wordcount报错：org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist:

Exception in thread "main" org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: hdfs://192.168.25.128:9000/export/yang/log.1
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:323)
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:265)
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:387)
at org.apache.hadoop.mapreduce.JobSubmitter.writeNewSplits(JobSubmitter.java:301)
at org.apache.hadoop.mapreduce.JobSubmitter.writeSplits(JobSubmitter.java:318)
at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:196)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1290)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1287)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287)
at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1308)
at hadoop1.WordCount.main(WordCount.java:53)

当本人在运行，Hadoop集群自带的wordcount实例的时候，报错内容为输入路径不存在，在网上找了很久没有解决，最后发现是因为我创建的log.1是在本地创建的，并没有上传到hdfs集群中，所以在运行的时候会报错，解决的办法是：执行命令：

[root@master ~]# hadoop fs -put log.1 / #（将log.1文件上传到/目录下）

操作之后可以再次运行命令：

[root@master ~]# hadoop jar /export/servers/hadoop/hadoop-2.7.3/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.3.jar wordcount /1.log /result

执行结果如下：

File System Counters
FILE: Number of bytes read=312
FILE: Number of bytes written=237571
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=300
HDFS: Number of bytes written=206
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)=7544
Total time spent by all reduces in occupied slots (ms)=5156
Total time spent by all map tasks (ms)=7544
Total time spent by all reduce tasks (ms)=5156
Total vcore-milliseconds taken by all map tasks=7544
Total vcore-milliseconds taken by all reduce tasks=5156
Total megabyte-milliseconds taken by all map tasks=7725056
Total megabyte-milliseconds taken by all reduce tasks=5279744
Map-Reduce Framework
Map input records=1
Map output records=35
Map output bytes=342
Map output materialized bytes=312
Input split bytes=97
Combine input records=35
Combine output records=25
Reduce input groups=25
Reduce shuffle bytes=312
Reduce input records=25
Reduce output records=25
Spilled Records=50
Shuffled Maps =1
Failed Shuffles=0
Merged Map outputs=1
GC time elapsed (ms)=230
CPU time spent (ms)=2110
Physical memory (bytes) snapshot=306843648
Virtual memory (bytes) snapshot=4163534848
Total committed heap usage (bytes)=142278656
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=203
File Output Format Counters
Bytes Written=206

运行成功！

原文链接：https://blog.csdn.net/yangmingtia/article/details/83993206