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From Mohammad Tariq <donta...@gmail.com>
Subject Re: Mappers vs. Map tasks
Date Wed, 26 Feb 2014 11:08:36 GMT
Since there is no OOTB feature that allows this, you have to write your
custom InputFormat to handle JSON data. Alternatively you could make use of
Pig or Hive as they have builtin JSON support.

Warm Regards,
Tariq
cloudfront.blogspot.com


On Wed, Feb 26, 2014 at 10:07 AM, Rajesh Nagaraju
<rajeshnagaraju@gmail.com>wrote:

> 1 simple way is to remove the new line characters so that the default
> record reader and default way the block is read will take care of the input
> splits and JSON will not get affected by the removal of NL character
>
>
> On Wed, Feb 26, 2014 at 10:01 AM, Sugandha Naolekar <
> sugandha.n87@gmail.com> wrote:
>
>> Ok. Got it. Now I have a single file which is of 129MB. Thus, it will be
>> split into two blocks. Now, since my file is a json file, I cannot use
>> textinputformat. As, every input split(logical) will be a single line of
>> the json file. Which I dont want. Thus, in this case, can I write a custom
>> input format and a custom record reader so that, every input split(logical)
>> will have only that part of data which I require.
>>
>> For. e.g:
>>
>> { "type": "Feature", "properties": { "OSM_NAME": "", "FLAGS": 3.000000,
>> "CLAZZ": 42.000000, "ROAD_TYPE": 3.000000, "END_ID": 33451.000000,
>> "OSM_META": "", "REVERSE_LE": 217.541279, "X1": 77.552595, "OSM_SOURCE":
>> 1520846283.000000, "COST": 0.007058, "OSM_TARGET": 1520846293.000000, "X2":
>> 77.554549, "Y2": 12.993056, "CONGESTED_": 227.541279, "Y1": 12.993107,
>> "REVERSE_CO": 0.007058, "CONGESTION": 10.000000, "OSM_ID":
>> 138697535.000000, "START_ID": 33450.000000, "KM": 0.000000, "LENGTH":
>> 217.541279, "REVERSE__1": 227.541279, "SPEED_IN_K": 30.000000, "ROW_FLAG":
>> "F" }, "geometry": { "type": "LineString", "coordinates": [ [
>> 8633115.407361, 1458944.819456 ], [ 8633332.869986, 1458938.970140 ] ] } }
>> ,
>> { "type": "Feature", "properties": { "OSM_NAME": "", "FLAGS": 3.000000,
>> "CLAZZ": 32.000000, "ROAD_TYPE": 3.000000, "END_ID": 37016.000000,
>> "OSM_META": "", "REVERSE_LE": 156.806535, "X1": 77.538462, "OSM_SOURCE":
>> 1037135286.000000, "COST": 0.003052, "OSM_TARGET": 1551615728.000000, "X2":
>> 77.537950, "Y2": 12.992099, "CONGESTED_": 176.806535, "Y1": 12.993377,
>> "REVERSE_CO": 0.003052, "CONGESTION": 20.000000, "OSM_ID": 89417379.000000,
>> "START_ID": 24882.000000, "KM": 0.000000, "LENGTH": 156.806535,
>> "REVERSE__1": 176.806535, "SPEED_IN_K": 50.000000, "ROW_FLAG": "F" },
>> "geometry": { "type": "LineString", "coordinates": [ [ 8631542.162393,
>> 1458975.665482 ], [ 8631485.144550, 1458829.592709 ] ] } }
>>
>> *I want here the every input split to consist of entire type data and
>> thus, I can process it accordingly by giving relevant k,V pairs to the map
>> function.*
>>
>>
>> --
>> Thanks & Regards,
>> Sugandha Naolekar
>>
>>
>>
>>
>>
>> On Wed, Feb 26, 2014 at 2:09 AM, Mohammad Tariq <dontariq@gmail.com>wrote:
>>
>>> Hi Sugandha,
>>>
>>> Please find my comments embedded below :
>>>
>>>                   No. of mappers are decided as: Total_File_Size/Max.
>>> Block Size. Thus, if the file is smaller than the block size, only one
>>> mapper will be                               invoked. Right?
>>>                   This is true(but not always). The basic criteria
>>> behind map creation is the logic inside *getSplits* method of
>>> *InputFormat* being used in your                     MR job. It is the
>>> behavior of *file based InputFormats*, typically sub-classes of
>>> *FileInputFormat*, to split the input data into splits based
>>>           on the total size, in bytes, of the input files. See *this*<http://hadoop.apache.org/docs/current2/api/org/apache/hadoop/mapreduce/InputFormat.html>for
more details. And yes, if the file is smaller than the block size then
>>> only 1 mapper will                     be created.
>>>
>>>                   If yes, it means, the map() will be called only once.
>>> Right? In this case, if there are two datanodes with a replication factor
>>> as 1: only one                               datanode(mapper machine) will
>>> perform the task. Right?
>>>                   A mapper is called for each split. Don't get confused
>>> with the MR's split and HDFS's block. Both are different(They may overlap
>>> though, as in                     case of FileInputFormat). HDFS blocks are
>>> physical partitioning of your data, while an InputSplit is just a logical
>>> partitioning. If you have a                       file which is smaller
>>> than the HDFS blocksize then only one split will be created, hence only 1
>>> mapper will be called. And this will happen on                     the node
>>> where this file resides.
>>>
>>>                   The map() function is called by all the
>>> datanodes/slaves right? If the no. of mappers are more than the no. of
>>> slaves, what happens?
>>>                   map() doesn't get called by anybody. It rather gets
>>> created on the node where the chunk of data to be processed resides. A
>>> slave node can run                       multiple mappers based on the
>>> availability of CPU slots.
>>>
>>>                  One more thing to ask: No. of blocks = no. of mappers.
>>> Thus, those many no. of times the map() function will be called right?
>>>                  No. of blocks = no. of splits = no. of mappers. A map
>>> is called only once per split per node where that split is present.
>>>
>>> HTH
>>>
>>> Warm Regards,
>>> Tariq
>>> cloudfront.blogspot.com
>>>
>>>
>>> On Tue, Feb 25, 2014 at 3:54 PM, Sugandha Naolekar <
>>> sugandha.n87@gmail.com> wrote:
>>>
>>>> Hi Bertrand,
>>>>
>>>> As you said, no. of HDFS blocks =  no. of input splits. But this is
>>>> only true when you set isSplittable() as false or when your input file size
>>>> is less than the block size. Also, when it comes to text files, the default
>>>> textinputformat considers each line as one input split which can be then
>>>> read by RecordReader in K,V format.
>>>>
>>>> Please correct me if I don't make sense.
>>>>
>>>> --
>>>> Thanks & Regards,
>>>> Sugandha Naolekar
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Tue, Feb 25, 2014 at 2:07 PM, Bertrand Dechoux <dechouxb@gmail.com>wrote:
>>>>
>>>>> The wiki (or Hadoop The Definitive Guide) are good ressources.
>>>>>
>>>>> https://www.inkling.com/read/hadoop-definitive-guide-tom-white-3rd/chapter-7/input-formats
>>>>>
>>>>> Mapper is the name of the abstract class/interface. It does not really
>>>>> make sense to talk about number of mappers.
>>>>> A task is a jvm that can be launched only if there is a free slot ie
>>>>> for a given slot, at a given time, there will be at maximum only a single
>>>>> task. During the task, the configured Mapper will be instantiated.
>>>>>
>>>>> Always :
>>>>> Number of input splits = no. of map tasks
>>>>>
>>>>> And generally :
>>>>> number of hdfs blocks = number of input splits
>>>>>
>>>>> Regards
>>>>>
>>>>> Bertrand
>>>>>
>>>>> PS : I don't know if it is only my client, but avoid red when writting
>>>>> a mail.
>>>>>
>>>>> On Tue, Feb 25, 2014 at 8:49 AM, Dieter De Witte <drdwitte@gmail.com>wrote:
>>>>>
>>>>>> Each node has a tasktracker with a number of map slots. A map slot
>>>>>> hosts as mapper. A mapper executes map tasks. If there are more map
tasks
>>>>>> than slots obviously there will be multiple rounds of mapping.
>>>>>>
>>>>>> The map function is called once for each input record. A block is
>>>>>> typically 64MB and can contain a multitude of record, therefore a
map task
>>>>>> = run the map() function on all records in the block.
>>>>>>
>>>>>> Number of blocks = no. of map tasks (not mappers)
>>>>>>
>>>>>> Furthermore you have to make a distinction between the two layers.
>>>>>> You have a layer for computations which consists of a jobtracker
and a set
>>>>>> of tasktrackers. The other layer is responsible for storage. The
HDFS has a
>>>>>> namenode and a set of datanodes.
>>>>>>
>>>>>> In mapreduce the code is executed where the data is. So if a block
is
>>>>>> in datanode 1, 2 and 3, then the map task associated with this block
will
>>>>>> likely be executed on one of those physical nodes, by tasktracker
1, 2 or
>>>>>> 3. But this is not necessary, thing can be rearranged.
>>>>>>
>>>>>> Hopefully this gives you a little more insigth.
>>>>>>
>>>>>> Regards, Dieter
>>>>>>
>>>>>>
>>>>>> 2014-02-25 7:05 GMT+01:00 Sugandha Naolekar <sugandha.n87@gmail.com>:
>>>>>>
>>>>>>  One more thing to ask: No. of blocks = no. of mappers. Thus, those
>>>>>>> many no. of times the map() function will be called right?
>>>>>>>
>>>>>>> --
>>>>>>> Thanks & Regards,
>>>>>>> Sugandha Naolekar
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Tue, Feb 25, 2014 at 11:27 AM, Sugandha Naolekar <
>>>>>>> sugandha.n87@gmail.com> wrote:
>>>>>>>
>>>>>>>> Hello,
>>>>>>>>
>>>>>>>> As per the various articles I went through till date, the
File(s)
>>>>>>>> are split in chunks/blocks. On the same note, would like
to ask few things:
>>>>>>>>
>>>>>>>>
>>>>>>>>    1. No. of mappers are decided as: Total_File_Size/Max.
Block
>>>>>>>>    Size. Thus, if the file is smaller than the block size,
only one mapper
>>>>>>>>    will be invoked. Right?
>>>>>>>>    2. If yes, it means, the map() will be called only once.
Right?
>>>>>>>>    In this case, if there are two datanodes with a replication
factor as 1:
>>>>>>>>    only one datanode(mapper machine) will perform the task.
Right?
>>>>>>>>    3. The map() function is called by all the datanodes/slaves
>>>>>>>>    right? If the no. of mappers are more than the no. of
slaves, what happens?
>>>>>>>>
>>>>>>>> --
>>>>>>>> Thanks & Regards,
>>>>>>>> Sugandha Naolekar
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>

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