1 例子jar位置

[hadoop@hadoop02 mapreduce]$ pwd
/hadoop/hadoop-2.8.2/share/hadoop/mapreduce
[hadoop@hadoop02 mapreduce]$ ls -lrt
总用量 5084
drwxr-xr-x 2 hadoop hadoop 4096 10月 20 05:11 lib
drwxr-xr-x 2 hadoop hadoop 4096 10月 20 05:11 jdiff
-rw-r--r-- 1 hadoop hadoop 301936 10月 20 05:11 hadoop-mapreduce-examples-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 77142 10月 20 05:11 hadoop-mapreduce-client-shuffle-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 1588114 10月 20 05:11 hadoop-mapreduce-client-jobclient-2.8.2-tests.jar
-rw-r--r-- 1 hadoop hadoop 67003 10月 20 05:11 hadoop-mapreduce-client-jobclient-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 31535 10月 20 05:11 hadoop-mapreduce-client-hs-plugins-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 195052 10月 20 05:11 hadoop-mapreduce-client-hs-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 1571759 10月 20 05:11 hadoop-mapreduce-client-core-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 782757 10月 20 05:11 hadoop-mapreduce-client-common-2.8.2.jar
-rw-r--r-- 1 hadoop hadoop 563771 10月 20 05:11 hadoop-mapreduce-client-app-2.8.2.jar
drwxr-xr-x 2 hadoop hadoop 4096 10月 20 05:11 sources
drwxr-xr-x 2 hadoop hadoop 29 10月 20 05:11 lib-examples

2 生成数据文件

[hadoop@hadoop01 ~]$ echo "Hello World">>word.txt
[hadoop@hadoop01 ~]$ echo "Hello Hadoop">>word.txt
[hadoop@hadoop01 ~]$ echo "Hello Hive">>word.txt

3 创建HDFS目录

[hadoop@hadoop01 ~]$ hadoop dfs -mkdir /work/data/input
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. [hadoop@hadoop01 ~]$ hadoop dfs -lsr /work/data
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. lsr: DEPRECATED: Please use 'ls -R' instead.
drwxr-xr-x - hadoop supergroup 0 2017-11-12 09:00 /work/data/input
[hadoop@hadoop01 ~]$

4 将数据文件word.txt上传以HDFS /work/data/input目录下

[hadoop@hadoop01 ~]$ hadoop dfs -copyFromLocal word.txt /work/data/input
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. [hadoop@hadoop01 ~]$ hadoop dfs -text /work/data/input/word.txt
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. Hello World
Hello Hadoop
Hello Hive
[hadoop@hadoop01 ~]$

5 运行wordcount例子

[hadoop@hadoop01 hadoop-2.8.2]$ pwd
/hadoop/hadoop-2.8.2
[hadoop@hadoop01 hadoop-2.8.2]$ hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.2.jar wordcount /work/data/input /work/data/output
17/11/12 09:05:14 INFO client.RMProxy: Connecting to ResourceManager at hadoop02/192.168.169.102:8032
17/11/12 09:05:15 INFO input.FileInputFormat: Total input files to process : 1
17/11/12 09:05:15 INFO mapreduce.JobSubmitter: number of splits:1
17/11/12 09:05:15 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1510447239720_0001
17/11/12 09:05:16 INFO impl.YarnClientImpl: Submitted application application_1510447239720_0001
17/11/12 09:05:16 INFO mapreduce.Job: The url to track the job: http://hadoop02:8088/proxy/application_1510447239720_0001/
17/11/12 09:05:16 INFO mapreduce.Job: Running job: job_1510447239720_0001
17/11/12 09:05:25 INFO mapreduce.Job: Job job_1510447239720_0001 running in uber mode : false
17/11/12 09:05:25 INFO mapreduce.Job: map 0% reduce 0%
17/11/12 09:05:35 INFO mapreduce.Job: map 100% reduce 0%
17/11/12 09:05:40 INFO mapreduce.Job: map 100% reduce 100%
17/11/12 09:05:41 INFO mapreduce.Job: Job job_1510447239720_0001 completed successfully
17/11/12 09:05:41 INFO mapreduce.Job: Counters: 49
File System Counters
FILE: Number of bytes read=53
FILE: Number of bytes written=276955
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=152
HDFS: Number of bytes written=31
HDFS: Number of read operations=6
HDFS: Number of large read operations=0
HDFS: Number of write operations=2
Job Counters
Launched map tasks=1
Launched reduce tasks=1
Data-local map tasks=1
Total time spent by all maps in occupied slots (ms)=5860
Total time spent by all reduces in occupied slots (ms)=3296
Total time spent by all map tasks (ms)=5860
Total time spent by all reduce tasks (ms)=3296
Total vcore-milliseconds taken by all map tasks=5860
Total vcore-milliseconds taken by all reduce tasks=3296
Total megabyte-milliseconds taken by all map tasks=6000640
Total megabyte-milliseconds taken by all reduce tasks=3375104
Map-Reduce Framework
Map input records=3
Map output records=6
Map output bytes=59
Map output materialized bytes=53
Input split bytes=117
Combine input records=6
Combine output records=4
Reduce input groups=4
Reduce shuffle bytes=53
Reduce input records=4
Reduce output records=4
Spilled Records=8
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=224
CPU time spent (ms)=2190
Physical memory (bytes) snapshot=443719680
Virtual memory (bytes) snapshot=4207517696
Total committed heap usage (bytes)=293076992
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=35
File Output Format Counters
Bytes Written=31
[hadoop@hadoop01 hadoop-2.8.2]$

6 查看结果

[hadoop@hadoop01 hadoop-2.8.2]$ hadoop dfs -lsr /work/data/output
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. lsr: DEPRECATED: Please use 'ls -R' instead.
-rw-r--r-- 2 hadoop supergroup 0 2017-11-12 09:05 /work/data/output/_SUCCESS
-rw-r--r-- 2 hadoop supergroup 31 2017-11-12 09:05 /work/data/output/part-r-00000
[hadoop@hadoop01 hadoop-2.8.2]$ hadoop dfs -text /work/data/output/part-r-00000
DEPRECATED: Use of this script to execute hdfs command is deprecated.
Instead use the hdfs command for it. Hadoop 1
Hello 3
Hive 1
World 1
[hadoop@hadoop01 hadoop-2.8.2]$

Hadoop2.8.2 运行wordcount的更多相关文章

  1. hadoop2.6.4运行wordcount

    hadoop用户登录,启动服务: start-dfs.sh && start-yarn.sh 创建输入目录: hadoop df -mkdir /input 把测试文件导入/input ...

  2. hadoop2.6.5运行wordcount实例

    运行wordcount实例 在/tmp目录下生成两个文本文件,上面随便写两个单词. cd /tmp/ mkdir file cd file/ echo "Hello world" ...

  3. hadoop2.7.x运行wordcount程序卡住在INFO mapreduce.Job: Running job:job _1469603958907_0002

    一.抛出问题 Hadoop集群(全分布式)配置好后,运行wordcount程序测试,发现每次运行都会卡住在Running job处,然后程序就呈现出卡死的状态. wordcount运行命令:[hado ...

  4. CentOS上安装Hadoop2.7,添加数据节点,运行wordcount

    安装hadoop的步骤比较繁琐,但是并不难. 在CentOS上安装Hadoop2.7 1. 安装 CentOS,注:图形界面并无必要 2. 在CentOS里设置静态IP,手工编辑如下4个文件 /etc ...

  5. win10+eclipse+hadoop2.7.2+maven+local模式直接通过Run as Java Application运行wordcount

    一.准备工作 (1)Hadoop2.7.2 在linux部署完毕,成功启动dfs和yarn,通过jps查看,进程都存在 (2)安装maven 二.最终效果 在windows系统中,直接通过Run as ...

  6. Spark源码编译并在YARN上运行WordCount实例

    在学习一门新语言时,想必我们都是"Hello World"程序开始,类似地,分布式计算框架的一个典型实例就是WordCount程序,接触过Hadoop的人肯定都知道用MapRedu ...

  7. 解决在windows的eclipse上面运行WordCount程序出现的一系列问题详解

    一.简介 要在Windows下的 Eclipse上调试Hadoop2代码,所以我们在windows下的Eclipse配置hadoop-eclipse-plugin- 2.6.0.jar插件,并在运行H ...

  8. Spark on YARN简介与运行wordcount(master、slave1和slave2)(博主推荐)

    前期博客 Spark on YARN模式的安装(spark-1.6.1-bin-hadoop2.6.tgz +hadoop-2.6.0.tar.gz)(master.slave1和slave2)(博主 ...

  9. Spark standalone简介与运行wordcount(master、slave1和slave2)

    前期博客 Spark standalone模式的安装(spark-1.6.1-bin-hadoop2.6.tgz)(master.slave1和slave2)  Spark运行模式概述 1. Stan ...

随机推荐

  1. HDU 6045 Is Derek lying?

    题目网址:http://acm.hdu.edu.cn/showproblem.php?pid=6045 题目: Is Derek lying? Time Limit: 3000/1000 MS (Ja ...

  2. IIS6.0使用冒号上传漏洞利用

    利用条件: 1.iis版本为6.0  2.上传文件名不会重命名 利用: 上传一个jpg木马图片 名字为:cs.asp:.jpg 注意是: 默认windows是不允许文件字含:(冒号)的 所以需要抓包后 ...

  3. selenium-find_element相关内容(2)

    find_element跟find_element_by_xxx的区别 1.查看文件D:\soft\python36\Lib\site-packages\selenium\webdriver\remo ...

  4. Rancher与ARM深化战略合作,“软硬结合”加速边缘计算时代

    时至今日,许多企业已将边缘计算列为战略目标,对于部分企业而言,边缘计算则已成为它们势在必行的部分.而随着对应用软件和硬件能力的需求不断增长,容器和Kubernetes已发展为边缘计算领域备受瞩目的一项 ...

  5. 浅谈原理--hashCode方法

    我们时常会判断一个元素是否相等重复,可以用equals方法. 每增加一个元素,我们就可以通过equals方法判断集合中的每一个元素是否重复,但是如果集合中有10000个元素了,我们每添加一个元素的时候 ...

  6. vue cli3.3 以上版本配置vue.config.js

    // vue.config.js 配置说明//官方vue.config.js 参考文档 https://cli.vuejs.org/zh/config/#css-loaderoptions// 这里只 ...

  7. 数据后台管理(五)AOP日志

    为了增加数据的安全性,在数据管理的过程中,我们需要将操作者访问时间,操作者的名称,访问的IP,访问资源的URL,执行时长,访问方法记录下来存储到数据库中,并可以通过页面查看. 1.将日志信息存储到数据 ...

  8. [apue] 如何处理 tcp 紧急数据(OOB)?

    在上大学的时候,我们可能就听说了OOB(Out Of Band 带外数据,又称紧急数据)这个概念. 当时老师给的解释就是在当前处理的数据流之外的数据,用于紧急的情况.然后就没有然后了…… 毕业这么多年 ...

  9. 高频Linux命令小结(新手向)

    示例代码托管在:http://www.github.com/dashnowords/blogs 博客园地址:<大史住在大前端>原创博文目录 华为云社区地址:[你要的前端打怪升级指南] 近期 ...

  10. 前端技术之:如何在Vue中使用clipboard.js复制服务端数据

    第一步 创建点击对象页面元素,并绑定业务数据. <el-button type="text" size="mini" class="copy-b ...