Hadoop2.6运行wordcount

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Hadoop2.6运行wordcount

1、启动hadoop
[hadoop@master hadoop-2.6.0]$ ./sbin/start-all.sh
[hadoop@master hadoop-2.6.0]$ jps
21444 ResourceManager
21301 SecondaryNameNode
22072 Jps
21117 NameNode
[hadoop@slave1 current]$ jps
5505 NodeManager
5397 DataNode
6102 Jps

2、在hadoop的目录下创建一个file文件夹（哪里其实无所谓，导入到input就行）
[hadoop@master ~]$ mkdir file
[hadoop@master ~]$ cd file
在file文件夹中创建两个子文件，并输入内容：
[hadoop@master file]$ echo "Hello World" > file1.txt
[hadoop@master file]$ echo "Hello World" > file2.txt
[hadoop@master file]$ ls
file1.txt  file2.txt
[hadoop@master file]$ cat file1.txt
Hello World
[hadoop@master file]$ cat file2.txt
Hello World

3、在HDFS上创建输入文件夹目录 input
[hadoop@master hadoop-2.6.0]$ bin/hadoop fs -mkdir /input
[hadoop@master hadoop-2.6.0]$ hadoop fs -ls /
Found 1 items
drwxr-xr-x   - hadoop supergroup          0 2016-02-28 15:51 /input
[hadoop@master hadoop-2.6.0]$ bin/hadoop fs -put ~/file/file
file1.txt  file2.txt

4、把本地文件传到hdfs的/input中
[hadoop@master hadoop-2.6.0]$ bin/hadoop fs -put ~/file/file* /input
[hadoop@master hadoop-2.6.0]$ bin/hadoop fs -ls /input
Found 2 items
-rw-r--r--   2 hadoop supergroup         12 2016-02-28 15:55 /input/file1.txt
-rw-r--r--   2 hadoop supergroup         12 2016-02-28 15:55 /input/file2.txt

5、运行wordcount程序（使用hadoop自带运行wordcount的jar包）
[hadoop@master hadoop-2.6.0]$ bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar wordcount /input/ /output/wordcount1
16/02/28 15:58:15 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/02/28 15:58:16 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.101.230:8032
16/02/28 15:58:17 INFO input.FileInputFormat: Total input paths to process : 2
16/02/28 15:58:17 INFO mapreduce.JobSubmitter: number of splits:2
16/02/28 15:58:18 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1456645810248_0001
16/02/28 15:58:19 INFO impl.YarnClientImpl: Submitted application application_1456645810248_0001
16/02/28 15:58:19 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1456645810248_0001/
16/02/28 15:58:19 INFO mapreduce.Job: Running job: job_1456645810248_0001
16/02/28 15:58:32 INFO mapreduce.Job: Job job_1456645810248_0001 running in uber mode : false
16/02/28 15:58:32 INFO mapreduce.Job:  map 0% reduce 0%
16/02/28 15:58:43 INFO mapreduce.Job:  map 100% reduce 0%
16/02/28 15:58:56 INFO mapreduce.Job:  map 100% reduce 100%
16/02/28 15:58:56 INFO mapreduce.Job: Job job_1456645810248_0001 completed successfully
16/02/28 15:58:56 INFO mapreduce.Job: Counters: 49
        File System Counters
                FILE: Number of bytes read=54
                FILE: Number of bytes written=317807
                FILE: Number of read operations=0
                FILE: Number of large read operations=0
                FILE: Number of write operations=0
                HDFS: Number of bytes read=222
                HDFS: Number of bytes written=16
                HDFS: Number of read operations=9
                HDFS: Number of large read operations=0
                HDFS: Number of write operations=2
        Job Counters
                Launched map tasks=2
                Launched reduce tasks=1
                Data-local map tasks=2
                Total time spent by all maps in occupied slots (ms)=19118
                Total time spent by all reduces in occupied slots (ms)=8889
                Total time spent by all map tasks (ms)=19118
                Total time spent by all reduce tasks (ms)=8889
                Total vcore-seconds taken by all map tasks=19118
                Total vcore-seconds taken by all reduce tasks=8889
                Total megabyte-seconds taken by all map tasks=19576832
                Total megabyte-seconds taken by all reduce tasks=9102336
        Map-Reduce Framework
                Map input records=2
                Map output records=4
                Map output bytes=40
                Map output materialized bytes=60
                Input split bytes=198
                Combine input records=4
                Combine output records=4
                Reduce input groups=2
                Reduce shuffle bytes=60
                Reduce input records=4
                Reduce output records=2
                Spilled Records=8
                Shuffled Maps =2
                Failed Shuffles=0
                Merged Map outputs=2
                GC time elapsed (ms)=394
                CPU time spent (ms)=3450
                Physical memory (bytes) snapshot=368005120
                Virtual memory (bytes) snapshot=959819776
                Total committed heap usage (bytes)=247578624
        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=24
        File Output Format Counters
                Bytes Written=16

6、查看输出结果，计数成功
[hadoop@master hadoop-2.6.0]$ bin/hdfs dfs -cat /output/wordcount1/*
16/02/28 16:00:07 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Hello   2
World   2

同时可以在web页面上查看wordcount运行的结果