Question

我正在尝试通过运行wordcount作业来测试我的hadoop安装。我的问题是，工作陷入ACCEPTED状态，似乎永远运行。我正在使用hadoop 2.3.0并尝试通过回答此问题here来解决问题，但它对我没有用。

这就是我所拥有的：

C:\hadoop-2.3.0>yarn jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.3.0.jar wordcount /data/test.txt /data/output
15/03/15 15:36:07 INFO client.RMProxy: Connecting to ResourceManager at/0.0.0.0:8032
15/03/15 15:36:09 INFO input.FileInputFormat: Total input paths to process : 1
15/03/15 15:36:10 INFO mapreduce.JobSubmitter: number of splits:1
15/03/15 15:36:10 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_14 26430101974_0001
15/03/15 15:36:11 INFO impl.YarnClientImpl: Submitted application application_14 26430101974_0001
15/03/15 15:36:11 INFO mapreduce.Job: The url to track the job: http://Agata-PC:8088/proxy/application_1426430101974_0001/
15/03/15 15:36:11 INFO mapreduce.Job: Running job: job_1426430101974_0001

这是我的mapred-site.xml：

<configuration>
<property>
   <name>mapreduce.framework.name</name>
   <value>yarn</value>
</property>
 <property>
    <name>mapred.job.tracker</name>
    <value>127.0.0.1:9001</value>
</property>
   <property>
    <name>mapreduce.jobtracker.staging.root.dir</name>
    <value>/user</value>
</property>
<property>
    <name>mapreduce.history.server.http.address</name>
    <value>127.0.0.1:51111</value>
    <description>Http address of the history server</description>
    <final>false</final>
</property>
<property>
    <name>yarn.app.mapreduce.am.resource.mb</name>
    <value>1024</value>
</property>
<property>
    <name>yarn.app.mapreduce.am.command-opts</name>
    <value>-Xmx768m</value>
</property>
<property>
    <name>mapreduce.map.cpu.vcores</name>
    <value>1</value>
    <description>The number of virtual cores required for each map task.</description>
</property>
<property>
    <name>mapreduce.reduce.cpu.vcores</name>
    <value>1</value>
    <description>The number of virtual cores required for each map task.</description>
</property>
<property>
    <name>mapreduce.map.memory.mb</name>
    <value>1024</value>
    <description>Larger resource limit for maps.</description>
</property>
<property>
    <name>mapreduce.map.java.opts</name>
    <value>-Xmx768m</value>
    <description>Heap-size for child jvms of maps.</description>
</property>
<property>
    <name>mapreduce.reduce.memory.mb</name>
    <value>1024</value>
    <description>Larger resource limit for reduces.</description>
</property>
<property>
    <name>mapreduce.reduce.java.opts</name>
    <value>-Xmx768m</value>
    <description>Heap-size for child jvms of reduces.</description>
</property>
</configuration>

这是我的yarn-site.xml：

<configuration>
    <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.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>2048</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>
</configuration>

非常感谢任何帮助。

Answer 1

您是否尝试重新启动hadoop的进程或群集？可能还有一些作品仍在运行。

通过关注作业的网址或浏览hadoop网址，查看日志可能会有所帮助。

干杯。

Answer 2

我之前遇到过类似的问题，你可能在mapper或reducer中有一个无限循环。检查您的减速器是否正确处理可迭代。

Hadoop 2.3.0 wordcount永远运行

2 个答案: