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. “无处不在” 的系统核心服务 —— ActivityManagerService 启动流程解析

    本文基于 Android 9.0 , 代码仓库地址 : android_9.0.0_r45 系列文章目录: Java 世界的盘古和女娲 -- Zygote Zygote 家的大儿子 -- System ...

  2. Centos中查找文件、目录、内容

    1.查找文件 find / -name 'filename' 2.查找文件夹(目录) find / -name 'path' -type d 3.查找内容 find . | xargs grep -r ...

  3. MySQL GROUP_CONCAT()函数 -- 字段合并查询

    在做查询的时候遇到一个问题,今天分享一下解决方法. 先看一下我想要什么效果. 清单名称类型要点,后面两列为清单步骤(外键表) 但我并不想让主表的内容重复那么多遍,于是 distinct去重.子查询.左 ...

  4. JDK1.8 新特性详解

    一  引言 现在java 10都已经出来了,而自己对java 8的一些新特性都不了解,很是惭愧,而且许多面试都有问到java8的新特性,借此博客好好学习这些新特性 二  新特性 1 default关键 ...

  5. Robot Framework——对时间操作的datetime库常用关键字

    1.对固定日期进行操作,增加或减去单位时间或者时间段 2.对两个时间段进行操作 3.对时间格式转化,获取时间戳 4.从完整时间中取指定年月日等 5.对时间类型进行格式化 6.获取当前时间或者指定时区时 ...

  6. fenby C语言 P10

    if判断语句; if(a<0)→if(条件) if(){C语言语句} #include <stdio.h> int main() { int a=10; if(a>0) { p ...

  7. python基础-字符串(str)类型及内置方法

    字符串-str 用途:多用于记录描述性的内容 定义方法: # 可用'','''''',"","""""" 都可以用于定义 ...

  8. 学习笔记52_mongodb增删改查

    使用use db1作为当前数据库 如果没有db1,会自动创建 使用switch db2,当前数据库切换为db2 使用show dbs,显示当前所有数据库 使用show collection ,显示当前 ...

  9. [考试反思]0927csp-s模拟测试53:沦陷

    很喜欢Yu-shi说过的一句话 在OI里,菜即是原罪 对啊. 都会.谁信呢? 没有分数,你说话算什么呢? 你就是菜,你就是不对,没有别的道理. 最没有用的,莫过于改题大神,这就是菜的借口. 但是其实这 ...

  10. 爬虫学习--Day3(小猿圈爬虫开发_1)

    爬虫基础简介 前戏: 1.你是否在夜深人静的时候,想看一些让你更睡不着的图片 2.你是否在考试或者面试前夕,想看一些具有针对性的题目和面试题 3.你是否想在杂乱的网络世界中获取你想要的数据 什么是爬虫 ...