一、MapReduce验证

1. 本地创建一个test.txt文件
   vim test.txt
   输入一些英文句子如下：

Beijing is the capital of China
I love Beijing
I love China

2. 上传test.txt到hdfs系统的 ouput目录

• hdfs dfs -mkdir /user
• hdfs dfs -mkdir /user/input
• hdfs dfs -put test.txt /user/input

3. 执行MapReduce例子程序

• /hadoop/hadoop-2.9.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.0.jar替换成自己的对应目录。

hadoop jar /hadoop/hadoop-2.9.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.0.jar wordcount /user/input/test.txt output

• 执行命令正常输出如下结果，map先从0-100然后reduce从0-100.

18/11/08 16:18:48 INFO client.RMProxy: Connecting to ResourceManager at master.hadoop/172.16.16.15:8032
18/11/08 16:18:49 INFO input.FileInputFormat: Total input files to process : 1
18/11/08 16:18:49 INFO mapreduce.JobSubmitter: number of splits:1
18/11/08 16:18:49 INFO Configuration.deprecation: yarn.resourcemanager.system-metrics-publisher.enabled is deprecated. Instead, use yarn.system-metrics-publisher.enabled
18/11/08 16:18:49 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1541665050140_0001
18/11/08 16:18:49 INFO impl.YarnClientImpl: Submitted application application_1541665050140_0001
18/11/08 16:18:49 INFO mapreduce.Job: The url to track the job: http://master.hadoop:8088/proxy/application_1541665050140_0001/
18/11/08 16:18:49 INFO mapreduce.Job: Running job: job_1541665050140_0001
18/11/08 16:18:55 INFO mapreduce.Job: Job job_1541665050140_0001 running in uber mode : false
18/11/08 16:18:55 INFO mapreduce.Job:  map 0% reduce 0%
18/11/08 16:19:00 INFO mapreduce.Job:  map 100% reduce 0%
18/11/08 16:19:05 INFO mapreduce.Job:  map 100% reduce 100%
18/11/08 16:19:06 INFO mapreduce.Job: Job job_1541665050140_0001 completed successfully
18/11/08 16:19:06 INFO mapreduce.Job: Counters: 49
	File System Counters
		FILE: Number of bytes read=106
		FILE: Number of bytes written=404235
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=175
		HDFS: Number of bytes written=64
		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
		Rack-local map tasks=1
		Total time spent by all maps in occupied slots (ms)=1945
		Total time spent by all reduces in occupied slots (ms)=1574
		Total time spent by all map tasks (ms)=1945
		Total time spent by all reduce tasks (ms)=1574
		Total vcore-milliseconds taken by all map tasks=1945
		Total vcore-milliseconds taken by all reduce tasks=1574
		Total megabyte-milliseconds taken by all map tasks=1991680
		Total megabyte-milliseconds taken by all reduce tasks=1611776
	Map-Reduce Framework
		Map input records=3
		Map output records=12
		Map output bytes=107
		Map output materialized bytes=106
		Input split bytes=116
		Combine input records=12
		Combine output records=9
		Reduce input groups=9
		Reduce shuffle bytes=106
		Reduce input records=9
		Reduce output records=9
		Spilled Records=18
		Shuffled Maps =1
		Failed Shuffles=0
		Merged Map outputs=1
		GC time elapsed (ms)=88
		CPU time spent (ms)=890
		Physical memory (bytes) snapshot=513982464
		Virtual memory (bytes) snapshot=4242575360
		Total committed heap usage (bytes)=316145664
	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=59
	File Output Format Counters 
		Bytes Written=64

• 查看结果
  hdfs dfs -ls output

Found 2 items
-rw-r--r--   1 root supergroup          0 2018-11-08 16:19 output1/_SUCCESS
-rw-r--r--   1 root supergroup         64 2018-11-08 16:19 output1/part-r-00000

hdfs dfs -cat output/part-r-00000

Beijing	2
China	2
I	2
capital	1
is	1
love	2
of	1
the	1

-下载到本地output目录看结果
hdfs dfs -get output output
cat ouput/part-r-00000
输出同样的结果

二、hdfs常用命令

图中显示了很多命令选项信息。以上截图不全，我在表格4-1中完整地列出了支持的命令选项。

注意：以上表格中路径包括hdfs中的路径和linux中的路径。对于容易产生歧义的地方，会特别指出“linux路径”或者“hdfs路径”。如果没有明确指出，意味着是hdfs路径。