Hello,
I have been able to make this work. I don't know why, but when but
input file is zipped (read as a input stream) it creates only 1 mapper.
However, when it's not zipped, it creates more mappers (running 3 instances
it created 4 mappers and running 5 instances, it created 8 mappers).
I really would like to know why this happens and even with this number
of mappers, I would like to know why more mappers aren't created. I was
reading part of the book "Hadoop - The definitive guide" (
https://www.inkling.com/read/hadoop-definitive-guide-tom-white-3rd/chapter-7/input-formats)
which says:
"The JobClient calls the getSplits() method, passing the desired number of
map tasks as the numSplits argument. This number is treated as a hint, as
InputFormat implementations are free to return a different number of splits
to the number specified in numSplits. Having calculated the splits, the
client sends them to the jobtracker, which uses their storage locations to
schedule map tasks to process them on the tasktrackers. ..."
I am not sure on how to get more info.
Would you recommend me to try to find the answer on the book? Or
should I read hadoop source code directly?
Best regards,
Marcelo.
2013/1/29 Marcelo Elias Del Valle <mvall...@gmail.com>
> I implemented my custom input format. Here is how I used it:
>
> https://github.com/mvallebr/CSVInputFormat/blob/master/src/test/java/org/apache/hadoop/mapreduce/lib/input/test/CSVTestRunner.java
>
> As you can see, I do:
> importerJob.setInputFormatClass(CSVNLineInputFormat.class);
>
> And here is the Input format and the linereader:
>
> https://github.com/mvallebr/CSVInputFormat/blob/master/src/main/java/org/apache/hadoop/mapreduce/lib/input/CSVNLineInputFormat.java
>
> https://github.com/mvallebr/CSVInputFormat/blob/master/src/main/java/org/apache/hadoop/mapreduce/lib/input/CSVLineRecordReader.java
>
> In this input format, I completely ignore these other parameters and get
> the splits by the number of lines. The amount of lines per map can be
> controlled by the same parameter used in NLineInputFormat:
>
> public static final String LINES_PER_MAP =
> "mapreduce.input.lineinputformat.linespermap";
> However, it has really no effect on the number of maps.
>
>
>
> 2013/1/29 Vinod Kumar Vavilapalli <vino...@hortonworks.com>
>
>>
>> Regarding your original question, you can use the min and max split
>> settings to control the number of maps:
>> http://hadoop.apache.org/docs/stable/api/org/apache/hadoop/mapreduce/lib/input/FileInputFormat.html.
>> See #setMinInputSplitSize and #setMaxInputSplitSize. Or
>> use mapred.min.split.size directly.
>>
>> W.r.t your custom inputformat, are you sure you job is using this
>> InputFormat and not the default one?
>>
>> HTH,
>> +Vinod Kumar Vavilapalli
>> Hortonworks Inc.
>> http://hortonworks.com/
>>
>> On Jan 28, 2013, at 12:56 PM, Marcelo Elias Del Valle wrote:
>>
>> Just to complement the last question, I have implemented the getSplits
>> method in my input format:
>>
>> https://github.com/mvallebr/CSVInputFormat/blob/master/src/main/java/org/apache/hadoop/mapreduce/lib/input/CSVNLineInputFormat.java
>>
>> However, it still doesn't create more than 2 map tasks. Is there
>> something I could do about it to assure more map tasks are created?
>>
>> Thanks
>> Marcelo.
>>
>>
>> 2013/1/28 Marcelo Elias Del Valle <mvall...@gmail.com>
>>
>>> Sorry for asking too many questions, but the answers are really
>>> happening.
>>>
>>>
>>> 2013/1/28 Harsh J <ha...@cloudera.com>
>>>
>>>> This seems CPU-oriented. You probably want the NLineInputFormat? See
>>>>
>>>> http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/mapred/lib/NLineInputFormat.html
>>>> .
>>>> This should let you spawn more maps as we, based on your N factor.
>>>>
>>>
>>> Indeed, CPU is my bottleneck. That's why I want more things in parallel.
>>> Actually, I wrote my own InputFormat, to be able to process multiline
>>> CSVs: https://github.com/mvallebr/CSVInputFormat
>>> I could change it to read several lines at a time, but would this alone
>>> allow more tasks running in parallel?
>>>
>>>
>>>> Not really - "Slots" are capacities, rather than split factors
>>>> themselves. You can have N slots always available, but your job has to
>>>> supply as many map tasks (based on its input/needs/etc.) to use them
>>>> up.
>>>>
>>>
>>> But how can I do that (supply map tasks) in my job? changing its code?
>>> hadoop config?
>>>
>>>
>>>> Unless your job sets the number of reducers to 0 manually, 1 default
>>>> reducer is always run that waits to see if it has any outputs from
>>>> maps. If it does not receive any outputs after maps have all
>>>> completed, it dies out with behavior equivalent to a NOP.
>>>>
>>> Ok, I did job.setNumReduceTasks(0); , guess this will solve this part,
>>> thanks!
>>>
>>>
>>> --
>>> Marcelo Elias Del Valle
>>> http://mvalle.com - @mvallebr
>>>
>>
>>
>>
>> --
>> Marcelo Elias Del Valle
>> http://mvalle.com - @mvallebr
>>
>>
>>
>
>
> --
> Marcelo Elias Del Valle
> http://mvalle.com - @mvallebr
>
--
Marcelo Elias Del Valle
http://mvalle.com - @mvallebr
