For each intermediate key, each reducer task can emit:
A.
One final key value pair per key; no restrictions on the type.
B.
One final key-value pair per value associated with the key; no restrictions on the type.
C.
As many final key-value pairs as desired, as long as all the keys have the same type and all the
values have the same type.
D.
As many final key-value pairs as desired, but they must have the same type as the intermediate
key-value pairs.
E.
As many final key value pairs as desired. There are no restrictions on the types of those keyvalue pairs (i.e., they can be heterogeneous)
Explanation:
Reducer reduces a set of intermediate values which share a key to a smaller set of
values.
Reference:Hadoop Map-Reduce Tutorial
Answer is D
emit as many key value pairs as desired but they must have same data type as intermediate keyvalues pairs
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C
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Answer is C, but should share the reason as well.
map: (K1, V1) → list(K2, V2)
reduce: (K2, list(V2)) → list(K3, V3)
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It is A only when all input keys are consolidated into one value(you are assuming word count)
What if there are two inputs as ,
Then there will be two outputs.
So it is D.
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A.
One final key value pair per key; no restrictions on the type.
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still ambiguous…Almost all options were given by different people…
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I choose A
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D is the answer
Two points here:
Reducer can emit many key-value pairs
All keys are of same type and values have the same type.
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