[英]how to define our own map and reduce class
i want to create map reduce job of my own. 我想创建自己的地图缩小工作。
the map class's output is :Text(key),Text(value) 地图类的输出为:Text(key),Text(value)
the reduce class's output is :Text,Intwritable reduce类的输出是:Text,Intwritable
I tried to implement it in following way: 我尝试通过以下方式实现它:
import java.io.IOException;
import java.util.*;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.util.*;
public class artistandTrack {
public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, Text> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key, Text value, OutputCollector<Text, Text> output, Reporter reporter) throws IOException {
String line = value.toString();
String[] names=line.split(" ");
Text artist_name = new Text(names[2]);
Text track_name = new Text(names[3]);
output.collect(artist_name,track_name);
}
}
public static class Reduce extends MapReduceBase implements Reducer<Text, Text, Text, IntWritable> {
public void reduce(Text key, Iterator<Text> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += 1;
Text x1=values.next();
}
output.collect(key, new IntWritable(sum));
}
}
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(artistandTrack.class);
conf.setJobName("artisttrack");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapOutputKeyClass(Text.class);
conf.setMapOutputValueClass(Text.class);
conf.setMapperClass(Map.class);
conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
}
}
when i try to run it it shows the following output and terminates 当我尝试运行它时,它显示以下输出并终止
WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/10/17 06:09:15 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
14/10/17 06:09:15 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
14/10/17 06:09:16 INFO jvm.JvmMetrics: Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized
14/10/17 06:09:18 WARN mapreduce.JobSubmitter: Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
14/10/17 06:09:19 INFO mapred.FileInputFormat: Total input paths to process : 1
14/10/17 06:09:19 INFO mapreduce.JobSubmitter: number of splits:1
14/10/17 06:09:19 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local803195645_0001
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/staging/userloki803195645/.staging/job_local803195645_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval; Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/staging/userloki803195645/.staging/job_local803195645_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts; Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/local/localRunner/userloki/job_local803195645_0001/job_local803195645_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval; Ignoring.
14/10/17 06:09:20 WARN conf.Configuration: file:/app/hadoop/tmp/mapred/local/localRunner/userloki/job_local803195645_0001/job_local803195645_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts; Ignoring.
14/10/17 06:09:20 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
14/10/17 06:09:20 INFO mapreduce.Job: Running job: job_local803195645_0001
14/10/17 06:09:20 INFO mapred.LocalJobRunner: OutputCommitter set in config null
14/10/17 06:09:20 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapred.FileOutputCommitter
14/10/17 06:09:20 INFO mapred.LocalJobRunner: Waiting for map tasks
14/10/17 06:09:20 INFO mapred.LocalJobRunner: Starting task: attempt_local803195645_0001_m_000000_0
14/10/17 06:09:20 INFO mapred.Task: Using ResourceCalculatorProcessTree : [ ]
14/10/17 06:09:20 INFO mapred.MapTask: Processing split: hdfs://localhost:54310/project5/input/sad.txt:0+272
14/10/17 06:09:21 INFO mapred.MapTask: numReduceTasks: 1
14/10/17 06:09:21 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
14/10/17 06:09:21 INFO mapreduce.Job: Job job_local803195645_0001 running in uber mode : false
14/10/17 06:09:21 INFO mapreduce.Job: map 0% reduce 0%
14/10/17 06:09:22 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
14/10/17 06:09:22 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
14/10/17 06:09:22 INFO mapred.MapTask: soft limit at 83886080
14/10/17 06:09:22 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
14/10/17 06:09:22 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
14/10/17 06:09:25 INFO mapred.LocalJobRunner:
14/10/17 06:09:25 INFO mapred.MapTask: Starting flush of map output
14/10/17 06:09:25 INFO mapred.MapTask: Spilling map output
14/10/17 06:09:25 INFO mapred.MapTask: bufstart = 0; bufend = 120; bufvoid = 104857600
14/10/17 06:09:25 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214384(104857536); length = 13/6553600
14/10/17 06:09:25 INFO mapred.LocalJobRunner: map task executor complete.
14/10/17 06:09:25 WARN mapred.LocalJobRunner: job_local803195645_0001
***java.lang.Exception: java.io.IOException: wrong value class: class org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text
at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:522)
Caused by: java.io.IOException: wrong value class: class org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text
at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:199)
at org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:1307)
at artistandTrack$Reduce.reduce(artistandTrack.java:44)
at artistandTrack$Reduce.reduce(artistandTrack.java:37)
at org.apache.hadoop.mapred.Task$OldCombinerRunner.combine(Task.java:1572)
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.sortAndSpill(MapTask.java:1611)
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.flush(MapTask.java:1462)
at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:437)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:342)
at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:243)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)***
14/10/17 06:09:26 INFO mapreduce.Job: Job job_local803195645_0001 failed with state FAILED due to: NA
14/10/17 06:09:26 INFO mapreduce.Job: Counters: 11
Map-Reduce Framework
Map input records=4
Map output records=4
Map output bytes=120
Map output materialized bytes=0
Input split bytes=97
Combine input records=0
Combine output records=0
Spilled Records=0
Failed Shuffles=0
Merged Map outputs=0
File Input Format Counters
Bytes Read=272
Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:836)
at artistandTrack.main(artistandTrack.java:68)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)
from where the wrong class is coming 从哪里来错课了
java.lang.Exception: java.io.IOException: wrong value class: class org.apache.hadoop.io.IntWritable is not class org.apache.hadoop.io.Text
and 和
why the job fails 为什么工作失败
Exception in thread "main" java.io.IOException: Job failed!
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:836)
at artistandTrack.main(artistandTrack.java:68)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.hadoop.util.RunJar.main(RunJar.java:212)
i dont understand where it's going wrong. 我不明白哪里出了问题。 any help
任何帮助
I think the problem is in line: 我认为这个问题符合要求:
conf.setCombinerClass(Reduce.class);
Your Map
produces a pair of Text
and Text
, then your combiner
takes it and produces a pair of Text
and IntWritable
, but your Reducer
can't accept IntWritable
as value so it throws an exception. Map
会生成一对Text
和Text
,然后您的combiner
会接受它并生成一对Text
和IntWritable
,但是Reducer
不能接受IntWritable
作为值,因此会引发异常。 Try to remove line with Combiner
setting. 尝试使用
Combiner
设置删除行。
Use Main from bellow: 从下面使用Main:
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(artistandTrack.class);
conf.setJobName("artisttrack");
FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
conf.setMapperClass(Map.class);
//conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
//conf.setOutputKeyClass(Text.class);
//conf.setOutputValueClass(IntWritable.class);
conf.setMapOutputKeyClass(Text.class);
conf.setMapOutputValueClass(Text.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
JobClient.runJob(conf);
}
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