MapReduce报错:「MKDirs failed to create file」
文章目录
0. 写在前面
- Linux:
Ubuntu Kylin16.04
- Hadoop:
Hadoop2.7.2
1. 程序代码及报错信息
输入、输出路径
zhangsan@hadoop01:/$ ll | grep input
drwxr-xr-x 3 zhangsan zhangsan 4096 9月 20 03:35 input/
zhangsan@hadoop01:/$ ll | grep output
zhangsan@hadoop01:/$
程序代码
package com.mr.ch07.maxmin;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
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;
public class MinMaxValueDemo7_2_1 {
public static class MinMaxMapper extends Mapper<Object, Text, Text, MinMaxWritable> {
private MinMaxWritable outTuple = new MinMaxWritable();
@Override
public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
String[] strs = value.toString().split(" ");
String strDate = strs[0];// 定义记录日期的字符串变量strDate
if (strDate == null) {
return;// 如果该日期值为空,则返回
}
System.out.println(strs[0] + ",,,," + strs[1]);
// 将值即做为最大值又做为最小值存储到自定义Writable类MinMaxWritable中。
outTuple.setMin(Integer.parseInt(strs[1]));
outTuple.setMax(Integer.parseInt(strs[1]));
// 将结果写入上下文
context.write(new Text(strDate), outTuple);
}
}
public static class MinMaxReducer extends Reducer<Text, MinMaxWritable, Text, MinMaxWritable> {
private MinMaxWritable result = new MinMaxWritable();
@Override
public void reduce(Text key, Iterable<MinMaxWritable> values, Context context)
throws IOException, InterruptedException {
result.setMax(0);
result.setMin(0);
// 按key迭代输出value的值
for (MinMaxWritable val : values) {
// 最小值放于结果集中
if (result.getMin() == 0 || val.getMin() < result.getMin()) {
result.setMin(val.getMin());
}
// 最大值放于结果集中
if (result.getMax() == 0 || val.getMax() > result.getMax()) {
System.out.println("val.getMax(): " + val.getMax() + ",,,,"
+ result.getMax());
result.setMax(val.getMax());
}
}
context.write(key, result);
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
// String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
String[] otherArgs = new String[] { "/input/ch07/minmax", "/output/ch07/minmax" };
if (otherArgs.length != 2) {
System.err.println("Usage: MinMaxCountDriver <in> <out>");
System.exit(2);
}
// Job job = new Job(conf, "StackOverflow Comment Date Min Max Count");
Job job = Job.getInstance(conf);
job.setJarByClass(MinMaxValueDemo7_2_1.class);
job.setMapperClass(MinMaxMapper.class);
job.setCombinerClass(MinMaxReducer.class);
job.setReducerClass(MinMaxReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(MinMaxWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
public static class MinMaxWritable implements Writable {
private int min;// 记录最小值
private int max;// 记录最大值
public int getMin() {
return min;
}
public void setMin(int min) {
this.min = min;
}
public int getMax() {
return max;
}
public void setMax(int max) {
this.max = max;
}
@Override
public void readFields(DataInput in) throws IOException {
min = in.readInt();
max = in.readInt();
}
@Override
public void write(DataOutput out) throws IOException {
out.writeInt(max);
out.writeInt(min);
}
@Override
public String toString() {
return max + "\t" + min;
}
}
}
报错信息
java.lang.Exception: java.io.IOException: Mkdirs failed to create file:/output/ch07/minmax/_temporary/0/_temporary/attempt_local391816241_0001_r_000000_0 (exists=false, cwd=file:/home/zhangsan/Java_Eclipse/eclipse-workspace/MapReduce)
at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:529)
Caused by: java.io.IOException: Mkdirs failed to create file:/output/ch07/minmax/_temporary/0/_temporary/attempt_local391816241_0001_r_000000_0 (exists=false, cwd=file:/home/zhangsan/Java_Eclipse/eclipse-workspace/MapReduce)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:449)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:435)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:909)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:890)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:787)
at org.apache.hadoop.mapreduce.lib.output.TextOutputFormat.getRecordWriter(TextOutputFormat.java:132)
at org.apache.hadoop.mapred.ReduceTask$NewTrackingRecordWriter.<init>(ReduceTask.java:540)
at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:614)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:389)
at org.apache.hadoop.mapred.LocalJobRunner$Job$ReduceTaskRunnable.run(LocalJobRunner.java:319)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2022-09-21 20:42:24,059 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1360)) - Job job_local391816241_0001 running in uber mode : false
2022-09-21 20:42:24,062 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1367)) - map 100% reduce 0%
2022-09-21 20:42:24,064 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1380)) - Job job_local391816241_0001 failed with state FAILED due to: NA
2022-09-21 20:42:24,080 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1385)) - Counters: 30
File System Counters
FILE: Number of bytes read=247
FILE: Number of bytes written=269461
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
Map-Reduce Framework
Map input records=8
Map output records=8
Map output bytes=128
Map output materialized bytes=60
Input split bytes=97
Combine input records=8
Combine output records=3
Reduce input groups=0
Reduce shuffle bytes=60
Reduce input records=0
Reduce output records=0
Spilled Records=3
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=0
Total committed heap usage (bytes)=193986560
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=96
File Output Format Counters
Bytes Written=0
2. 查找资料
网上有一个帖子提到了这个报错信息
https://community.cloudera.com/t5/Support-Questions/MKDirs-failed-to-create-file/td-p/35041
根据@snm1523的回答,我尝试将mapred-site.xml
添加如下内容
<property>
<name>mapreduce.jobtracker.address</name>
<value>localhost:9101</value>
</property>
3. 原因分析
输出路径不能
create
,那就先创建输出路径
- 创建输出路径目录/output
zhangsan@hadoop01:/$ sudo mkdir /output
[sudo] zhangsan 的密码:
zhangsan@hadoop01:/$ ll | grep output
drwxr-xr-x 2 root root 4096 9月 21 20:43 output/
依旧跟前面一样的报错信息
创建了路径还是报错,那应该是涉及到
权限问题
- 修改
/output
目录权限为当前用户
「即hadoop安装目录所在的所有者」
zhangsan@hadoop01:/$ sudo chown -R zhangsan:zhangsan output/
zhangsan@hadoop01:/$ ll | grep output
drwxr-xr-x 2 zhangsan zhangsan 4096 9月 21 20:43 output/
重新执行MR程序
- 运行成功
2022-09-21 20:44:53,945 INFO [Thread-15] mapred.LocalJobRunner (LocalJobRunner.java:runTasks(456)) - reduce task executor complete.
2022-09-21 20:44:54,597 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1360)) - Job job_local2141955672_0001 running in uber mode : false
2022-09-21 20:44:54,600 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1367)) - map 100% reduce 100%
2022-09-21 20:44:54,602 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1378)) - Job job_local2141955672_0001 completed successfully
2022-09-21 20:44:54,615 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1385)) - Counters: 30
File System Counters
FILE: Number of bytes read=646
FILE: Number of bytes written=541974
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
Map-Reduce Framework
Map input records=8
Map output records=8
Map output bytes=128
Map output materialized bytes=60
Input split bytes=97
Combine input records=8
Combine output records=3
Reduce input groups=3
Reduce shuffle bytes=60
Reduce input records=3
Reduce output records=3
Spilled Records=6
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=0
Total committed heap usage (bytes)=387973120
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=96
File Output Format Counters
Bytes Written=60
- 查看结果
zhangsan@hadoop01:/output/ch07/minmax$ ll
总用量 20
drwxrwxr-x 2 zhangsan zhangsan 4096 9月 21 20:44 ./
drwxrwxr-x 3 zhangsan zhangsan 4096 9月 21 20:44 ../
-rw-r--r-- 1 zhangsan zhangsan 48 9月 21 20:44 part-r-00000
-rw-r--r-- 1 zhangsan zhangsan 12 9月 21 20:44 .part-r-00000.crc
-rw-r--r-- 1 zhangsan zhangsan 0 9月 21 20:44 _SUCCESS
-rw-r--r-- 1 zhangsan zhangsan 8 9月 21 20:44 ._SUCCESS.crc
4. 参考
https://community.cloudera.com/t5/Support-Questions/MKDirs-failed-to-create-file/td-p/35041
顺利结束
本文来自博客园,作者:{WHYBIGDATA},转载请注明原文链接:https://www.cnblogs.com/shadowlim/p/17051767.html