-site.xml:
<configuration>
     <property>
         <name>fs.default.name</name>
         <value>hdfs://localhost:9000</value>
     </property>
</configuration>

conf/hdfs-site.xml:
<configuration>
     <property>
         <name>dfs.replication</name>
         <value>1</value>
     </property>
</configuration>

conf/mapred-site.xml:
<configuration>
     <property>
         <name>mapred.job.tracker</name>
         <value>localhost:9001</value>
     </property>
</configuration>


2.设置SSH无密码登陆
$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa 
$ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys 

ps:如果是Centos系统,有关SSH无密码的详细设置请看:Linux(Centos)配置OpenSSH无密码登陆

3.测试:
相关操作的基本命令如下:
#Format a new distributed-filesystem:
$ bin/hadoop namenode -format 

#Start the hadoop daemons:
$ bin/start-all.sh 
Copy the input files into the distributed filesystem:
$ bin/hadoop fs -put conf input 

#Run some of the examples provided:
$ bin/hadoop jar hadoop-examples-*.jar grep input output 'dfs[a-z.]+' 

#Copy the output files from the distributed filesystem to the local filesytem and examine them:
$ bin/hadoop fs -get output output 

$ cat output/output/* 


以上的测试操作在Centos5中测试顺利成功,而在Ubuntu10.10系统中却失败了,在执行命令:bin/hadoop fs -put conf input 时出错,错误信息类似“could only be replicated to 0 nodes, instead of 1”,引起该错误信息的原因有多种(详见:http://sjsky.iteye.com/blog/1124545),但此处的出错的原因是由于hadoop.tmp.dir默认配置指向/tmp/hadoop-${user.name},而在Ubuntu系统中,/tmp目录下的文件系统的类型往往是Hadoop不支持的。

解决的办法是重新定义hadoop.tmp.dir指向,修改配置文件conf/core-site.xml如下:
<configuration>
	<property>
		<name>fs.default.name</name>
		<value>hdfs://localhost:9000</value>
	</property>
	<property>
		<name>hadoop.tmp.dir</name>
		<value>/home/michael/hadooptmp/hadoop-${user.name}</value>
		<description>
			A base for other temporary directories.
		</description>
	</property>
</configuration>

再次进行测试,成功运行。
整个测试过程的详细信息如下:
引用
michael@michael-VirtualBox:~/hadoop$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa
Generating public/private dsa key pair.
Your identification has been saved in /home/michael/.ssh/id_dsa.
Your public key has been saved in /home/michael/.ssh/id_dsa.pub.
The key fingerprint is:
2a:47:e3:3a:c8:80:ab:97:d1:c6:68:54:9a:45:9f:59 michael@michael-VirtualBox
The key's randomart image is:
+--[ DSA 1024]----+
|   ..   E        |
|    o. +         |
|   =  +          |
|  +              |
|.. +  o S        |
|o + +o o         |
| = =. +          |
|. = .+           |
|o.  ..           |
+-----------------+
michael@michael-VirtualBox:~/hadoop$ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
michael@michael-VirtualBox:~/hadoop$ ssh localhost
Linux michael-VirtualBox 2.6.35-22-generic #33-Ubuntu SMP Sun Sep 19 20:34:50 UTC 2010 i686 GNU/Linux
Ubuntu 10.10

Welcome to Ubuntu!
* Documentation:  https://help.ubuntu.com/

71 packages can be updated.
71 updates are security updates.

New release 'natty' available.
Run 'do-release-upgrade' to upgrade to it.

Last login: Wed Jul 15 15:56:17 2011 from shnap.local
michael@michael-VirtualBox:~$ exit
注销
Connection to localhost closed.


michael@michael-VirtualBox:~/hadoop$ bin/hadoop namenode -format
11/07/16 12:43:45 INFO namenode.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG:   host = michael-VirtualBox/127.0.1.1
STARTUP_MSG:   args = [-format]
STARTUP_MSG:   version = 0.20.203.0
STARTUP_MSG:   build = http://svn.apache.org/repos/asf/hadoop/common/branches/branch-0.20-security-203 -r 1099333; compiled by 'oom' on Wed May  4 07:57:50 PDT 2011
************************************************************/
11/07/16 12:43:46 INFO util.GSet: VM type       = 32-bit
11/07/16 12:43:46 INFO util.GSet: 2% max memory = 19.33375 MB
11/07/16 12:43:46 INFO util.GSet: capacity      = 2^22 = 4194304 entries
11/07/16 12:43:46 INFO util.GSet: recommended=4194304, actual=4194304
11/07/16 12:43:46 INFO namenode.FSNamesystem: fsOwner=michael
11/07/16 12:43:46 INFO namenode.FSNamesystem: supergroup=supergroup
11/07/16 12:43:46 INFO namenode.FSNamesystem: isPermissionEnabled=true
11/07/16 12:43:46 INFO namenode.FSNamesystem: dfs.block.invalidate.limit=100
11/07/16 12:43:46 INFO namenode.FSNamesystem: isAccessTokenEnabled=false accessKeyUpdateInterval=0 min(s), accessTokenLifetime=0 min(s)
11/07/16 12:43:46 INFO namenode.NameNode: Caching file names occuring more than 10 times
11/07/16 12:43:47 INFO common.Storage: Image file of size 113 saved in 0 seconds.
11/07/16 12:43:47 INFO common.Storage: Storage directory /home/michael/hadooptmp/hadoop-michael/dfs/name has been successfully formatted.
11/07/16 12:43:47 INFO namenode.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at michael-VirtualBox/127.0.1.1
************************************************************/
michael@michael-VirtualBox:~/hadoop$ bin/start-all.sh
starting namenode, logging to /home/michael/hadoop/bin/../logs/hadoop-michael-namenode-michael-VirtualBox.out
localhost: starting datanode, logging to /home/michael/hadoop/bin/../logs/hadoop-michael-datanode-michael-VirtualBox.out
localhost: starting secondarynamenode, logging to /home/michael/hadoop/bin/../logs/hadoop-michael-secondarynamenode-michael-VirtualBox.out
starting jobtracker, logging to /home/michael/hadoop/bin/../logs/hadoop-michael-jobtracker-michael-VirtualBox.out
localhost: starting tasktracker, logging to /home/michael/hadoop/bin/../logs/hadoop-michael-tasktracker-michael-VirtualBox.out

michael@michael-VirtualBox:~/hadoop$ jps
7948 SecondaryNameNode
8033 JobTracker
8887 Jps
7627 NameNode
7781 DataNode
8190 TaskTracker


michael@michael-VirtualBox:~/hadoop$ bin/hadoop fs -put conf input
michael@michael-VirtualBox:~/hadoop$ bin/hadoop jar hadoop-examples-*.jar grep input output 'dfs[a-z.]+'
11/07/16 12:46:21 INFO mapred.FileInputFormat: Total input paths to process : 15
11/07/16 12:46:21 INFO mapred.JobClient: Running job: job_201107161244_0001
11/07/16 12:46:22 INFO mapred.JobClient:  map 0% reduce 0%
11/07/16 12:47:09 INFO mapred.JobClient:  map 13% reduce 0%
11/07/16 12:47:33 INFO mapred.JobClient:  map 26% reduce 0%
11/07/16 12:47:45 INFO mapred.JobClient:  map 26% reduce 8%
11/07/16 12:47:54 INFO mapred.JobClient:  map 40% reduce 8%
11/07/16 12:48:07 INFO mapred.JobClient:  map 53% reduce 13%
11/07/16 12:48:16 INFO mapred.JobClient:  map 53% reduce 17%
11/07/16 12:48:24 INFO mapred.JobClient:  map 66% reduce 17%
11/07/16 12:48:36 INFO mapred.JobClient:  map 80% reduce 22%
11/07/16 12:48:42 INFO mapred.JobClient:  map 80% reduce 26%
11/07/16 12:48:45 INFO mapred.JobClient:  map 93% reduce 26%
11/07/16 12:48:53 INFO mapred.JobClient:  map 100% reduce 26%
11/07/16 12:48:58 INFO mapred.JobClient:  map 100% reduce 33%
11/07/16 12:49:07 INFO mapred.JobClient:  map 100% reduce 100%
11/07/16 12:49:14 INFO mapred.JobClient: Job complete: job_201107161244_0001
11/07/16 12:49:15 INFO mapred.JobClient: Counters: 26
11/07/16 12:49:15 INFO mapred.JobClient:   Job Counters
11/07/16 12:49:15 INFO mapred.JobClient:     Launched reduce tasks=1
11/07/16 12:49:15 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=255488
11/07/16 12:49:15 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0
11/07/16 12:49:15 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0
11/07/16 12:49:15 INFO mapred.JobClient:     Launched map tasks=15
11/07/16 12:49:15 INFO mapred.JobClient:     Data-local map tasks=15
11/07/16 12:49:15 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=115656
11/07/16 12:49:15 INFO mapred.JobClient:   File Input Format Counters
11/07/16 12:49:15 INFO mapred.JobClient:     Bytes Read=25623
11/07/16 12:49:15 INFO mapred.JobClient:   File Output Format Counters
11/07/16 12:49:15 INFO mapred.JobClient:     Bytes Written=180
11/07/16 12:49:15 INFO mapred.JobClient:   FileSystemCounters
11/07/16 12:49:15 INFO mapred.JobClient:     FILE_BYTES_READ=82
11/07/16 12:49:15 INFO mapred.JobClient:     HDFS_BYTES_READ=27281
11/07/16 12:49:15 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=342206
11/07/16 12:49:15 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=180
11/07/16 12:49:15 INFO mapred.JobClient:   Map-Reduce Framework
11/07/16 12:49:15 INFO mapred.JobClient:     Map output materialized bytes=166
11/07/16 12:49:15 INFO mapred.JobClient:     Map input records=716
11/07/16 12:49:15 INFO mapred.JobClient:     Reduce shuffle bytes=166
11/07/16 12:49:15 INFO mapred.JobClient:     Spilled Records=6
11/07/16 12:49:15 INFO mapred.JobClient:     Map output bytes=70
11/07/16 12:49:15 INFO mapred.JobClient:     Map input bytes=25623
11/07/16 12:49:15 INFO mapred.JobClient:     Combine input records=3
11/07/16 12:49:15 INFO mapred.JobClient:     SPLIT_RAW_BYTES=1658
11/07/16 12:49:15 INFO mapred.JobClient:     Reduce input records=3
11/07/16 12:49:15 INFO mapred.JobClient:     Reduce input groups=3
11/07/16 12:49:15 INFO mapred.JobClient:     Combine output records=3
11/07/16 12:49:15 INFO mapred.JobClient:     Reduce output records=3
11/07/16 12:49:15 INFO mapred.JobClient:     Map output records=3
11/07/16 12:49:16 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
11/07/16 12:49:17 INFO mapred.FileInputFormat: Total input paths to process : 1
11/07/16 12:49:18 INFO mapred.JobClient: Running job: job_201107161244_0002
11/07/16 12:49:19 INFO mapred.JobClient:  map 0% reduce 0%
11/07/16 12:49:40 INFO mapred.JobClient:  map 100% reduce 0%
11/07/16 12:49:55 INFO mapred.JobClient:  map 100% reduce 100%
11/07/16 12:50:00 INFO mapred.JobClient: Job complete: job_201107161244_0002
11/07/16 12:50:00 INFO mapred.JobClient: Counters: 26
11/07/16 12:50:00 INFO mapred.JobClient:   Job Counters
11/07/16 12:50:00 INFO mapred.JobClient:     Launched reduce tasks=1
11/07/16 12:50:00 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=16946
11/07/16 12:50:00 INFO mapred.JobClient:     Total time spent by all reduces waiting after reserving slots (ms)=0
11/07/16 12:50:00 INFO mapred.JobClient:     Total time spent by all maps waiting after reserving slots (ms)=0
11/07/16 12:50:00 INFO mapred.JobClient:     Launched map tasks=1
11/07/16 12:50:00 INFO mapred.JobClient:     Data-local map tasks=1
11/07/16 12:50:00 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=14357
11/07/16 12:50:00 INFO mapred.JobClient:   File Input Format Counters
11/07/16 12:50:00 INFO mapred.JobClient:     Bytes Read=180
11/07/16 12:50:00 INFO mapred.JobClient:   File Output Format Counters
11/07/16 12:50:00 INFO mapred.JobClient:     Bytes Written=52
11/07/16 12:50:00 INFO mapred.JobClient:   FileSystemCounters
11/07/16 12:50:00 INFO mapred.JobClient:     FILE_BYTES_READ=82
11/07/16 12:50:00 INFO mapred.JobClient:     HDFS_BYTES_READ=298
11/07/16 12:50:00 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=41947
11/07/16 12:50:00 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=52
11/07/16 12:50:00 INFO mapred.JobClient:   Map-Reduce Framework
11/07/16 12:50:00 INFO mapred.JobClient:     Map output materialized bytes=82
11/07/16 12:50:00 INFO mapred.JobClient:     Map input records=3
11/07/16 12:50:00 INFO mapred.JobClient:     Reduce shuffle bytes=82
11/07/16 12:50:00 INFO mapred.JobClient:     Spilled Records=6
11/07/16 12:50:00 INFO mapred.JobClient:     Map output bytes=70
11/07/16 12:50:00 INFO mapred.JobClient:     Map input bytes=94
11/07/16 12:50:00 INFO mapred.JobClient:     Combine input records=0
11/07/16 12:50:00 INFO mapred.JobClient:     SPLIT_RAW_BYTES=118
11/07/16 12:50:00 INFO mapred.JobClient:     Reduce input records=3
11/07/16 12:50:00 INFO mapred.JobClient:     Reduce input groups=1
11/07/16 12:50:00 INFO mapred.JobClient:     Combine output records=0
11/07/16 12:50:00 INFO mapred.JobClient:     Reduce output records=3
11/07/16 12:50:00 INFO mapred.JobClient:     Map output records=3
michael@michael-VirtualBox:~/hadoop$

michael@michael-VirtualBox:~/hadoop$ cat output/output/*
cat: output/output/_logs: 是一个目录
1 dfs.replication
1 dfs.server.namenode.
1 dfsadmin

michael@michael-VirtualBox:~/hadoop$

到此伪分布式的演示成功。


转载请注明来自:Michael's blog @ http://sjsky.iteye.com

----------------------------- 分 ------------------------------ 隔 ------------------------------ 线 ------------------------------

5
4
分享到:
评论
3 楼 Menuz 2012-11-06  
文档翻译的不错。
2 楼 sjsky 2011-07-16  
conneyma 写道
牛人啊,都整些高深的东东~

现在对hadoop才是个入门,还没有深入理解呢
1 楼 conneyma 2011-07-16  
牛人啊,都整些高深的东东~

相关推荐

    hadoop2.7.3 Winutils.exe hadoop.dll

    在IT行业中,Hadoop是一个广泛使用的开源框架,主要用于大数据处理和分布式存储。Hadoop 2.7.3是这个框架的一个稳定版本,它包含了多个改进和优化,以提高性能和稳定性。在这个版本中,Winutils.exe和hadoop.dll是两...

    hadoop winutils hadoop.dll

    Hadoop是Apache软件基金会开发的一个开源分布式计算框架,它允许在普通硬件上高效处理大量数据。在Windows环境下,Hadoop的使用与Linux有所不同,因为它的设计最初是针对Linux操作系统的。"winutils"和"hadoop.dll...

    hadoop的dll文件 hadoop.zip

    Hadoop是一个开源的分布式计算框架,由Apache基金会开发,它主要设计用于处理和存储大量数据。在提供的信息中,我们关注的是"Hadoop的dll文件",这是一个动态链接库(DLL)文件,通常在Windows操作系统中使用,用于...

    hadoop2.7.3的hadoop.dll和winutils.exe

    在IT行业中,Hadoop是一个广泛使用的开源框架,主要用于大数据处理和分布式存储。Hadoop 2.7.3是Hadoop发展中的一个重要版本,它包含了众多的优化和改进,旨在提高性能、稳定性和易用性。在这个版本中,`hadoop.dll`...

    hadoop.dll & winutils.exe For hadoop-2.7.1

    在大数据处理领域,Hadoop是一个不可或缺的开源框架,它提供了分布式存储和计算的能力。本文将详细探讨与"Hadoop.dll"和"winutils.exe"相关的知识点,以及它们在Hadoop-2.7.1版本中的作用。 Hadoop.dll是Hadoop在...

    hadoop的hadoop.dll和winutils.exe下载

    在Hadoop生态系统中,`hadoop.dll`和`winutils.exe`是两个关键组件,尤其对于Windows用户来说,它们在本地开发和运行Hadoop相关应用时必不可少。`hadoop.dll`是一个动态链接库文件,主要用于在Windows环境中提供...

    Hadoop下载 hadoop-2.9.2.tar.gz

    Hadoop 是一个处理、存储和分析海量的分布式、非结构化数据的开源框架。最初由 Yahoo 的工程师 Doug Cutting 和 Mike Cafarella Hadoop 是一个处理、存储和分析海量的分布式、非结构化数据的开源框架。最初由 Yahoo...

    hadoop2.7.7对应的hadoop.dll,winutils.exe

    在Hadoop生态系统中,Hadoop 2.7.7是一个重要的版本,它为大数据处理提供了稳定性和性能优化。Hadoop通常被用作Linux环境下的分布式计算框架,但有时开发者或学习者在Windows环境下也需要进行Hadoop相关的开发和测试...

    hadoop.dll & winutils.exe For hadoop-2.6.0

    在Hadoop生态系统中,`hadoop.dll`和`winutils.exe`是两个关键组件,尤其对于Windows用户来说。本文将详细介绍这两个文件以及它们在Hadoop 2.6.0版本中的作用。 `hadoop.dll`是Hadoop在Windows环境下运行所必需的一...

    Hadoop下载 hadoop-3.3.3.tar.gz

    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 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...

    hadoop2.6 hadoop.dll+winutils.exe

    标题 "hadoop2.6 hadoop.dll+winutils.exe" 提到的是Hadoop 2.6版本中的两个关键组件:`hadoop.dll` 和 `winutils.exe`,这两个组件对于在Windows环境中配置和运行Hadoop至关重要。Hadoop原本是为Linux环境设计的,...

    win环境 hadoop 3.1.0安装包

    在Windows环境下安装Hadoop 3.1.0是学习和使用大数据处理技术的重要步骤。Hadoop是一个开源框架,主要用于分布式存储和处理大规模数据集。在这个过程中,我们将详细讲解Hadoop 3.1.0在Windows上的安装过程以及相关...

    各个版本Hadoop,hadoop.dll以及winutils.exe文件下载大合集

    在IT行业中,Hadoop是一个广泛使用的开源框架,主要用于大数据处理和分布式存储。它是由Apache软件基金会开发并维护的,旨在实现高效、可扩展的数据处理能力。Hadoop的核心由两个主要组件构成:Hadoop Distributed ...

    hadoop2.7.4 hadoop.dll包括winutils.exe

    Hadoop是Apache软件基金会开发的一个开源分布式计算框架,主要由HDFS(Hadoop Distributed File System)和MapReduce两大部分组成,旨在提供一种可靠、可扩展、高效的数据处理和存储解决方案。在标题中提到的...

    winutils+hadoop.dll+eclipse插件(hadoop2.7)

    在Hadoop生态系统中,`winutils.exe`和`hadoop.dll`是Windows环境下运行Hadoop必备的组件,尤其对于开发和测试环境来说至关重要。这里我们深入探讨这两个组件以及与Eclipse插件的相关性。 首先,`winutils.exe`是...

    hadoop2.6.0插件+64位winutils+hadoop.dll

    在IT行业中,Hadoop是一个广泛使用的开源框架,主要用于大数据处理和分布式存储。Hadoop2.6.0是这个框架的一个重要版本,它包含了多项优化和改进,以提高系统的稳定性和性能。在这个压缩包中,我们关注的是与Windows...

    hadoop环境缺少的hadoop.dll ,winutils.exe包

    在搭建Hadoop环境的过程中,经常会遇到一些特定的依赖问题,比如缺少`hadoop.dll`和`winutils.exe`这两个关键组件。本文将详细介绍这两个文件及其在Hadoop生态系统中的作用,以及如何解决它们缺失的问题。 首先,`...

    hadoop.dll & winutils.exe For hadoop-2.8.0

    在IT行业中,Hadoop是一个广泛使用的开源框架,主要用于大数据处理和分析。这个压缩包文件包含的是"Hadoop.dll"和"winutils.exe"两个关键组件,它们对于在Windows环境下配置和运行Hadoop生态系统至关重要。 首先,...

    hadoop-eclipse-plugin1.2.1 and hadoop-eclipse-plugin2.8.0

    《Hadoop Eclipse Plugin:开发利器的进化》 在大数据领域,Hadoop作为开源分布式计算框架,扮演着核心角色。为了方便开发者在Eclipse或MyEclipse这样的集成开发环境中高效地进行Hadoop应用开发,Hadoop-Eclipse-...

    Hadoop3.1.3.rar

    Hadoop是Apache软件基金会开发的一个开源分布式计算框架,它的核心设计是处理和存储大量数据的能力。这个名为"Hadoop3.1.3.rar"的压缩包文件包含了Hadoop 3.1.3版本的所有组件和相关文件,使得用户可以下载并进行...

Global site tag (gtag.js) - Google Analytics