solution:No job file jar和ClassNotFoundException(hadoop,mapreduce)，hadoopmapreduce
solution:No job file jar和ClassNotFoundException(hadoop,mapreduce)，hadoopmapreduce
hadoop-1.2.1伪分布式搭建好了，也只是用命令跑过hadoop-example.jar包的wordcount，这一切看起来so easy。
但没想到的是，自己的mr程序，运行起来却遇到了No job file jar和ClassNotFoundException的问题。
经过一番周折，自己写的mapreduce 终于成功运行了。
我没有将第三方jar包（hadoop-core，commons-cli，commons-xxx等6个jar包）和自己的代码的jar包全部都添加到远程集群上，在本地也没有将第三方jar包打成third-party.jar，也没有用到“-libjars”参数，连GenericOptionsParser也没使用（网上很多solution都说这个用来解析hadoop的命令参数），，
关键代码：
Job job = new Job(getConf());
job.setJarByClass(WordCountJob.class)；
和
int res = ToolRunner.run(new WordCountJob(),args);
source code：
package wordcount2;
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.util.GenericOptionsParser;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class WordCountJob extends Configured implements Tool {
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);
}
}
@Override
public int run(String[] args) throws Exception {
// TODO Auto-generated method stub
// Configuration conf = new Configuration();
// String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();
if(args.length !=2){
System.err.println("Usage:wordcount <in> <out>");
System.exit(2);
}
// Job job = new Job(conf,"wordcountmr");
Job job = new Job(getConf());
job.setJarByClass(WordCountJob.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(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true)?0:1);
return 0;
}
public static void main(String[] args) throws Exception{
int res = ToolRunner.run(new WordCountJob(),args);
System.exit(res);
}
}
编译成jar包，可以使用命令（javac -classpath /home/lzc/hadoop-1.2.1/hadoop-core-1.2.1.jar:/home/lzc/hadoop-1.2.1/lib/commons-cli-1.2.jar -d ./classes/ ./src/WordCountJob.java以及jar -cvfm wordcountjob.jar -C ./classes/两个命令），最简单的方式是使用eclipse的导出jar文件功能，单独将该class生成一个jar文件。
把生成的jar包cp到hadoop_home下，执行以下命令。
hadoop121@ubuntu:~/Dolphin/hadoop-1.2.1$ bin/hadoop jar wc2.jar wordcount2.WordCountJob input/file*.txt output
14/12/10 15:48:59 INFO input.FileInputFormat: Total input paths to process : 2
14/12/10 15:48:59 INFO util.NativeCodeLoader: Loaded the native-hadoop library
14/12/10 15:48:59 WARN snappy.LoadSnappy: Snappy native library not loaded
14/12/10 15:49:00 INFO mapred.JobClient: Running job: job_201412080836_0026
14/12/10 15:49:01 INFO mapred.JobClient: map 0% reduce 0%
14/12/10 15:49:06 INFO mapred.JobClient: map 100% reduce 0%
14/12/10 15:49:13 INFO mapred.JobClient: map 100% reduce 33%
14/12/10 15:49:15 INFO mapred.JobClient: map 100% reduce 100%
14/12/10 15:49:15 INFO mapred.JobClient: Job complete: job_201412080836_0026
14/12/10 15:49:15 INFO mapred.JobClient: Counters: 29
14/12/10 15:49:15 INFO mapred.JobClient: Job Counters
14/12/10 15:49:15 INFO mapred.JobClient: Launched reduce tasks=1
14/12/10 15:49:15 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=7921
14/12/10 15:49:15 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0
14/12/10 15:49:15 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0
14/12/10 15:49:15 INFO mapred.JobClient: Launched map tasks=2
14/12/10 15:49:15 INFO mapred.JobClient: Data-local map tasks=2
14/12/10 15:49:15 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=9018
14/12/10 15:49:15 INFO mapred.JobClient: File Output Format Counters
14/12/10 15:49:15 INFO mapred.JobClient: Bytes Written=48
14/12/10 15:49:15 INFO mapred.JobClient: FileSystemCounters
14/12/10 15:49:15 INFO mapred.JobClient: FILE_BYTES_READ=102
14/12/10 15:49:15 INFO mapred.JobClient: HDFS_BYTES_READ=284
14/12/10 15:49:15 INFO mapred.JobClient: FILE_BYTES_WRITTEN=190665
14/12/10 15:49:15 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=48
14/12/10 15:49:15 INFO mapred.JobClient: File Input Format Counters
14/12/10 15:49:15 INFO mapred.JobClient: Bytes Read=48
14/12/10 15:49:15 INFO mapred.JobClient: Map-Reduce Framework
14/12/10 15:49:15 INFO mapred.JobClient: Map output materialized bytes=108
14/12/10 15:49:15 INFO mapred.JobClient: Map input records=2
14/12/10 15:49:15 INFO mapred.JobClient: Reduce shuffle bytes=108
14/12/10 15:49:15 INFO mapred.JobClient: Spilled Records=16
14/12/10 15:49:15 INFO mapred.JobClient: Map output bytes=80
14/12/10 15:49:15 INFO mapred.JobClient: CPU time spent (ms)=2420
14/12/10 15:49:15 INFO mapred.JobClient: Total committed heap usage (bytes)=390004736
14/12/10 15:49:15 INFO mapred.JobClient: Combine input records=8
14/12/10 15:49:15 INFO mapred.JobClient: SPLIT_RAW_BYTES=236
14/12/10 15:49:15 INFO mapred.JobClient: Reduce input records=8
14/12/10 15:49:15 INFO mapred.JobClient: Reduce input groups=6
14/12/10 15:49:15 INFO mapred.JobClient: Combine output records=8
14/12/10 15:49:15 INFO mapred.JobClient: Physical memory (bytes) snapshot=436707328
14/12/10 15:49:15 INFO mapred.JobClient: Reduce output records=6
14/12/10 15:49:15 INFO mapred.JobClient: Virtual memory (bytes) snapshot=1908416512
14/12/10 15:49:15 INFO mapred.JobClient: Map output records=8
hadoop121@ubuntu:~/Dolphin/hadoop-1.2.1$ bin/hadoop fs -ls output
Found 3 items
-rw-r--r-- 2 hadoop121 supergroup 0 2014-12-10 15:49 /user/hadoop121/output/_SUCCESS
drwxr-xr-x - hadoop121 supergroup 0 2014-12-10 15:49 /user/hadoop121/output/_logs
-rw-r--r-- 2 hadoop121 supergroup 48 2014-12-10 15:49 /user/hadoop121/output/part-r-00000
hadoop121@ubuntu:~/Dolphin/hadoop-1.2.1$ bin/hadoop fs -cat output/part-r-00000
Hadoop 1
Hello 2
Word 1
hadoop 1
hello 2
word 1
有人说hdfs不能访问本地文件，有权限问题，但我特意试了下，本地一样成功执行。
hadoop121@ubuntu:~/Dolphin/hadoop-1.2.1$ bin/hadoop jar /home/lzc/workspace/wordcount1/wc2.jar wordcount2.WordCountJob input/file*.txt output
14/12/10 16:08:26 INFO input.FileInputFormat: Total input paths to process : 2
14/12/10 16:08:26 INFO util.NativeCodeLoader: Loaded the native-hadoop library
14/12/10 16:08:26 WARN snappy.LoadSnappy: Snappy native library not loaded
14/12/10 16:08:27 INFO mapred.JobClient: Running job: job_201412080836_0027
14/12/10 16:08:28 INFO mapred.JobClient: map 0% reduce 0%
14/12/10 16:08:33 INFO mapred.JobClient: map 100% reduce 0%
14/12/10 16:08:40 INFO mapred.JobClient: map 100% reduce 33%
14/12/10 16:08:41 INFO mapred.JobClient: map 100% reduce 100%
14/12/10 16:08:42 INFO mapred.JobClient: Job complete: job_201412080836_0027
14/12/10 16:08:42 INFO mapred.JobClient: Counters: 29
14/12/10 16:08:42 INFO mapred.JobClient: Job Counters
14/12/10 16:08:42 INFO mapred.JobClient: Launched reduce tasks=1
14/12/10 16:08:42 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=7221
14/12/10 16:08:42 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0
14/12/10 16:08:42 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0
14/12/10 16:08:42 INFO mapred.JobClient: Launched map tasks=2
14/12/10 16:08:42 INFO mapred.JobClient: Data-local map tasks=2
14/12/10 16:08:42 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=8677
14/12/10 16:08:42 INFO mapred.JobClient: File Output Format Counters
14/12/10 16:08:42 INFO mapred.JobClient: Bytes Written=48
14/12/10 16:08:42 INFO mapred.JobClient: FileSystemCounters
14/12/10 16:08:42 INFO mapred.JobClient: FILE_BYTES_READ=102
14/12/10 16:08:42 INFO mapred.JobClient: HDFS_BYTES_READ=284
14/12/10 16:08:42 INFO mapred.JobClient: FILE_BYTES_WRITTEN=190665
14/12/10 16:08:42 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=48
14/12/10 16:08:42 INFO mapred.JobClient: File Input Format Counters
14/12/10 16:08:42 INFO mapred.JobClient: Bytes Read=48
14/12/10 16:08:42 INFO mapred.JobClient: Map-Reduce Framework
14/12/10 16:08:42 INFO mapred.JobClient: Map output materialized bytes=108
14/12/10 16:08:42 INFO mapred.JobClient: Map input records=2
14/12/10 16:08:42 INFO mapred.JobClient: Reduce shuffle bytes=108
14/12/10 16:08:42 INFO mapred.JobClient: Spilled Records=16
14/12/10 16:08:42 INFO mapred.JobClient: Map output bytes=80
14/12/10 16:08:42 INFO mapred.JobClient: CPU time spent (ms)=2280
14/12/10 16:08:42 INFO mapred.JobClient: Total committed heap usage (bytes)=373489664
14/12/10 16:08:42 INFO mapred.JobClient: Combine input records=8
14/12/10 16:08:42 INFO mapred.JobClient: SPLIT_RAW_BYTES=236
14/12/10 16:08:42 INFO mapred.JobClient: Reduce input records=8
14/12/10 16:08:42 INFO mapred.JobClient: Reduce input groups=6
14/12/10 16:08:42 INFO mapred.JobClient: Combine output records=8
14/12/10 16:08:42 INFO mapred.JobClient: Physical memory (bytes) snapshot=433147904
14/12/10 16:08:42 INFO mapred.JobClient: Reduce output records=6
14/12/10 16:08:42 INFO mapred.JobClient: Virtual memory (bytes) snapshot=1911033856
14/12/10 16:08:42 INFO mapred.JobClient: Map output records=8
hadoop121@ubuntu:~/Dolphin/hadoop-1.2.1$
references：
1.http://dongxicheng.org/mapreduce/run-hadoop-job-problems/
2.http://lucene.472066.n3.nabble.com/Trouble-with-Word-Count-example-td4023269.html
3.http://stackoverflow.com/questions/22850532/warn-mapred-jobclient-no-job-jar-file-set-user-classes-may-not-be-found
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