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:

18/11/12 14:55:18 INFO client.RMProxy: Connecting to ResourceManager at /192.168.25.128:8032
18/11/12 14:55:19 INFO input.FileInputFormat: Total input paths to process : 1
18/11/12 14:55:19 INFO mapreduce.JobSubmitter: number of splits:1
18/11/12 14:55:19 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1542005142273_0001
18/11/12 14:55:20 INFO impl.YarnClientImpl: Submitted application application_1542005142273_0001
18/11/12 14:55:20 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1542005142273_0001/
18/11/12 14:55:20 INFO mapreduce.Job: Running job: job_1542005142273_0001
18/11/12 14:55:32 INFO mapreduce.Job: Job job_1542005142273_0001 running in uber mode : false
18/11/12 14:55:32 INFO mapreduce.Job:  map 0% reduce 0%
18/11/12 14:55:43 INFO mapreduce.Job:  map 100% reduce 0%
18/11/12 14:55:51 INFO mapreduce.Job:  map 100% reduce 100%
18/11/12 14:55:51 INFO mapreduce.Job: Job job_1542005142273_0001 completed successfully
18/11/12 14:55:51 INFO mapreduce.Job: Counters: 49
        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!

Exception in thread "main" org.apache.hadoop.mapreduce.lib.input.InvalidInputException: 回答: 这个错误通常是由于输入路径不存在导致的。根据引用\[2\]的解释,当使用Eclipse运行MapReduce程序时,默认的参数是单机参数,而不是HDFS目录。因此,如果输入路径在HDFS中不存在,就会出现这个错误。解决这个问题的方法是在项目的src下加入core-site.xml和hdfs-site.xml两个文件,并将它们复制到WordCount项目的src文件夹中。这样,程序就能正确读取HDFS中的输入路径了。 #### 引用[.reference_title] - *1* *3* [Exception in thread "main" org.apache.hadoop.mapred.InvalidJobConfException: Output directory not se](https://blog.csdn.net/mtj66/article/details/52644800)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item] - *2* [错误Exception in thread “main“ org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input ...](https://blog.csdn.net/m0_60318777/article/details/121398932)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item] [ .reference_list ]
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