Hi Sudhakar,
Indeed there was a type the complete command is as follows except the main
class since my manifest has the entry for main class.
/hadoop jar wordCount.jar /opt/ApacheHadoop/temp/worker.log
/opt/ApacheHadoop/out/
Next I killed the datanode in 10.12.11.210 and l see the following messages
in the log files. Looks like the namenode is still trying to assign the
complete task to one single node and since it does not find the complete
data set in one node it is complaining.
2014-01-15 16:38:26,894 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1-DEV05:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:27,348 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1dev-211:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:27,871 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1-dev06:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:27,897 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1-DEV05:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:28,349 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1dev-211:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:28,874 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1-dev06:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
2014-01-15 16:38:28,900 WARN
org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.LeafQueue:
Node : l1-DEV05:1004 does not have sufficient resource for request :
{Priority: 0, Capability: <memory:2048, vCores:1>, # Containers: 1,
Location: *, Relax Locality: true} node total capability : <memory:1024,
vCores:8>
--Ashish
On Wed, Jan 15, 2014 at 3:59 PM, sudhakara st <[email protected]>wrote:
> Hello Ashish
>
>
> 2) Run the example again using the command
> ./hadoop dfs wordCount.jar /opt/ApacheHadoop/temp/worker.log
> /opt/ApacheHadoop/out/
>
>
> Unless if it typo mistake the command should be
> ./hadoop jar wordCount.jar WordCount /opt/ApacheHadoop/temp/worker.log
> /opt/ApacheHadoop/out/
>
> One more thing try , just stop datanode process in 10.12.11.210 and run
> the job
>
>
>
>
> On Wed, Jan 15, 2014 at 2:07 PM, Ashish Jain <[email protected]> wrote:
>
>> Hello Sudhakara,
>>
>> Thanks for your suggestion. However once I change the mapreduce framework
>> to yarn my map reduce jobs does not get executed at all. It seems it is
>> waiting on some thread indefinitely. Here is what I have done
>>
>> 1) Set the mapreduce framework to yarn in mapred-site.xml
>> <property>
>> <name>mapreduce.framework.name</name>
>> <value>yarn</value>
>> </property>
>> 2) Run the example again using the command
>> ./hadoop dfs wordCount.jar /opt/ApacheHadoop/temp/worker.log
>> /opt/ApacheHadoop/out/
>>
>> The jobs are just stuck and do not move further.
>>
>>
>> I also tried the following and it complains of filenotfound exception and
>> some security exception
>>
>> ./hadoop dfs wordCount.jar file:///opt/ApacheHadoop/temp/worker.log
>> file:///opt/ApacheHadoop/out/
>>
>> Below is the status of the job from hadoop application console. The
>> progress bar does not move at all.
>>
>> ID
>> User
>> Name
>> Application Type
>> Queue
>> StartTime
>> FinishTime
>> State
>> FinalStatus
>> Progress
>> Tracking UI
>> application_1389771586883_0002<http://10.12.11.210:8088/cluster/app/application_1389771586883_0002>
>> rootwordcount MAPREDUCEdefaultWed, 15 Jan 2014 07:52:04 GMTN/AACCEPTED
>> UNDEFINED
>>
>> UNASSIGNE <http://10.12.11.210:8088/cluster/apps#>
>> Please advice what should I do
>>
>> --Ashish
>>
>>
>> On Tue, Jan 14, 2014 at 5:48 PM, sudhakara st <[email protected]>wrote:
>>
>>> Hello Ashish
>>> It seems job is running in Local job runner(LocalJobRunner) by reading
>>> the Local file system. Can you try by give the full URI path of the input
>>> and output path.
>>> like
>>> $hadoop jar program.jar ProgramName -Dmapreduce.framework.name=yarn
>>> file:///home/input/ file:///home/output/
>>>
>>>
>>> On Mon, Jan 13, 2014 at 3:02 PM, Ashish Jain <[email protected]> wrote:
>>>
>>>> German,
>>>>
>>>> This does not seem to be helping. I tried to use the Fairscheduler as
>>>> my resource manger but the behavior remains same. I could see the
>>>> fairscheduler log getting continuous heart beat from both the other nodes.
>>>> But it is still not distributing the work to other nodes. What I did next
>>>> was started 3 jobs simultaneously so that may be some part of one of the
>>>> job be distributed to other nodes. However still only one node is being
>>>> used :(((. What is that is going wrong can some one help?
>>>>
>>>> Sample of fairsheduler log:
>>>> 2014-01-13 15:13:54,293 HEARTBEAT l1dev-211
>>>> 2014-01-13 15:13:54,953 HEARTBEAT l1-dev06
>>>> 2014-01-13 15:13:54,988 HEARTBEAT l1-DEV05
>>>> 2014-01-13 15:13:55,295 HEARTBEAT l1dev-211
>>>> 2014-01-13 15:13:55,956 HEARTBEAT l1-dev06
>>>> 2014-01-13 15:13:55,993 HEARTBEAT l1-DEV05
>>>> 2014-01-13 15:13:56,297 HEARTBEAT l1dev-211
>>>> 2014-01-13 15:13:56,960 HEARTBEAT l1-dev06
>>>> 2014-01-13 15:13:56,997 HEARTBEAT l1-DEV05
>>>> 2014-01-13 15:13:57,299 HEARTBEAT l1dev-211
>>>> 2014-01-13 15:13:57,964 HEARTBEAT l1-dev06
>>>> 2014-01-13 15:13:58,001 HEARTBEAT l1-DEV05
>>>>
>>>> My Data distributed as blocks to other nodes. The host with IP
>>>> 10.12.11.210 has all the data and this is the one which is serving all the
>>>> request.
>>>>
>>>> Total number of blocks: 8
>>>> 1073741866: 10.12.11.211:50010 View Block Info
>>>> 10.12.11.210:50010 View Block Info
>>>> 1073741867: 10.12.11.211:50010 View Block Info
>>>> 10.12.11.210:50010 View Block Info
>>>> 1073741868: 10.12.11.210:50010 View Block Info
>>>> 10.12.11.209:50010 View Block Info
>>>> 1073741869: 10.12.11.210:50010 View Block Info
>>>> 10.12.11.209:50010 View Block Info
>>>> 1073741870: 10.12.11.211:50010 View Block Info
>>>> 10.12.11.210:50010 View Block Info
>>>> 1073741871: 10.12.11.210:50010 View Block Info
>>>> 10.12.11.209:50010 View Block Info
>>>> 1073741872: 10.12.11.211:50010 View Block Info
>>>> 10.12.11.210:50010 View Block Info
>>>> 1073741873: 10.12.11.210:50010 View Block Info
>>>> 10.12.11.209:50010 View Block Info
>>>>
>>>> Someone please advice on how to go about this.
>>>>
>>>> --Ashish
>>>>
>>>>
>>>> On Fri, Jan 10, 2014 at 12:58 PM, Ashish Jain <[email protected]>wrote:
>>>>
>>>>> Thanks for all these suggestions. Somehow I do not have access to the
>>>>> servers today and will try the suggestions made on monday and will let you
>>>>> know how it goes.
>>>>>
>>>>> --Ashish
>>>>>
>>>>>
>>>>> On Thu, Jan 9, 2014 at 7:53 PM, German Florez-Larrahondo <
>>>>> [email protected]> wrote:
>>>>>
>>>>>> Ashish
>>>>>>
>>>>>> Could this be related to the scheduler you are using and its
>>>>>> settings?.
>>>>>>
>>>>>>
>>>>>>
>>>>>> On lab environments when running a single type of job I often use
>>>>>> FairScheduler (the YARN default in 2.2.0 is CapacityScheduler) and it
>>>>>> does
>>>>>> a good job distributing the load.
>>>>>>
>>>>>>
>>>>>>
>>>>>> You could give that a try (
>>>>>> https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/FairScheduler.html
>>>>>> )
>>>>>>
>>>>>>
>>>>>>
>>>>>> I think just changing yarn-site.xml as follows could demonstrate
>>>>>> this theory (note that how the jobs are scheduled depend on resources
>>>>>> such
>>>>>> as memory on the nodes and you would need to setup yarn-site.xml
>>>>>> accordingly).
>>>>>>
>>>>>>
>>>>>>
>>>>>> <property>
>>>>>>
>>>>>> <name>yarn.resourcemanager.scheduler.class</name>
>>>>>>
>>>>>>
>>>>>> <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
>>>>>>
>>>>>> </property>
>>>>>>
>>>>>>
>>>>>>
>>>>>> Regards
>>>>>>
>>>>>> ./g
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> *From:* Ashish Jain [mailto:[email protected]]
>>>>>> *Sent:* Thursday, January 09, 2014 6:46 AM
>>>>>> *To:* [email protected]
>>>>>> *Subject:* Re: Distributing the code to multiple nodes
>>>>>>
>>>>>>
>>>>>>
>>>>>> Another point to add here 10.12.11.210 is the host which has
>>>>>> everything running including a slave datanode. Data was also distributed
>>>>>> this host as well as the jar file. Following are running on 10.12.11.210
>>>>>>
>>>>>> 7966 DataNode
>>>>>> 8480 NodeManager
>>>>>> 8353 ResourceManager
>>>>>> 8141 SecondaryNameNode
>>>>>> 7834 NameNode
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Jan 9, 2014 at 6:12 PM, Ashish Jain <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>> Logs were updated only when I copied the data. After copying the data
>>>>>> there has been no updates on the log files.
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Jan 9, 2014 at 5:08 PM, Chris Mawata <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>> Do the logs on the three nodes contain anything interesting?
>>>>>> Chris
>>>>>>
>>>>>> On Jan 9, 2014 3:47 AM, "Ashish Jain" <[email protected]> wrote:
>>>>>>
>>>>>> Here is the block info for the record I distributed. As can be seen
>>>>>> only 10.12.11.210 has all the data and this is the node which is serving
>>>>>> all the request. Replicas are available with 209 as well as 210
>>>>>>
>>>>>> 1073741857: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>> 1073741858: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.211:50010 View Block Info
>>>>>> 1073741859: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>> 1073741860: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.211:50010 View Block Info
>>>>>> 1073741861: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>> 1073741862: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>> 1073741863: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>> 1073741864: 10.12.11.210:50010 View Block Info
>>>>>> 10.12.11.209:50010 View Block Info
>>>>>>
>>>>>> --Ashish
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Jan 9, 2014 at 2:11 PM, Ashish Jain <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>> Hello Chris,
>>>>>>
>>>>>> I have now a cluster with 3 nodes and replication factor being 2.
>>>>>> When I distribute a file I could see that there are replica of data
>>>>>> available in other nodes. However when I run a map reduce job again only
>>>>>> one node is serving all the request :(. Can you or anyone please provide
>>>>>> some more inputs.
>>>>>>
>>>>>> Thanks
>>>>>> Ashish
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Wed, Jan 8, 2014 at 7:16 PM, Chris Mawata <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>> 2 nodes and replication factor of 2 results in a replica of each
>>>>>> block present on each node. This would allow the possibility that a
>>>>>> single
>>>>>> node would do the work and yet be data local. It will probably happen if
>>>>>> that single node has the needed capacity. More nodes than the
>>>>>> replication
>>>>>> factor are needed to force distribution of the processing.
>>>>>> Chris
>>>>>>
>>>>>> On Jan 8, 2014 7:35 AM, "Ashish Jain" <[email protected]> wrote:
>>>>>>
>>>>>> Guys,
>>>>>>
>>>>>> I am sure that only one node is being used. I just know ran the job
>>>>>> again and could see that CPU usage only for one server going high other
>>>>>> server CPU usage remains constant and hence it means other node is not
>>>>>> being used. Can someone help me to debug this issue?
>>>>>>
>>>>>> ++Ashish
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Wed, Jan 8, 2014 at 5:04 PM, Ashish Jain <[email protected]>
>>>>>> wrote:
>>>>>>
>>>>>> Hello All,
>>>>>>
>>>>>> I have a 2 node hadoop cluster running with a replication factor of
>>>>>> 2. I have a file of size around 1 GB which when copied to HDFS is
>>>>>> replicated to both the nodes. Seeing the block info I can see the file
>>>>>> has
>>>>>> been subdivided into 8 parts which means it has been subdivided into 8
>>>>>> blocks each of size 128 MB. I use this file as input to run the word
>>>>>> count
>>>>>> program. Some how I feel only one node is doing all the work and the code
>>>>>> is not distributed to other node. How can I make sure code is distributed
>>>>>> to both the nodes? Also is there a log or GUI which can be used for this?
>>>>>>
>>>>>> Please note I am using the latest stable release that is 2.2.0.
>>>>>>
>>>>>> ++Ashish
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>>
>>> Regards,
>>> ...Sudhakara.st
>>>
>>>
>>
>>
>
>
> --
>
> Regards,
> ...Sudhakara.st
>
>
