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From jaylac <Jayalakshmi.Munias...@cognizant.com>
Subject Re: MapReduce
Date Fri, 02 Mar 2007 17:32:48 GMT
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Is that necessary to find the key/value pairs for fitting a problem to
mapreduce..... If we dont use key/value pairs, shouldn't we call it as
MapReduce?

Coz my project manager has proposed an idea to fit our problem into
mapreduce... in that there is no key/value pairs... but he is telling that
we can have MapReduce without key/value pairs....

Albert Chern wrote:
>
> Sometimes you need to do a little work to fit a problem into map reduce.
> You are correct; in this problem, there really are no key/value pairs, so
> you would use a dummy value.  For example, we could just use 0 as a key,
> so
> our test scores are:
>
> (0, 95)
> (0,100)
> (0, 70)
> and so on...
>
> Each map gets one of these and subtracts one from the score, giving us:
>
> (0, 94)
> (0, 99)
> (0, 69)
> and so on...
>
> There will be a reduce for each key, but we only have one key, so there
> will
> be one reduce that gets:
>
> (0, [94,99,69,...])
>
> The Wikipedia example isn't very good, but we can make it better by
> dividing
> the scores into scores for different subjects where we want to find the
> average for each subject.  We might have:
>
> (Biology, 100)
> (Biology, 95)
> (Biology, 90)
> and so on...
>
> (Chemistry, 90)
> (Chemistry, 85)
> (Chemistry, 80)
> and so on...
>
> After you subtract one from each of these key/value pairs, there will be a
> reduce for each key, which are the different subjects.  So you will have
> one
> reduce for each subject:
>
> (Biology, [99,94,89,...])
> (Chemistry, [89,84,79,...])
> and so on...
>
> One more thing: the Wikipedia example says that each reduce outputs one
> value.  This isn't a requirement for Hadoop map reduce.
>
> On 3/1/07, jaylac <Jayalakshmi.Muniasamy@cognizant.com> wrote:
>>
>>
>> Hi
>>
>> I was just going thro abt MapReduce for my final year project work.....
>>
>> I got confused in the middle.... What i thought is "MapReduce deals
>> greatly
>> with key/value pairs only... For fitting a problem into mapreduce we
>> should
>> find the key/value pairs"
>>
>> I want to know whether im right or wrong....
>>
>> I got confused after looking at the explanation in wikipedia... The
>> following is the content in wikipedia abt mapreduce...
>>
>>
>> ========================================================================================
>> "A map function iterates over a list of independent elements and performs
>> a
>> specified operation on each element. The list of answers is stored
>> independently from the original list. Because each element is operated on
>> independently and the original list is not being modified, it is very
>> easy
>> to perform a map operation in parallel. On appropriate hardware this
>> allows
>> extremely large data sets to be processed in short amounts of elapsed
>> time.
>>
>> For example consider a list of test scores where each score has been
>> found
>> to be 1 too high. A map function of s − 1 could be applied to correct
>> every
>> score s.
>>
>> A reduce operation takes a list and combines elements according to some
>> algorithm. Since a reduce always ends up with a single answer, it is not
>> as
>> parallelizable as a map function, but the large number of relatively
>> independent calculations means that reduce functions are still useful in
>> highly parallel environments.
>>
>> Continuing the previous example, what if one wanted to know the average
>> of
>> the test scores? One could define a reduce function which halved the size
>> of
>> the list by adding an entry in the list to its neighbor, recursively
>> continuing until there is only one (large) entry, and dividing the total
>> sum
>> by the original number of elements to get the average."
>>
>>
>> =========================================================================================
>>
>> Here in map function we are simply adding up the test scores.... we are
>> not
>> using any key/value pair..... Im totally confused....
>>
>> I might be wrong at any point... please someone help me out..... Am i
>> wrong
>> in the basic understanding of MapReduce itself..... Ill be thankful if
>> anyone explains me clearly...
>>
>>
>> Jaya
>>
>> --
>> View this message in context:
>> http://www.nabble.com/MapReduce-tf3331603.html#a9263847
>> Sent from the Hadoop Users mailing list archive at Nabble.com.
>>
>>
>
>

--
View this message in context: http://www.nabble.com/MapReduce-tf3331603.html#a9273832
Sent from the Hadoop Users mailing list archive at Nabble.com.

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