hadoop运行任务

前置准备1：启动hadoop

sh start-dfs.sh

sh start-yarn.sh

log：/appl/hadoop-2.7.0/logs

jps：datanode,namenode,nodemanager,secondarynamenode,resourcemanager

验证：http://192.168.56.250:8088/cluster

前置准备2：hadoop命令

hadoop fs -put localfile /user/hadoop/hadoopfile

hadoop fs -ls /user/hadoop/file1

hadoop fs -ls hdfs://localhost:9200

1、wordCount

Java Lib



Java source

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 MrTest01 {

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);
}
}

/**
* @param args
*/
public static void main(String[] args) throws Exception {
// TODO Auto-generated method stub
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount ");
System.exit(2);
}

Job job = new Job(conf, "word count");
job.setJarByClass(MrTest01.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}

打包方法：http://www.aboutyun.com/thread-7408-1-1.html（普通jar包可以了，此例子不需要可运行包）

# 启动hadoop

sh start-dfs.sh

sh start-yarn.sh

# log：/appl/hadoop-2.7.0/logs

# hadoop fs -put filename hdfs

hadoop fs -put /appl/hadoop-2.7.0/NOTICE.txt /test/

# hadoop jar xxx.jar [arg0,arg1,...]

hadoop jar /mk/test/MrTest01.jar hdfs://localhost:9000/test/NOTICE.txt hdfs://localhost:9000/test02/

[root@centos1 current]# hadoop jar /mk/test/MrTest01.jar hdfs://localhost:9000/test/NOTICE.txt hdfs://localhost:9000/test02
16/03/22 18:10:31 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/03/22 18:10:32 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
16/03/22 18:10:34 INFO input.FileInputFormat: Total input paths to process : 1
16/03/22 18:10:34 INFO mapreduce.JobSubmitter: number of splits:1
16/03/22 18:10:34 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1458639126126_0001
16/03/22 18:10:35 INFO impl.YarnClientImpl: Submitted application application_1458639126126_0001
16/03/22 18:10:35 INFO mapreduce.Job: The url to track the job: http://centos1:8088/proxy/application_1458639126126_0001/ 16/03/22 18:10:35 INFO mapreduce.Job: Running job: job_1458639126126_0001
16/03/22 18:10:46 INFO mapreduce.Job: Job job_1458639126126_0001 running in uber mode : false
16/03/22 18:10:46 INFO mapreduce.Job:  map 0% reduce 0%
16/03/22 18:10:53 INFO mapreduce.Job:  map 100% reduce 0%
16/03/22 18:11:02 INFO mapreduce.Job:  map 100% reduce 100%
16/03/22 18:11:02 INFO mapreduce.Job: Job job_1458639126126_0001 completed successfully
16/03/22 18:11:03 INFO mapreduce.Job: Counters: 49
File System Counters
FILE: Number of bytes read=173
FILE: Number of bytes written=229659
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=203
HDFS: Number of bytes written=123
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)=5612
Total time spent by all reduces in occupied slots (ms)=6218
Total time spent by all map tasks (ms)=5612
Total time spent by all reduce tasks (ms)=6218
Total vcore-seconds taken by all map tasks=5612
Total vcore-seconds taken by all reduce tasks=6218
Total megabyte-seconds taken by all map tasks=5746688
Total megabyte-seconds taken by all reduce tasks=6367232
Map-Reduce Framework
Map input records=2
Map output records=11
Map output bytes=145
Map output materialized bytes=173
Input split bytes=102
Combine input records=11
Combine output records=11
Reduce input groups=11
Reduce shuffle bytes=173
Reduce input records=11
Reduce output records=11
Spilled Records=22
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=126
CPU time spent (ms)=1480
Physical memory (bytes) snapshot=322916352
Virtual memory (bytes) snapshot=2383241216
Total committed heap usage (bytes)=164630528
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=101
File Output Format Counters
Bytes Written=123

hadoop fs -ls /test02/

-rw-r--r--   3 root supergroup          0 2016-03-22 18:11 /test02/_SUCCESS
-rw-r--r--   3 root supergroup        123 2016-03-22 18:11 /test02/part-r-00000

hadoop fs -cat /test02/part-r-00000

[root@centos1 current]# hadoop fs -cat /test02/part-r-00000
16/03/22 18:12:37 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
(http://www.apache.org/).	1
Apache	1
Foundation	1
Software	1
The	1
This	1
by	1
developed	1
includes	1
product	1
software	1

引入第三方包的方法

/appl/hadoop-2.7.0/etc/hadoop/hadoop-env.sh
export HADOOP_CLASSPATH=/appl/elasticsearch-hadoop-2.1.2/dist/elasticsearch-hadoop-2.1.2.jar

Refer
http://www.aboutyun.com/thread-7408-1-1.html