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windows10上Eclipse运行MapReduce wordcount程序遇到的坑

时间:2018-03-22 22:34:12      阅读:1471      评论:0      收藏:0      [点我收藏+]

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我的wordcount代码:

  1 package com.walloce.wordcount;
  2 
  3 import java.io.IOException;
  4 import org.apache.hadoop.conf.Configuration;
  5 import org.apache.hadoop.conf.Configured;
  6 import org.apache.hadoop.fs.FileSystem;
  7 import org.apache.hadoop.fs.Path;
  8 import org.apache.hadoop.io.IntWritable;
  9 import org.apache.hadoop.io.LongWritable;
 10 import org.apache.hadoop.io.Text;
 11 import org.apache.hadoop.mapreduce.Job;
 12 import org.apache.hadoop.mapreduce.Mapper;
 13 import org.apache.hadoop.mapreduce.Reducer;
 14 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
 15 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 16 import org.apache.hadoop.util.Tool;
 17 import org.apache.hadoop.util.ToolRunner;
 18 
 19 import com.walloce.wordcount.MyMapReduce.myMap.myReduce;
 20 
 21 public class MyMapReduce extends Configured implements Tool {
 22     
 23     /**
 24      * KEYIN LongWritable 传入的key类型(偏移量)
 25      * VALUEIN Text 传入的value类型(文本)
 26      * KEYOUT 传出的key类型
 27      * VALUEOUT 传出的value类型
 28      * @author Walloce
 29      * 2018
 30      */
 31     static class myMap extends Mapper<LongWritable, Text, Text, IntWritable> {
 32         //输出结果的key
 33         Text text = new Text();
 34         //输出结果的value
 35         IntWritable mr_value = new IntWritable(1);
 36         
 37         int line_count = 1;
 38         
 39         @Override
 40         protected void map(LongWritable key, Text value, Context context)
 41                 throws IOException, InterruptedException {
 42             
 43             System.out.println("map阶段开始...");
 44             //将获取的文本类型转为字符串类型
 45             String line = value.toString();
 46             
 47             System.out.println("第 "+ line_count +" 行的字符串的偏移量为:" + key.get());
 48             
 49             //将的到的一行字符串拆解为多个单词的字符串数组
 50             String[] words = line.split(" ");
 51             
 52             //遍历得到的所有word
 53             for (String word : words) {
 54                 text.set(word);
 55                 context.write(text, mr_value);
 56             }
 57             line_count++;
 58         }
 59         
 60         /**
 61          * Text, IntWritable, Text, IntWritable
 62          * reduce时输入的key-value和输出的key-value.
 63          * eg:(hello,2)
 64          * @author Walloce
 65          * 2018
 66          */
 67         static class myReduce extends Reducer<Text, IntWritable, Text, IntWritable> {
 68             
 69             private IntWritable result = new IntWritable();
 70             
 71             int reduce_time = 0;
 72             
 73             @Override
 74             protected void reduce(Text key, Iterable<IntWritable> values, Context context)
 75                     throws IOException, InterruptedException {
 76                 System.out.println("这是第"+ reduce_time +"次reduce");
 77                 System.out.println("Reduce阶段开始....");
 78                 
 79                 int sum = 0;
 80                 for (IntWritable value : values) {
 81                     sum += value.get();
 82                 }
 83                 result.set(sum);
 84                 context.write(key, result);
 85                 reduce_time++;
 86             }
 87             
 88         }
 89 
 90     }
 91     
 92     public int run(String[] args) throws Exception {
 93         
 94         //hadoop的八股文
 95         Configuration conf = this.getConf();
 96         Job job = Job.getInstance(conf, this.getClass().getSimpleName());
 97         //对job进行具体的配置
 98         
 99         //当你本地运行,这个设置可以不写,不会报错
100         //当提价到集群上面运行的时候,这个设置不写,会报类找不到的异常 
101         job.setJarByClass(MyMapReduce.class);
102         
103         //写一个输入路径
104         Path input = new Path(args[0]);
105         FileInputFormat.addInputPath(job, input);
106         //写一个输出路径
107         Path output = new Path(args[1]);
108         FileOutputFormat.setOutputPath(job, output);
109         
110         //执行前先判断输出路径是否存在,存在就删除
111         FileSystem fs = output.getFileSystem(conf);
112         if(fs.exists(output)){
113             fs.delete(output,true);
114         }
115         
116         //设置运行的map类的相关参数
117         job.setMapperClass(myMap.class);
118         job.setMapOutputKeyClass(Text.class);
119         job.setMapOutputValueClass(IntWritable.class);
120         //==============shuffle=======================
121 //        job.setCombinerClass(MyCombiner.class);
122         
123         
124         //==============shuffle=======================
125         //设置运行的Reduce的相关参数
126         job.setReducerClass(myReduce.class);
127         job.setOutputKeyClass(Text.class);
128         job.setOutputValueClass(IntWritable.class);
129         
130         boolean isSuccess =  job.waitForCompletion(true);
131         
132         
133         return isSuccess?0:1;
134     }
135     
136     public static void main(String[] args) {
137         // TODO Auto-generated method stub
138         Configuration conf = new Configuration();
139         args = new String[]{
140                 "hdfs://bigdata-study-104:8020/testdata/word.txt",
141                 "hdfs://bigdata-study-104:8020/testresult/output/"
142         };
143 
144         try {
145             ToolRunner.run(conf, new MyMapReduce(), args);
146         } catch (Exception e) {
147             // TODO Auto-generated catch block
148             e.printStackTrace();
149         }
150     }
151 
152 }

 

异常信息:

 1 18/03/22 20:41:24 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
 2 18/03/22 20:41:25 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
 3 18/03/22 20:41:25 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
 4 18/03/22 20:41:25 WARN mapreduce.JobSubmitter: No job jar file set.  User classes may not be found. See Job or Job#setJar(String).
 5 18/03/22 20:41:25 INFO input.FileInputFormat: Total input paths to process : 1
 6 18/03/22 20:41:26 INFO mapreduce.JobSubmitter: number of splits:1
 7 18/03/22 20:41:26 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local1064879045_0001
 8 18/03/22 20:41:26 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/staging/Walloce1064879045/.staging/job_local1064879045_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
 9 18/03/22 20:41:26 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/staging/Walloce1064879045/.staging/job_local1064879045_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
10 18/03/22 20:41:26 INFO mapreduce.JobSubmitter: Cleaning up the staging area file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/staging/Walloce1064879045/.staging/job_local1064879045_0001
11 Exception in thread "main" java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
12     at org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)
13     at org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:571)
14     at org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:977)
15     at org.apache.hadoop.util.DiskChecker.checkAccessByFileMethods(DiskChecker.java:173)
16     at org.apache.hadoop.util.DiskChecker.checkDirAccess(DiskChecker.java:160)
17     at org.apache.hadoop.util.DiskChecker.checkDir(DiskChecker.java:94)
18     at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.confChanged(LocalDirAllocator.java:285)
19     at org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:344)
20     at org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:150)
21     at org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:131)
22     at org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:115)
23     at org.apache.hadoop.mapred.LocalDistributedCacheManager.setup(LocalDistributedCacheManager.java:131)
24     at org.apache.hadoop.mapred.LocalJobRunner$Job.<init>(LocalJobRunner.java:163)
25     at org.apache.hadoop.mapred.LocalJobRunner.submitJob(LocalJobRunner.java:731)
26     at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:432)
27     at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1285)
28     at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1282)
29     at java.security.AccessController.doPrivileged(Native Method)
30     at javax.security.auth.Subject.doAs(Unknown Source)
31     at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
32     at org.apache.hadoop.mapreduce.Job.submit(Job.java:1282)
33     at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1303)
34     at com.walloce.wordcount.MyMapReduce.run(MyMapReduce.java:130)
35     at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
36     at com.walloce.wordcount.MyMapReduce.main(MyMapReduce.java:145)

 

修改代码:将570行注释掉,直接return true;

技术分享图片

 

再运行还是报错!!!

  1 18/03/22 20:53:42 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
  2 18/03/22 20:53:42 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
  3 18/03/22 20:53:42 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
  4 18/03/22 20:53:43 WARN mapreduce.JobSubmitter: No job jar file set.  User classes may not be found. See Job or Job#setJar(String).
  5 18/03/22 20:53:43 INFO input.FileInputFormat: Total input paths to process : 1
  6 18/03/22 20:53:43 INFO mapreduce.JobSubmitter: number of splits:1
  7 18/03/22 20:53:43 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local105563724_0001
  8 18/03/22 20:53:43 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
  9 18/03/22 20:53:43 INFO mapreduce.Job: Running job: job_local105563724_0001
 10 18/03/22 20:53:43 INFO mapred.LocalJobRunner: OutputCommitter set in config null
 11 18/03/22 20:53:43 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
 12 18/03/22 20:53:43 INFO mapred.LocalJobRunner: Waiting for map tasks
 13 18/03/22 20:53:43 INFO mapred.LocalJobRunner: Starting task: attempt_local105563724_0001_m_000000_0
 14 18/03/22 20:53:43 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
 15 18/03/22 20:53:43 INFO mapred.Task:  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@4a86a3cd
 16 18/03/22 20:53:43 INFO mapred.MapTask: Processing split: hdfs://bigdata-study-104:8020/testdata/word.txt:0+210
 17 18/03/22 20:53:43 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
 18 18/03/22 20:53:43 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
 19 18/03/22 20:53:43 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
 20 18/03/22 20:53:43 INFO mapred.MapTask: soft limit at 83886080
 21 18/03/22 20:53:43 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
 22 18/03/22 20:53:43 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
 23 map阶段开始...
 24 第 1 行的字符串的偏移量为:0
 25 map阶段开始...
 26 第 2 行的字符串的偏移量为:46
 27 map阶段开始...
 28 第 3 行的字符串的偏移量为:86
 29 map阶段开始...
 30 第 4 行的字符串的偏移量为:120
 31 map阶段开始...
 32 第 5 行的字符串的偏移量为:149
 33 map阶段开始...
 34 第 6 行的字符串的偏移量为:172
 35 map阶段开始...
 36 第 7 行的字符串的偏移量为:190
 37 map阶段开始...
 38 第 8 行的字符串的偏移量为:204
 39 18/03/22 20:53:44 INFO mapred.LocalJobRunner: 
 40 18/03/22 20:53:44 INFO mapred.MapTask: Starting flush of map output
 41 18/03/22 20:53:44 INFO mapred.MapTask: Spilling map output
 42 18/03/22 20:53:44 INFO mapred.MapTask: bufstart = 0; bufend = 348; bufvoid = 104857600
 43 18/03/22 20:53:44 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214256(104857024); length = 141/6553600
 44 18/03/22 20:53:44 INFO mapred.MapTask: Finished spill 0
 45 18/03/22 20:53:44 INFO mapred.Task: Task:attempt_local105563724_0001_m_000000_0 is done. And is in the process of committing
 46 18/03/22 20:53:44 INFO mapred.LocalJobRunner: map
 47 18/03/22 20:53:44 INFO mapred.Task: Task ‘attempt_local105563724_0001_m_000000_0‘ done.
 48 18/03/22 20:53:44 INFO mapred.LocalJobRunner: Finishing task: attempt_local105563724_0001_m_000000_0
 49 18/03/22 20:53:44 INFO mapred.LocalJobRunner: map task executor complete.
 50 18/03/22 20:53:44 INFO mapred.LocalJobRunner: Waiting for reduce tasks
 51 18/03/22 20:53:44 INFO mapred.LocalJobRunner: Starting task: attempt_local105563724_0001_r_000000_0
 52 18/03/22 20:53:44 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
 53 18/03/22 20:53:44 INFO mapred.Task:  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@66a2f2c4
 54 18/03/22 20:53:44 INFO mapred.ReduceTask: Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@7c3f147f
 55 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: MergerManager: memoryLimit=1323407744, maxSingleShuffleLimit=330851936, mergeThreshold=873449152, ioSortFactor=10, memToMemMergeOutputsThreshold=10
 56 18/03/22 20:53:44 INFO reduce.EventFetcher: attempt_local105563724_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
 57 18/03/22 20:53:44 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local105563724_0001_m_000000_0 decomp: 422 len: 426 to MEMORY
 58 18/03/22 20:53:44 INFO reduce.InMemoryMapOutput: Read 422 bytes from map-output for attempt_local105563724_0001_m_000000_0
 59 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 422, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->422
 60 18/03/22 20:53:44 INFO reduce.EventFetcher: EventFetcher is interrupted.. Returning
 61 18/03/22 20:53:44 INFO mapred.LocalJobRunner: 1 / 1 copied.
 62 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
 63 18/03/22 20:53:44 INFO mapred.Merger: Merging 1 sorted segments
 64 18/03/22 20:53:44 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 413 bytes
 65 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: Merged 1 segments, 422 bytes to disk to satisfy reduce memory limit
 66 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: Merging 1 files, 426 bytes from disk
 67 18/03/22 20:53:44 INFO reduce.MergeManagerImpl: Merging 0 segments, 0 bytes from memory into reduce
 68 18/03/22 20:53:44 INFO mapred.Merger: Merging 1 sorted segments
 69 18/03/22 20:53:44 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 413 bytes
 70 18/03/22 20:53:44 INFO mapred.LocalJobRunner: 1 / 1 copied.
 71 18/03/22 20:53:44 INFO mapred.LocalJobRunner: reduce task executor complete.
 72 18/03/22 20:53:44 WARN mapred.LocalJobRunner: job_local105563724_0001
 73 java.lang.Exception: java.lang.NoSuchMethodError: org.apache.hadoop.fs.FSOutputSummer.<init>(Ljava/util/zip/Checksum;II)V
 74     at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
 75     at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:529)
 76 Caused by: java.lang.NoSuchMethodError: org.apache.hadoop.fs.FSOutputSummer.<init>(Ljava/util/zip/Checksum;II)V
 77     at org.apache.hadoop.hdfs.DFSOutputStream.<init>(DFSOutputStream.java:1563)
 78     at org.apache.hadoop.hdfs.DFSOutputStream.<init>(DFSOutputStream.java:1594)
 79     at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:1626)
 80     at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1488)
 81     at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1413)
 82     at org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:387)
 83     at org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:383)
 84     at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
 85     at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:383)
 86     at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:327)
 87     at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
 88     at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
 89     at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
 90     at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.getRecordWriter(TextOutputFormat.java:132)
 91     at org.apache.hadoop.mapred.ReduceTask$NewTrackingRecordWriter.<init>(ReduceTask.java:540)
 92     at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:614)
 93     at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:389)
 94     at org.apache.hadoop.mapred.LocalJobRunner$Job$ReduceTaskRunnable.run(LocalJobRunner.java:319)
 95     at java.util.concurrent.Executors$RunnableAdapter.call(Unknown Source)
 96     at java.util.concurrent.FutureTask.run(Unknown Source)
 97     at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
 98     at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
 99     at java.lang.Thread.run(Unknown Source)
100 18/03/22 20:53:44 INFO mapreduce.Job: Job job_local105563724_0001 running in uber mode : false
101 18/03/22 20:53:44 INFO mapreduce.Job:  map 100% reduce 0%
102 18/03/22 20:53:44 INFO mapreduce.Job: Job job_local105563724_0001 failed with state FAILED due to: NA
103 18/03/22 20:53:44 INFO mapreduce.Job: Counters: 38
104     File System Counters
105         FILE: Number of bytes read=175
106         FILE: Number of bytes written=262184
107         FILE: Number of read operations=0
108         FILE: Number of large read operations=0
109         FILE: Number of write operations=0
110         HDFS: Number of bytes read=210
111         HDFS: Number of bytes written=0
112         HDFS: Number of read operations=6
113         HDFS: Number of large read operations=0
114         HDFS: Number of write operations=2
115     Map-Reduce Framework
116         Map input records=8
117         Map output records=36
118         Map output bytes=348
119         Map output materialized bytes=426
120         Input split bytes=112
121         Combine input records=0
122         Combine output records=0
123         Reduce input groups=0
124         Reduce shuffle bytes=426
125         Reduce input records=0
126         Reduce output records=0
127         Spilled Records=36
128         Shuffled Maps =1
129         Failed Shuffles=0
130         Merged Map outputs=1
131         GC time elapsed (ms)=0
132         CPU time spent (ms)=0
133         Physical memory (bytes) snapshot=0
134         Virtual memory (bytes) snapshot=0
135         Total committed heap usage (bytes)=232783872
136     Shuffle Errors
137         BAD_ID=0
138         CONNECTION=0
139         IO_ERROR=0
140         WRONG_LENGTH=0
141         WRONG_MAP=0
142         WRONG_REDUCE=0
143     File Input Format Counters 
144         Bytes Read=210
145     File Output Format Counters 
146         Bytes Written=0

 

主要异常信息:

 1 java.lang.Exception: java.lang.NoSuchMethodError: org.apache.hadoop.fs.FSOutputSummer.<init>(Ljava/util/zip/Checksum;II)V 

 

好不容易解决一个,又来一个....要崩溃了,继续百度!

问题大致的原因是因为jar包冲突了,所以我buildpath看下导入的jar包有哪些,结果发现问题了。。。。。

技术分享图片

 

同时存在cdh版本的和apache版本的hadoop-common-2.5.0jar包,删掉cdh版本的后运行结果:

  1 18/03/22 20:57:26 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
  2 18/03/22 20:57:26 INFO Configuration.deprecation: session.id is deprecated. Instead, use dfs.metrics.session-id
  3 18/03/22 20:57:26 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
  4 18/03/22 20:57:27 WARN mapreduce.JobSubmitter: No job jar file set.  User classes may not be found. See Job or Job#setJar(String).
  5 18/03/22 20:57:27 INFO input.FileInputFormat: Total input paths to process : 1
  6 18/03/22 20:57:27 INFO mapreduce.JobSubmitter: number of splits:1
  7 18/03/22 20:57:27 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_local1889225814_0001
  8 18/03/22 20:57:27 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/staging/Walloce1889225814/.staging/job_local1889225814_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
  9 18/03/22 20:57:27 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/staging/Walloce1889225814/.staging/job_local1889225814_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
 10 18/03/22 20:57:27 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/local/localRunner/Walloce/job_local1889225814_0001/job_local1889225814_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
 11 18/03/22 20:57:27 WARN conf.Configuration: file:/opt/modules/cdh/hadoop-2.5.0-cdh5.3.6/data/temp/mapred/local/localRunner/Walloce/job_local1889225814_0001/job_local1889225814_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
 12 18/03/22 20:57:27 INFO mapreduce.Job: The url to track the job: http://localhost:8080/
 13 18/03/22 20:57:27 INFO mapreduce.Job: Running job: job_local1889225814_0001
 14 18/03/22 20:57:27 INFO mapred.LocalJobRunner: OutputCommitter set in config null
 15 18/03/22 20:57:27 INFO mapred.LocalJobRunner: OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
 16 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Waiting for map tasks
 17 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Starting task: attempt_local1889225814_0001_m_000000_0
 18 18/03/22 20:57:28 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
 19 18/03/22 20:57:28 INFO mapred.Task:  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@73a61b48
 20 18/03/22 20:57:28 INFO mapred.MapTask: Processing split: hdfs://bigdata-study-104:8020/testdata/word.txt:0+210
 21 18/03/22 20:57:28 INFO mapred.MapTask: Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer
 22 18/03/22 20:57:28 INFO mapred.MapTask: (EQUATOR) 0 kvi 26214396(104857584)
 23 18/03/22 20:57:28 INFO mapred.MapTask: mapreduce.task.io.sort.mb: 100
 24 18/03/22 20:57:28 INFO mapred.MapTask: soft limit at 83886080
 25 18/03/22 20:57:28 INFO mapred.MapTask: bufstart = 0; bufvoid = 104857600
 26 18/03/22 20:57:28 INFO mapred.MapTask: kvstart = 26214396; length = 6553600
 27 map阶段开始...
 28 第 1 行的字符串的偏移量为:0
 29 map阶段开始...
 30 第 2 行的字符串的偏移量为:46
 31 map阶段开始...
 32 第 3 行的字符串的偏移量为:86
 33 map阶段开始...
 34 第 4 行的字符串的偏移量为:120
 35 map阶段开始...
 36 第 5 行的字符串的偏移量为:149
 37 map阶段开始...
 38 第 6 行的字符串的偏移量为:172
 39 map阶段开始...
 40 第 7 行的字符串的偏移量为:190
 41 map阶段开始...
 42 第 8 行的字符串的偏移量为:204
 43 18/03/22 20:57:28 INFO mapred.LocalJobRunner: 
 44 18/03/22 20:57:28 INFO mapred.MapTask: Starting flush of map output
 45 18/03/22 20:57:28 INFO mapred.MapTask: Spilling map output
 46 18/03/22 20:57:28 INFO mapred.MapTask: bufstart = 0; bufend = 348; bufvoid = 104857600
 47 18/03/22 20:57:28 INFO mapred.MapTask: kvstart = 26214396(104857584); kvend = 26214256(104857024); length = 141/6553600
 48 18/03/22 20:57:28 INFO mapred.MapTask: Finished spill 0
 49 18/03/22 20:57:28 INFO mapred.Task: Task:attempt_local1889225814_0001_m_000000_0 is done. And is in the process of committing
 50 18/03/22 20:57:28 INFO mapred.LocalJobRunner: map
 51 18/03/22 20:57:28 INFO mapred.Task: Task ‘attempt_local1889225814_0001_m_000000_0‘ done.
 52 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Finishing task: attempt_local1889225814_0001_m_000000_0
 53 18/03/22 20:57:28 INFO mapred.LocalJobRunner: map task executor complete.
 54 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Waiting for reduce tasks
 55 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Starting task: attempt_local1889225814_0001_r_000000_0
 56 18/03/22 20:57:28 INFO util.ProcfsBasedProcessTree: ProcfsBasedProcessTree currently is supported only on Linux.
 57 18/03/22 20:57:28 INFO mapred.Task:  Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@504037fc
 58 18/03/22 20:57:28 INFO mapred.ReduceTask: Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@1de1d428
 59 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: MergerManager: memoryLimit=1323407744, maxSingleShuffleLimit=330851936, mergeThreshold=873449152, ioSortFactor=10, memToMemMergeOutputsThreshold=10
 60 18/03/22 20:57:28 INFO reduce.EventFetcher: attempt_local1889225814_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events
 61 18/03/22 20:57:28 INFO reduce.LocalFetcher: localfetcher#1 about to shuffle output of map attempt_local1889225814_0001_m_000000_0 decomp: 422 len: 426 to MEMORY
 62 18/03/22 20:57:28 INFO reduce.InMemoryMapOutput: Read 422 bytes from map-output for attempt_local1889225814_0001_m_000000_0
 63 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: closeInMemoryFile -> map-output of size: 422, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->422
 64 18/03/22 20:57:28 INFO reduce.EventFetcher: EventFetcher is interrupted.. Returning
 65 18/03/22 20:57:28 INFO mapred.LocalJobRunner: 1 / 1 copied.
 66 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs
 67 18/03/22 20:57:28 INFO mapred.Merger: Merging 1 sorted segments
 68 18/03/22 20:57:28 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 413 bytes
 69 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: Merged 1 segments, 422 bytes to disk to satisfy reduce memory limit
 70 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: Merging 1 files, 426 bytes from disk
 71 18/03/22 20:57:28 INFO reduce.MergeManagerImpl: Merging 0 segments, 0 bytes from memory into reduce
 72 18/03/22 20:57:28 INFO mapred.Merger: Merging 1 sorted segments
 73 18/03/22 20:57:28 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 413 bytes
 74 18/03/22 20:57:28 INFO mapred.LocalJobRunner: 1 / 1 copied.
 75 18/03/22 20:57:28 INFO Configuration.deprecation: mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords
 76 这是第0次reduce
 77 Reduce阶段开始....
 78 这是第1次reduce
 79 Reduce阶段开始....
 80 这是第2次reduce
 81 Reduce阶段开始....
 82 这是第3次reduce
 83 Reduce阶段开始....
 84 这是第4次reduce
 85 Reduce阶段开始....
 86 这是第5次reduce
 87 Reduce阶段开始....
 88 这是第6次reduce
 89 Reduce阶段开始....
 90 这是第7次reduce
 91 Reduce阶段开始....
 92 18/03/22 20:57:28 INFO mapred.Task: Task:attempt_local1889225814_0001_r_000000_0 is done. And is in the process of committing
 93 18/03/22 20:57:28 INFO mapred.LocalJobRunner: 1 / 1 copied.
 94 18/03/22 20:57:28 INFO mapred.Task: Task attempt_local1889225814_0001_r_000000_0 is allowed to commit now
 95 18/03/22 20:57:28 INFO output.FileOutputCommitter: Saved output of task ‘attempt_local1889225814_0001_r_000000_0‘ to hdfs://bigdata-study-104:8020/testresult/output/_temporary/0/task_local1889225814_0001_r_000000
 96 18/03/22 20:57:28 INFO mapred.LocalJobRunner: reduce > reduce
 97 18/03/22 20:57:28 INFO mapred.Task: Task ‘attempt_local1889225814_0001_r_000000_0‘ done.
 98 18/03/22 20:57:28 INFO mapred.LocalJobRunner: Finishing task: attempt_local1889225814_0001_r_000000_0
 99 18/03/22 20:57:28 INFO mapred.LocalJobRunner: reduce task executor complete.
100 18/03/22 20:57:28 INFO mapreduce.Job: Job job_local1889225814_0001 running in uber mode : false
101 18/03/22 20:57:28 INFO mapreduce.Job:  map 100% reduce 100%
102 18/03/22 20:57:28 INFO mapreduce.Job: Job job_local1889225814_0001 completed successfully
103 18/03/22 20:57:28 INFO mapreduce.Job: Counters: 38
104     File System Counters
105         FILE: Number of bytes read=1234
106         FILE: Number of bytes written=508548
107         FILE: Number of read operations=0
108         FILE: Number of large read operations=0
109         FILE: Number of write operations=0
110         HDFS: Number of bytes read=420
111         HDFS: Number of bytes written=61
112         HDFS: Number of read operations=15
113         HDFS: Number of large read operations=0
114         HDFS: Number of write operations=6
115     Map-Reduce Framework
116         Map input records=8
117         Map output records=36
118         Map output bytes=348
119         Map output materialized bytes=426
120         Input split bytes=112
121         Combine input records=0
122         Combine output records=0
123         Reduce input groups=8
124         Reduce shuffle bytes=426
125         Reduce input records=36
126         Reduce output records=8
127         Spilled Records=72
128         Shuffled Maps =1
129         Failed Shuffles=0
130         Merged Map outputs=1
131         GC time elapsed (ms)=0
132         CPU time spent (ms)=0
133         Physical memory (bytes) snapshot=0
134         Virtual memory (bytes) snapshot=0
135         Total committed heap usage (bytes)=471859200
136     Shuffle Errors
137         BAD_ID=0
138         CONNECTION=0
139         IO_ERROR=0
140         WRONG_LENGTH=0
141         WRONG_MAP=0
142         WRONG_REDUCE=0
143     File Input Format Counters 
144         Bytes Read=210
145     File Output Format Counters 
146         Bytes Written=61

运行成功,在dfs上看到运行的结果文件!!

 技术分享图片

 

参考:https://getpocket.com/a/read/2123376367 解决问题。

 

windows10上Eclipse运行MapReduce wordcount程序遇到的坑

标签:let   sort   counter   actor   tps   record   oca   etl   package   

原文地址:https://www.cnblogs.com/yin1361866686/p/8626647.html

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