1. 本地创建文本文件
[root@s166 fantj]# mkdir input
[root@s166 fantj]# cd input/
[root@s166 input]# echo "hello fantj" > file1.txt
[root@s166 input]# echo "hello hadoop" > file2.txt
[root@s166 input]# echo "hello mapreduce" > file3.txt
[root@s166 input]# ls
file1.txt file2.txt file3.txt
2. 将文件上传到hadoop
[root@s166 input]# hadoop fs -mkdir /wordcount
[root@s166 input]# hadoop fs -ls /
Found 1 items
drwxr-xr-x - root supergroup 0 2018-07-27 07:51 /wordcount
[root@s166 input]# cd ..
[root@s166 fantj]# ls
download hadoop input jdk
[root@s166 fantj]# hadoop fs -put input/* /wordcount
[root@s166 fantj]# hadoop fs -ls /wordcount
Found 3 items
-rw-r--r-- 3 root supergroup 12 2018-07-27 07:52 /wordcount/file1.txt
-rw-r--r-- 3 root supergroup 13 2018-07-27 07:52 /wordcount/file2.txt
-rw-r--r-- 3 root supergroup 16 2018-07-27 07:52 /wordcount/file3.txt
3. 启用hadoop自带单词统计进行处理
[root@s166 fantj]# cd /home/fantj/hadoop/share/hadoop/
[root@s166 hadoop]# ls
common hdfs httpfs kms mapreduce tools yarn
[root@s166 hadoop]# cd mapreduce/
[root@s166 mapreduce]# ls
hadoop-mapreduce-client-app-2.7.0.jar hadoop-mapreduce-client-hs-plugins-2.7.0.jar hadoop-mapreduce-examples-2.7.0.jar
hadoop-mapreduce-client-common-2.7.0.jar hadoop-mapreduce-client-jobclient-2.7.0.jar lib
hadoop-mapreduce-client-core-2.7.0.jar hadoop-mapreduce-client-jobclient-2.7.0-tests.jar lib-examples
hadoop-mapreduce-client-hs-2.7.0.jar hadoop-mapreduce-client-shuffle-2.7.0.jar sources
[root@s166 mapreduce]# hadoop jar hadoop-mapreduce-examples-2.7.0.jar wordcount /wordcount /print
查看结果
[root@s166 mapreduce]# hadoop fs -ls /print
Found 2 items
-rw-r--r-- 3 root supergroup 0 2018-07-27 07:55 /print/_SUCCESS
-rw-r--r-- 3 root supergroup 37 2018-07-27 07:55 /print/part-r-00000
[root@s166 mapreduce]# hadoop fs -cat /print/part-r-00000
fantj 1
hadoop 1
hello 3
mapreduce 1
