Hadoop2.8.2 运行wordcount
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
- 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 ...
- 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" ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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 ...
- 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
- xss姿势利用
1.定位页面可以出现xss的位置 可能会出现联合点利用 一个页面多个存储位置或者一个页面多个参数联合利用 例如输入xss 查看页面源码页面里有多个xss 或者多个参数显示 可以利用 需要注意的是有的是 ...
- insert into select 引起的 "子查询返回的值不止一个。当子查询跟随在**之后,或子查询用作表达式时,这种情况是不允许的"
目录 1.事故现场 1.1 在使用 Insert into Table2 select * from Table1 将表1的数据插入到表2时,报错如下: 1.2 sql 语句 2.推测 3.解决方案 ...
- C#初始类和命名空间
本节内容: 1.剖析Hello,World程序 1.1初始类(class)与名称空间(namespace) 2.类库的引用 2.1DLL的引用(黑盒引用) 2.2项目引用(白盒引用) 2.3建立自己的 ...
- vue-cli3 搭建 vue 项目
vue-cli3 搭建 vue 项目 项目是在mac的环境下配置的 win的同学请移步[https://www.cnblogs.com/zhaomeizi/p/8483597.html] 安装 nod ...
- 将windows项目移植到linux上
提要:由于项目使用java开发,移植中没有什么编译问题(移植很快,但小问题多) 1.移植过程中遇到的问题: (1).由于项目中使用了 1024以下的端口号,导致网络通信一直出错 原因:因为Linux要 ...
- requests用法基础-进阶
本节内容 模块的安装 -----------------------基础用法--------------------- GET用法.POST用法 -----------------------进阶用法 ...
- Md5与HMAC-SHA256
Md5签名算法 private string CalMd5(string str) { var md5 = MD5.Create(); var bs = md5.ComputeHash(Encodin ...
- arango集群部署
arango集群部署 ############arango集群操作################## arangodb3-3.3.16-1.x86_64.rpm(使用rpm包方式安装) arango ...
- 详细讲解IPython
ipython是一个python的交互式shell,比默认的python shell好用得多,支持变量自动补全,自动缩进,支持bash shell命令,内置了许多很有用的功能和函数.学习ipython ...
- 2018.8.1 python中字典的增删改查及其它操作
一.字典的简单介绍 1.dict 用{}来表示 键值对数据 {key:value} 唯一性 2.键都必须是可哈希,不可变的数据类型就可以当做字典中的键 值没有任何限制 ...