Linux巩固记录（5） hadoop 2.7.4下自己编译代码并运行MapReduce程序

程序代码为 ~\hadoop-2.7.4\share\hadoop\mapreduce\sources\hadoop-mapreduce-examples-2.7.4-sources\org\apache\hadoop\examples\WordCount.java

第一次 删除了package

package org.apache.hadoop.examples;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

public static class TokenizerMapper
extends Mapper<Object, Text, Text, IntWritable>{

private final static IntWritable one = new IntWritable(1);
private Text word = new Text();

public void map(Object key, Text value, Context context
) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
context.write(word, one);
}
}
}

public static class IntSumReducer
extends Reducer<Text,IntWritable,Text,IntWritable> {
private IntWritable result = new IntWritable();

public void reduce(Text key, Iterable<IntWritable> values,
Context context
) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}

public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length < 2) {
System.err.println("Usage: wordcount <in> [<in>...] <out>");
System.exit(2);
}
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
for (int i = 0; i < otherArgs.length - 1; ++i) {
FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
}
FileOutputFormat.setOutputPath(job,
new Path(otherArgs[otherArgs.length - 1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}

View Code

[root@master classes]#
[root@master classes]# tree
.

0 directories, 0 files
[root@master classes]# javac -classpath .:/home/jars/* -d /home/classes/ /home/javaFile/WordCount.java
[root@master classes]# tree
.
└── org
└── apache
└── hadoop
└── examples
├── WordCount.class
├── WordCount$IntSumReducer.class
└── WordCount$TokenizerMapper.class

4 directories, 3 files
[root@master classes]# jar -cvf wordcount.jar ./*
added manifest
adding: org/(in = 0) (out= 0)(stored 0%)
adding: org/apache/(in = 0) (out= 0)(stored 0%)
adding: org/apache/hadoop/(in = 0) (out= 0)(stored 0%)
adding: org/apache/hadoop/examples/(in = 0) (out= 0)(stored 0%)
adding: org/apache/hadoop/examples/WordCount$TokenizerMapper.class(in = 1790) (out= 764)(deflated 57%)
adding: org/apache/hadoop/examples/WordCount$IntSumReducer.class(in = 1793) (out= 749)(deflated 58%)
adding: org/apache/hadoop/examples/WordCount.class(in = 1988) (out= 1050)(deflated 47%)
[root@master classes]# /home/hadoop-2.7.4/bin/hadoop jar /home/classes/wordcount.jar org.apache.hadoop.examples.WordCount /hdfs-input.txt /result-package
17/09/02 02:20:41 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.0.80:8032
17/09/02 02:20:43 INFO input.FileInputFormat: Total input paths to process : 1
17/09/02 02:20:43 INFO mapreduce.JobSubmitter: number of splits:1
17/09/02 02:20:43 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1504320356950_0011
17/09/02 02:20:43 INFO impl.YarnClientImpl: Submitted application application_1504320356950_0011
17/09/02 02:20:43 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1504320356950_0011/ 17/09/02 02:20:43 INFO mapreduce.Job: Running job: job_1504320356950_0011
17/09/02 02:20:51 INFO mapreduce.Job: Job job_1504320356950_0011 running in uber mode : false
17/09/02 02:20:51 INFO mapreduce.Job:  map 0% reduce 0%
17/09/02 02:20:58 INFO mapreduce.Job:  map 100% reduce 0%
17/09/02 02:21:05 INFO mapreduce.Job:  map 100% reduce 100%
17/09/02 02:21:06 INFO mapreduce.Job: Job job_1504320356950_0011 completed successfully
17/09/02 02:21:06 INFO mapreduce.Job: Counters: 49
File System Counters
FILE: Number of bytes read=118
FILE: Number of bytes written=241857
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=174
HDFS: Number of bytes written=76
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)=3828
Total time spent by all reduces in occupied slots (ms)=4312
Total time spent by all map tasks (ms)=3828
Total time spent by all reduce tasks (ms)=4312
Total vcore-milliseconds taken by all map tasks=3828
Total vcore-milliseconds taken by all reduce tasks=4312
Total megabyte-milliseconds taken by all map tasks=3919872
Total megabyte-milliseconds taken by all reduce tasks=4415488
Map-Reduce Framework
Map input records=6
Map output records=12
Map output bytes=118
Map output materialized bytes=118
Input split bytes=98
Combine input records=12
Combine output records=9
Reduce input groups=9
Reduce shuffle bytes=118
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)=186
CPU time spent (ms)=1200
Physical memory (bytes) snapshot=297316352
Virtual memory (bytes) snapshot=4159815680
Total committed heap usage (bytes)=139595776
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=76
File Output Format Counters
Bytes Written=76
[root@master classes]# /home/hadoop-2.7.4/bin/hadoop fs -ls /
Found 4 items
-rw-r--r--   2 root supergroup         76 2017-09-02 00:57 /hdfs-input.txt
drwxr-xr-x   - root supergroup          0 2017-09-02 02:21 /result-package
drwxr-xr-x   - root supergroup          0 2017-09-02 02:12 /result-self-compile
drwx------   - root supergroup          0 2017-09-02 02:11 /tmp
[root@master classes]#
[root@master classes]#

为啥要删除package，就是因为有包路径的时候 调用方式就要 xxx.xxxxx.xxx来执行，而且打包的时候就不能只打class了，目录结构也要一并打进去

同理，自己写的代码也可按照这个方式执行

顺便提一点，如果只是打jar包 用

jar -cvf test.jar XXX.class

但是如果要修改MANIFEST.MF，在里面指定mainClass，按照如下方式

#解压文件
jar -xf test.jar

#在MANIFEST.MF 增加mainclass
Manifest-Version: 1.0
Created-By: 1.6.0_20 (Sun Microsystems Inc.)
Main-class: WordCount

#再打包
jar -cvfm test.jar MANIFEST.MF XXXX.class

这样就可以直接用 java -jar test.jar 运行了，后面不用跟具体的类