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This question should be clarified a bit to say how many workers are there. Otherwise both true and false can be correct. If there are less workers then maps which are running at given moment will be less. Otherwise if more or equal workers are available then all can run.
In an ideal implementation for your size M, it should be true but obviously it isn't always true and is therefore false. We don't have an infinite number of processors.
The question is wrong IMHO. Number of workers is totally independent on number of data partitions. You can have mn.
The question should be "the number of workers is typically...", "you can have M workers", "you must have at least M workers", "you can't have more than M workers", "if you have M workers, you get better performance than M/2 workers" or something like that...
True but on a logical perspective, the maximum number of physical workers on your problem is going to be M. I presume, one's operating system would hide this, no?
Empty Editorial, seriously??
False. There are generally less worker nodes than partitions
Assuming I have my terminology correct, this is simply because nobody owns an infinite number of processors and therefore if the problem is large enough, we will have less?
very nice for beginner of given domain
This Question Should be clarified
Map/Reduce Library partitions the input data into M pieces of typically 16-64 MB.
If there are M partitions of the input, there are M map workers running simultaneously.
False. There are generally less worker nodes than partitions.
Reduce function accepts intermediate key and a set of values for that key and merges together these values to form possibly a smaller set of values.
Map and Reduce are user defined functions
MapReduce is a restricted programming model?
Thanks for valuable question
what exactly is a map worker in this context? Would someone recommend a resource to study up on this?
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The correct answer is False
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