Error launching job , bad input path

最新推荐文章于 2024-05-01 10:45:44 发布

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#Hadoop

本文介绍了一个关于使用Python的mrjob库在Hadoop集群上运行PegasosSVM算法时遇到的问题及解决过程。主要错误在于作业启动失败，并指向了文件路径不存在的问题。通过调整Hadoop配置文件并重新格式化namenode，最终解决了该问题。

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python /home/hduser/Workspace/Ch5_Py_mrjob_PegasosSVM/mrSVM.py -r hadoop < Workspace/Ch5_Py_mrjob_PegasosSVM/kickStart.txt

之前顺利执行过一次，也尝试过格式话namenode；重新删除建立data文件夹，问题仍然存在：
报错：

No handlers could be found for logger "mrjob.launch"
No configs found; falling back on auto-configuration
No configs specified for hadoop runner
Looking for hadoop binary in /usr/local/hadoop/bin...
Found hadoop binary: /usr/local/hadoop/bin/hadoop
Using Hadoop version 2.7.5
Looking for Hadoop streaming jar in /usr/local/hadoop...
Found Hadoop streaming jar: /usr/local/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.7.5.jar
Creating temp directory /tmp/mrSVM.hduser.20180604.015226.736070
reading from STDIN
Copying local files to hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/files/...
Running step 1 of 2...
  session.id is deprecated. Instead, use dfs.metrics.session-id
  Initializing JVM Metrics with processName=JobTracker, sessionId=
  Cannot initialize JVM Metrics with processName=JobTracker, sessionId= - already initialized
  Cleaning up the staging area file:/usr/local/hadoop/hadoop_data/mapred/staging/hduser854512016/.staging/job_local854512016_0001
  Error launching job , bad input path : File does not exist: /usr/local/hadoop/hadoop_data/mapred/staging/hduser854512016/.staging/job_local854512016_0001/files/mrSVM.py#mrSVM.py
  Streaming Command Failed!
Attempting to fetch counters from logs...
Can't fetch history log; missing job ID
No counters found
Scanning logs for probable cause of failure...
Can't fetch history log; missing job ID
Can't fetch task logs; missing application ID
Step 1 of 2 failed: Command '['/usr/local/hadoop/bin/hadoop', 'jar', '/usr/local/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.7.5.jar', '-files', 'hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/files/mrSVM.py#mrSVM.py,hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/files/mrjob.zip#mrjob.zip,hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/files/setup-wrapper.sh#setup-wrapper.sh', '-input', 'hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/files/STDIN', '-output', 'hdfs:///user/hduser/tmp/mrjob/mrSVM.hduser.20180604.015226.736070/step-output/0000', '-mapper', 'sh -ex setup-wrapper.sh python mrSVM.py --step-num=0 --mapper', '-reducer', 'sh -ex setup-wrapper.sh python mrSVM.py --step-num=0 --reducer']' returned non-zero exit status 512

解决办法：
在网上查询得到：在master和各个节点执行以下操作：
core-site.xml

<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://localhost:9000</value>
    </property>
 <property>
      <name>hadoop.tmp.dir</name>
      <value>file:///usr/local/hadoop/hadoop_data</value>
      <description>A base for other temporary directories.</description>
    </property>
</configuration>

hdfs-site.xml


<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
 <property>
      <name>hadoop.tmp.dir</name>
    <value>file:///usr/local/hadoop/hadoop_data</value>
      <description>A base for other temporary directories.</description>
    </property>
</configuration>

mapred-site.xml


<configuration>
  <property> 
    <name>mapreduce.framework.name</name> 
    <value>yarn</value> 
  </property>
</configuration>

yarn-site.xml


<configuration>

    <!-- Site specific YARN configuration properties -->
    <property>
        <name>yarn.scheduler.minimum-allocation-mb</name>
        <value>128</value>
        <description>Minimum limit of memory to allocate to each container request at the Resource Manager.</description>
    </property>
    <property>
        <name>yarn.scheduler.maximum-allocation-mb</name>
        <value>2048</value>
        <description>Maximum limit of memory to allocate to each container request at the Resource Manager.</description>
    </property>
    <property>
        <name>yarn.scheduler.minimum-allocation-vcores</name>
        <value>1</value>
        <description>The minimum allocation for every container request at the RM, in terms of virtual CPU cores. Requests lower than this won't take effect, and the specified value will get allocated the minimum.</description>
    </property>
    <property>
        <name>yarn.scheduler.maximum-allocation-vcores</name>
        <value>2</value>
        <description>The maximum allocation for every container request at the RM, in terms of virtual CPU cores. Requests higher than this won't take effect, and will get capped to this value.</description>
    </property>
    <property>
        <name>yarn.nodemanager.resource.memory-mb</name>
        <value>4096</value>
        <description>Physical memory, in MB, to be made available to running containers</description>
    </property>
    <property>
        <name>yarn.nodemanager.resource.cpu-vcores</name>
        <value>4</value>
        <description>Number of CPU cores that can be allocated for containers.</description>
    </property>

    <property>
      <name>yarn.nodemanager.aux-services</name>
      <value>mapreduce_shuffle</value>
      <description>shuffle service that needs to be set for Map Reduce to run </description>
    </property>
</configuration>