我在四台机器上安装了Hadood-2.6（分布式模式）。所有守护进程都正常运行。但是当我运行标准的teragen示例时 -
hadoop jar hadoop-mapreduce-examples-2.6.0.jar teragen 10 /input
它给了我以下错误 -
hadoop jar /root/exp_testing/hadoop_new/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar teragen 10 /input
15/04/28 05:45:50 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/04/28 05:45:51 INFO client.RMProxy: Connecting to ResourceManager at enode1/192.168.1.231:8050
15/04/28 05:45:53 INFO terasort.TeraSort: Generating 10 using 2
15/04/28 05:45:53 INFO mapreduce.JobSubmitter: number of splits:2
15/04/28 05:45:54 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1430180067597_0001
15/04/28 05:45:54 INFO impl.YarnClientImpl: Submitted application application_1430180067597_0001
15/04/28 05:45:54 INFO mapreduce.Job: The url to track the job: http://ubuntu:8088/proxy/application_1430180067597_0001/
15/04/28 05:45:54 INFO mapreduce.Job: Running job: job_1430180067597_0001
15/04/28 05:46:15 INFO mapreduce.Job: Job job_1430180067597_0001 running in uber mode : false
15/04/28 05:46:15 INFO mapreduce.Job: map 0% reduce 0%
15/04/28 05:46:15 INFO mapreduce.Job: Job job_1430180067597_0001 failed with state FAILED due to: Application application_1430180067597_0001 failed 2 times due to Error launching appattempt_1430180067597_0001_000002. Got exception: java.net.ConnectException: Call From ubuntu/127.0.1.1 to ubuntu:60839 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:791)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:731)
at org.apache.hadoop.ipc.Client.call(Client.java:1472)
at org.apache.hadoop.ipc.Client.call(Client.java:1399)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
at com.sun.proxy.$Proxy79.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.launch(AMLauncher.java:119)
at org.apache.hadoop.yarn.server.resourcemanager.amlauncher.AMLauncher.run(AMLauncher.java:254)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:530)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:494)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:607)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:705)
at org.apache.hadoop.ipc.Client$Connection.access$2800(Client.java:368)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1521)
at org.apache.hadoop.ipc.Client.call(Client.java:1438)
... 9 more
. Failing the application.
15/04/28 05:46:15 INFO mapreduce.Job: Counters: 0
我有两套（每组包含4个节点）机器相同设置正在为其他设置工作但我不知道为什么我面临一套问题？
的/ etc /主机
127.0.0.1 localhost
#127.0.1.1 ubuntu
127.0.0.1 ubuntu
#192.168.1.231 ubuntu
192.168.1.231 enode1
192.168.1.232 enode2
192.168.1.233 enode3
192.168.1.234 enode4
# The following lines are desirable for IPv6 capable hosts
::1 ip6-localhost ip6-loopback
fe00::0 ip6-localnet
ff00::0 ip6-mcastprefix
ff02::1 ip6-allnodes
ff02::2 ip6-allrouters
~
芯-site.xml中
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://enode1:9000/</value>
</property>
</configuration>
HDFS-site.xml中
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:/home/exp_testing/hdfs/namenode</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:/home/exp_testing/hdfs/datanode</value>
</property>
</configuration>
mapred-site.xml中
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
<property>
<name>yarn.app.mapreduce.am.resource.mb</name>
<value>1536</value>
</property>
<property>
<name>yarn.app.mapreduce.am.command-opts</name>
<value>-Xmx1024m</value>
</property>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</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>-Xmx400m</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>-Xmx400m</value>
<description>Heap-size for child jvms of reduces.</description>
</property>
<property>
<name>mapreduce.jobtracker.address</name>
<value>enode1:54311</value>
</property>
</configuration>
纱的site.xml
<?xml version="1.0"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Site specific YARN configuration properties -->
<configuration>
<property>
<description>Whether to enable log aggregation</description>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>10</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>6144</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>32</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>6144</value>
<description>Physical memory, in MB, to be made available to running containers</description>
</property>
<property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>8</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>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>enode1:8025</value>
<description>The hostname of the RM.</description>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>enode1:8030</value>
<description>The hostname of the RM.</description>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>enode1:8050</value>
<description>The hostname of the RM.</description>
</property>
</configuration>
hadoop fs -ls /
的结果root@ubuntu:~/exp_testing/mysrc# hadoop fs -ls /
15/04/29 00:43:57 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 2 items
drwxr-xr-x - root supergroup 0 2015-04-29 00:43 /input
drwx------ - root supergroup 0 2015-04-29 00:43 /tmp
@ sandeep007734解决方案正在为我的新集群工作，我对他的解决方案深信不疑但是在旧的集群中我已经评论过了 在/ etc / hosts中的以下行，它正常工作
＃127.0.1.1 ubuntu
我不知道为什么会这样？
答案 0 :(得分：0)
得到异常：java.net.ConnectException：从ubuntu / 127.0.1.1 调用到ubuntu：60839连接异常失败：java.net.ConnectException：拒绝连接
此错误主要是由于环回问题引起的。要解决此问题，请在127.0.1.1文件中将127.0.0.1更改为etc/hosts。现在，重新启动hadoop进程并尝试运行该示例。它应该工作。
答案 1 :(得分：0)
尝试从/etc/hosts删除这些行，如果您不使用它，请禁用ipv6：
127.0.0.1 localhost
127.0.0.1 ubuntu
# The following lines are desirable for IPv6 capable hosts
::1 ip6-localhost ip6-loopback
fe00::0 ip6-localnet
ff00::0 ip6-mcastprefix
ff02::1 ip6-allnodes
ff02::2 ip6-allrouters
~
IPv6的一个问题是，将0.0.0.0用于各种与网络相关的Hadoop配置选项将导致Hadoop绑定到IPv6地址。
因此，如果您不使用IPv6，最好禁用它，因为它可能会在运行Hadoop时导致问题。
要禁用IPv6，请在您选择的编辑器中打开/etc/sysctl.conf，并将以下行添加到文件末尾：
# disable ipv6
net.ipv6.conf.all.disable_ipv6 = 1
net.ipv6.conf.default.disable_ipv6 = 1
net.ipv6.conf.lo.disable_ipv6 = 1
希望这会对你有所帮助
答案 2 :(得分：0)
问题是主机名配置。如果您使用自定义主机名（仅在/ etc / hosts文件中而不是在dns中定义），则hadoop有时会以奇怪的方式运行。
您使用名称enode1，enode2等作为节点的名称。
但是你发布的错误显示：
15/04/28 05:45:54 INFO mapreduce.Job: The url to track the job: http://ubuntu:8088/proxy/application_1430180067597_0001/
这里是说要跟踪工作，网址是http://ubuntu ... 这意味着hadoop正在获取系统的主机名以进行操作。
现在一个明显的解决方案是进入/ etc / hosts文件并添加条目（在每个节点中，包括master）。例如，在enode1
上192.168.1.231 ubuntu
当您尝试格式化namenode并启动集群时，这将正常工作。
但是如果你尝试运行一些工作，你会遇到麻烦，因为奴隶会尝试使用地址连接资源管理器
ubuntu/192.168.1.231
这意味着，如果您无法解析ubuntu主机名，请使用IP。但是奴隶能够解析映射到其自己的IP的IP。
例如，当在机器enode2上运行的从站尝试连接到资源管理器时，它使用 ubuntu / 192.168.1.231 。 ubuntu主机名被解析为 192.168.1.232 ，因为您只是在/ etc / hosts文件中定义了它。
在执行作业期间，您应该能够在日志中看到错误：
org.apache.hadoop.ipc.Client: Retrying connect to server
它确实尝试连接资源管理器很长一段时间，这就是为什么你的teragen工作需要很长时间才能执行。由于在从属服务器上调度的MAP任务会尝试很长时间连接到资源管理器并最终失败。只有在主节点上调度的MAP任务（因为您将主服务器也用作从服务器）才会成功（因为ubuntu仅在主节点上正确解析了资源管理器IP）。
解决这个问题的方法是。
停止Hadoop群集
在每台计算机上编辑文件/ etc / hostname 例如在机器enode1
自：
ubuntu
要：
enode1
enode2，相应机器上的enode3。
确保命令
更改了主机名主机名
格式化Namdenode
答案 3 :(得分：0)
我遇到了同样的问题，最后幸运的是我解决了这个问题。问题是主持人!!!!。
刚 苏根
主节点上的主机名主机
从属节点上的主机名从站
重启群集。
没关系
............................................... ............
这是我机器上的样子。
（1）这是我的问题：
miaofu@miaofu-Virtual-Machine:~/hadoop-2.6.4/etc/hadoop$ hadoop jar ../../share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.4.jar wordcount /in /out2
16/09/17 15:41:14 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.202.104:8032
16/09/17 15:41:17 INFO input.FileInputFormat: Total input paths to process : 9
16/09/17 15:41:17 INFO mapreduce.JobSubmitter: number of splits:9
16/09/17 15:41:17 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1474096034614_0002
16/09/17 15:41:18 INFO impl.YarnClientImpl: Submitted application application_1474096034614_0002
16/09/17 15:41:18 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1474096034614_0002/
16/09/17 15:41:18 INFO mapreduce.Job: Running job: job_1474096034614_0002
16/09/17 15:41:26 INFO mapreduce.Job: Job job_1474096034614_0002 running in uber mode : false
16/09/17 15:41:26 INFO mapreduce.Job: map 0% reduce 0%
16/09/17 15:41:39 INFO mapreduce.Job: map 11% reduce 0%
16/09/17 15:41:40 INFO mapreduce.Job: map 22% reduce 0%
16/09/17 15:41:41 INFO mapreduce.Job: map 67% reduce 0%
16/09/17 15:41:54 INFO mapreduce.Job: map 67% reduce 22%
16/09/17 15:44:29 INFO mapreduce.Job: Task Id : attempt_1474096034614_0002_m_000006_0, Status : FAILED
Container launch failed for container_1474096034614_0002_01_000008 : java.net.ConnectException: Call From miaofu-Virtual-Machine/127.0.0.1 to localhost:57019 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.GeneratedConstructorAccessor32.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:791)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:731)
at org.apache.hadoop.ipc.Client.call(Client.java:1473)
at org.apache.hadoop.ipc.Client.call(Client.java:1400)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)
at com.sun.proxy.$Proxy36.startContainers(Unknown Source)
at org.apache.hadoop.yarn.api.impl.pb.client.ContainerManagementProtocolPBClientImpl.startContainers(ContainerManagementProtocolPBClientImpl.java:96)
at sun.reflect.GeneratedMethodAccessor5.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy37.startContainers(Unknown Source)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:151)
at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:369)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
（2）这是我的配置： 的/ etc /主机：
127.0.0.1 localhost
127.0.0.1 miaofu-Virtual-Machine
192.168.202.104 master
192.168.202.31 slave01
192.168.202.105 slave02
# The following lines are desirable for IPv6 capable hosts
::1 ip6-localhost ip6-loopback
fe00::0 ip6-localnet
ff00::0 ip6-mcastprefix
ff02::1 ip6-allnodes
ff02::2 ip6-allrouters
（3）设置主机名 在主节点上：
root@miaofu-Virtual-Machine:/home/miaofu# vi /etc/hostname
root@miaofu-Virtual-Machine:/home/miaofu# hostname
miaofu-Virtual-Machine
root@miaofu-Virtual-Machine:/home/miaofu# hostname master
root@miaofu-Virtual-Machine:/home/miaofu# hostname
master
：
miaofu@miaofu-Virtual-Machine:~$ su root
密码：
^Z
[3]+ 已停止 su root
miaofu@miaofu-Virtual-Machine:~$ sudo passwd root
[sudo] password for miaofu:
输入新的 UNIX 密码：
重新输入新的 UNIX 密码：
passwd：已成功更新密码
miaofu@miaofu-Virtual-Machine:~$ hostname slave02
hostname: you must be root to change the host name
miaofu@miaofu-Virtual-Machine:~$ su root
密码：
root@miaofu-Virtual-Machine:/home/miaofu#
root@miaofu-Virtual-Machine:/home/miaofu#
root@miaofu-Virtual-Machine:/home/miaofu#
root@miaofu-Virtual-Machine:/home/miaofu# hostname slave02
root@miaofu-Virtual-Machine:/home/miaofu# hostname
slave02
（4）重启集群
stop-yarn.sh
stop-dfs.sh
cd
rm -r hadoop-2.6.4/tmp/*
hadoop namenode -format
start-dfs.sh
start-yarn.sh
（5）只需运行wordcount
miaofu@miaofu-Virtual-Machine:~$ hadoop fs -mkdir /in
miaofu@miaofu-Virtual-Machine:~$ vi retry.sh
miaofu@miaofu-Virtual-Machine:~$ hadoop fs -put etc/hadoop/*.xml /in
put: `etc/hadoop/*.xml': No such file or directory
miaofu@miaofu-Virtual-Machine:~$ hadoop fs -put hadoop-2.6.4/etc/hadoop/*.xml /in
jpmiaofu@miaofu-Virtual-Machine:~$ jps
61591 Jps
60601 ResourceManager
60297 SecondaryNameNode
60732 NodeManager
60092 DataNode
59927 NameNode
miaofu@miaofu-Virtual-Machine:~$ hadoop jar hadoop-2.6.4/
bin/ etc/ include/ lib/ LICENSE.txt NOTICE.txt sbin/ tmp/
conf.sh home/ input/ libexec/ logs/ README.txt share/
miaofu@miaofu-Virtual-Machine:~$ hadoop jar hadoop-2.6.4/share/
doc/ hadoop/
miaofu@miaofu-Virtual-Machine:~$ hadoop jar hadoop-2.6.4/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.4.jar wordcount /in /out
^Z
[1]+ 已停止 hadoop jar hadoop-2.6.4/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.4.jar wordcount /in /out
miaofu@miaofu-Virtual-Machine:~$ hadoop jar hadoop-2.6.4/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.4.jar wordcount /in /out3
16/09/17 16:46:24 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.202.104:8032
16/09/17 16:46:25 INFO input.FileInputFormat: Total input paths to process : 9
16/09/17 16:46:25 INFO mapreduce.JobSubmitter: number of splits:9
16/09/17 16:46:26 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1474101888060_0001
16/09/17 16:46:26 INFO impl.YarnClientImpl: Submitted application application_1474101888060_0001
16/09/17 16:46:26 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1474101888060_0001/
16/09/17 16:46:26 INFO mapreduce.Job: Running job: job_1474101888060_0001
16/09/17 16:46:35 INFO mapreduce.Job: Job job_1474101888060_0001 running in uber mode : false
16/09/17 16:46:35 INFO mapreduce.Job: map 0% reduce 0%
16/09/17 16:46:44 INFO mapreduce.Job: map 22% reduce 0%
16/09/17 16:46:45 INFO mapreduce.Job: map 33% reduce 0%
16/09/17 16:46:48 INFO mapreduce.Job: map 67% reduce 0%
16/09/17 16:46:49 INFO mapreduce.Job: map 100% reduce 0%
16/09/17 16:46:51 INFO mapreduce.Job: map 100% reduce 100%
16/09/17 16:46:52 INFO mapreduce.Job: Job job_1474101888060_0001 completed successfully
16/09/17 16:46:52 INFO mapreduce.Job: Counters: 50
File System Counters
FILE: Number of bytes read=21875
FILE: Number of bytes written=1110853
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=28532
HDFS: Number of bytes written=10579
HDFS: Number of read operations=30
HDFS: Number of large read operations=0
HDFS: Number of write operations=2
Job Counters
Killed map tasks=1
Launched map tasks=9
Launched reduce tasks=1
Data-local map tasks=9
Total time spent by all maps in occupied slots (ms)=84614
Total time spent by all reduces in occupied slots (ms)=4042
Total time spent by all map tasks (ms)=84614
Total time spent by all reduce tasks (ms)=4042
Total vcore-milliseconds taken by all map tasks=84614
Total vcore-milliseconds taken by all reduce tasks=4042
Total megabyte-milliseconds taken by all map tasks=86644736
Total megabyte-milliseconds taken by all reduce tasks=4139008
Map-Reduce Framework
Map input records=796
Map output records=2887
Map output bytes=36776
Map output materialized bytes=21923
Input split bytes=915
Combine input records=2887
Combine output records=1265
Reduce input groups=606
Reduce shuffle bytes=21923
Reduce input records=1265
Reduce output records=606
Spilled Records=2530
Shuffled Maps =9
Failed Shuffles=0
Merged Map outputs=9
GC time elapsed (ms)=590
CPU time spent (ms)=6470
Physical memory (bytes) snapshot=2690990080
Virtual memory (bytes) snapshot=8380964864
Total committed heap usage (bytes)=1966604288
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=27617
File Output Format Counters
Bytes Written=10579
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