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Date: Wed, 29 Aug 2012 14:01:16 +0530
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Subject: Re: MRBench Maps strange behaviour
From: Hemanth Yamijala <yhemanth@gmail.com>
To: user@hadoop.apache.org
Content-Type: text/plain; charset=ISO-8859-1

Assume you are asking about what is the exact number of maps launched.
If yes, then the output of the MRBench run is printing the counter
"Launched map tasks". That is the exact value of maps launched.

Thanks
Hemanth

On Wed, Aug 29, 2012 at 1:14 PM, Gaurav Dasgupta <gdsayshi@gmail.com> wrote:
> Hi Hemanth,
>
> Thanks for the reply.
> Can you tell me how can I calculate or ensure from the counters what should
> be the exact number of Maps?
> Thanks,
> Gaurav Dasgupta
> On Wed, Aug 29, 2012 at 11:26 AM, Hemanth Yamijala <yhemanth@gmail.com>
> wrote:
>>
>> Hi,
>>
>> The number of maps specified to any map reduce program (including
>> those part of MRBench) is generally only a hint, and the actual number
>> of maps will be influenced in typical cases by the amount of data
>> being processed. You can take a look at this wiki link to understand
>> more: http://wiki.apache.org/hadoop/HowManyMapsAndReduces
>>
>> In the examples below, since the data you've generated is different,
>> the number of mappers are different. To be able to judge your
>> benchmark results, you'd need to benchmark against the same data (or
>> at least same type of type - i.e. size and type).
>>
>> The number of maps printed at the end is straight from the input
>> specified and doesn't reflect what the job actually ran with. The
>> information from the counters is the right one.
>>
>> Thanks
>> Hemanth
>>
>> On Tue, Aug 28, 2012 at 4:02 PM, Gaurav Dasgupta <gdsayshi@gmail.com>
>> wrote:
>> > Hi All,
>> >
>> > I executed the "MRBench" program from "hadoop-test.jar" in my 12 node
>> > CDH3
>> > cluster. After executing, I had some strange observations regarding the
>> > number of Maps it ran.
>> >
>> > First I ran the command:
>> > hadoop jar /usr/lib/hadoop-0.20/hadoop-test.jar mrbench -numRuns 3 -maps
>> > 200
>> > -reduces 200 -inputLines 1024 -inputType random
>> > And I could see that the actual number of Maps it ran was 201 (for all
>> > the 3
>> > runs) instead of 200 (Though the end report displays the launched to be
>> > 200). Here is the console report:
>> >
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient: Job complete:
>> > job_201208230144_0035
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient: Counters: 28
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:   Job Counters
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Launched reduce tasks=200
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=617209
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Total time spent by all
>> > reduces
>> > waiting after reserving slots (ms)=0
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Total time spent by all
>> > maps
>> > waiting after reserving slots (ms)=0
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Rack-local map tasks=137
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Launched map tasks=201
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:     Data-local map tasks=64
>> >
>> > 12/08/28 04:34:35 INFO mapred.JobClient:
>> > SLOTS_MILLIS_REDUCES=1756882
>> >
>> >
>> >
>> > Again, I ran the MRBench for just 10 Maps and 10 Reduces:
>> >
>> > hadoop jar /usr/lib/hadoop-0.20/hadoop-test.jar mrbench -maps 10
>> > -reduces 10
>> >
>> >
>> >
>> > This time the actual number of Maps were only 2 and again the end report
>> > displays Maps Lauched to be 10. The console output:
>> >
>> >
>> >
>> > 12/08/28 05:05:35 INFO mapred.JobClient: Job complete:
>> > job_201208230144_0040
>> > 12/08/28 05:05:35 INFO mapred.JobClient: Counters: 27
>> > 12/08/28 05:05:35 INFO mapred.JobClient:   Job Counters
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Launched reduce tasks=20
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     SLOTS_MILLIS_MAPS=6648
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Total time spent by all
>> > reduces
>> > waiting after reserving slots (ms)=0
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Total time spent by all
>> > maps
>> > waiting after reserving slots (ms)=0
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Launched map tasks=2
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Data-local map tasks=2
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     SLOTS_MILLIS_REDUCES=163257
>> > 12/08/28 05:05:35 INFO mapred.JobClient:   FileSystemCounters
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     FILE_BYTES_READ=407
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     HDFS_BYTES_READ=258
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=1072596
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=3
>> > 12/08/28 05:05:35 INFO mapred.JobClient:   Map-Reduce Framework
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Map input records=1
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Reduce shuffle bytes=647
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Spilled Records=2
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Map output bytes=5
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     CPU time spent (ms)=17070
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Total committed heap usage
>> > (bytes)=6218842112
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Map input bytes=2
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Combine input records=0
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     SPLIT_RAW_BYTES=254
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Reduce input records=1
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Reduce input groups=1
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Combine output records=0
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Physical memory (bytes)
>> > snapshot=3348828160
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Reduce output records=1
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Virtual memory (bytes)
>> > snapshot=22955810816
>> > 12/08/28 05:05:35 INFO mapred.JobClient:     Map output records=1
>> > DataLines Maps Reduces AvgTime (milliseconds)
>> > 1                20     20           17451
>> >
>> > Can some one please help me understand this behaviour of Hadoop in this
>> > case. My main purpose of running a MRBench is to calculate the Average
>> > time
>> > for certain amount of Maps, Reduces, InputLines etc. If the number of
>> > Maps
>> > is not what I submitted, then how can I judge my benchmark results?
>> >
>> >
>> >
>> > Thanks,
>> >
>> > Gaurav Dasgupta
>
>