For each intermediate key, each reducer task can emit:
A.
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).
B.
As many final key-value pairs as desired, but they must have the same type as the intermediate
key-value pairs.
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.
One final key-value pair per value associated with the key; no restrictions on the type.
E.
One final key-value pair per key; no restrictions on the type.
Explanation:
Reducer reduces a set of intermediate values which share a key to a smaller set of
values.
Reducing lets you aggregate values together. A reducer function receives an iterator of input
values from an input list. It then combines these values together, returning a single output value.
Reference: Hadoop Map-Reduce Tutorial; Yahoo! Hadoop Tutorial, Module 4: MapReduce
Correct answer is C
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Answer is E. reducer emit one key-value pair.no restrication on the type.
If Maper the answer is C.
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Reducer can emit 0,1 or many K,V pairs.But they should be of same type.
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But point E says “no restriction on type” . Thats not true. The Out Format is already defined in the driver class.
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Yes, E is not correct. C is the correct answer
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C
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Ya think its C
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Yes C is the correct answer
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Answer is C .
For each input k1, v1 map emits zero or more k2, v2.
For each k2 reducer receives k2, list(v1,v3,v4..).
For each input k2, list(v) reducer can emit zero or more k3, v3.
Values are arbitrarily ordered in step 2. Key, value – output of mapper and reducer should be of same type i.e. all key must be same type and all value must be same type.
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I have the same idea. E
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