Passing keys and values to the reducers during a standard sort and shuffle phase of MapReduce

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I am working with MapReduce and I want to know that how are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?

Can someone help!
Jul 27, 2018 in Big Data Hadoop by Meci Matt
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Let me explain you the whole scenario

Reducer has 3 primary phases: 
 
1. Shuffle The Reducer copies the sorted output from each Mapper using HTTP across the network. 
 
2. Sort The framework merge sorts Reducer inputs by keys (since different Mappers may have output the same key). 
 
The shuffle and sort phases occur simultaneously i.e. while outputs are being fetched they are merged. 
 
SecondarySort To achieve a secondary sort on the values returned by the value iterator, the application should extend the key with the secondary key and define a grouping comparator. The keys will be sorted using the entire key, but will be grouped using the grouping comparator to decide which keys and values are sent in the same call to reduce. 
 
3. Reduce In this phase the reduce(Object, Iterable, Context) method is called for each <key, (collection of values)> in the sorted inputs. 
 
The output of the reduce task is typically written to a RecordWriter via TaskInputOutputContext.write(Object, Object). 
 
The output of the Reducer is not re-sorted. 
Hope this will help!

answered Jul 27, 2018 by nitinrawat895
• 9,450 points

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