Hadoop2.6运行wordcount

Posted 2020-06-17

Hadoop2.6运行wordcount

1、启动hadoop

[[email protected] hadoop-2.6.0]$ ./sbin/start-all.sh

[[email protected] hadoop-2.6.0]$ jps

21444 ResourceManager

21301 SecondaryNameNode

22072 Jps

21117 NameNode

[[email protected] 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）

[[email protected] ~]$ mkdir file

[[email protected] ~]$ cd file

在file文件夹中创建两个子文件，并输入内容：

[[email protected] file]$ echo "Hello World" > file1.txt

[[email protected] file]$ echo "Hello World" > file2.txt

[[email protected] file]$ ls

file1.txt  file2.txt

[[email protected] file]$ cat file1.txt

Hello World

[[email protected] file]$ cat file2.txt

Hello World

3、在HDFS上创建输入文件夹目录 input

[[email protected] hadoop-2.6.0]$ bin/hadoop fs -mkdir /input

[[email protected] hadoop-2.6.0]$ hadoop fs -ls /

Found 1 items

drwxr-xr-x   - hadoop supergroup          0 2016-02-28 15:51 /input

[[email protected] 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

[[email protected] hadoop-2.6.0]$ bin/hadoop fs -put ~/file/file* /input

[[email protected] 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）

[[email protected] 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

[[email protected] 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

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