EMERGING TRENDS IN COMPUTING
CLOUD COMPUTING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following statements are true about key/value pairs in Hadoop?
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A map() function can emit up to a maximum number of key/value pairs (depending on the Hadoop environment).
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A map() function can emit anything between zero and an unlimited number of key/value pairs.
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A reduce() function can iterate over key/value pairs multiple times.
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A call to reduce() is guaranteed to receive key/value pairs from only one key.
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Explanation:
Detailed explanation-1: -Hadoop MapReduce uses a key-value pair to process the data in an efficient manner. The MapReduce concept is actually derived from Google white papers which uses this concept. Key-value pairs are not part of the input data, but rather the input data is split in the form of key and value to be processed in the mapper.
Detailed explanation-2: -Answer: A MapReduce partitioner makes sure that all the value of a single key goes to the same reducer thus allows evenly distribution of the map output over the reducers.
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