A. Hadoop works better with a small number of large files than a large number of small files
B. CombineFileInputFormat is designed to work well with small files
C. CombineFileInputFormat does not compromise the speed at which it can process the input in a typical MapReduce job
D. None of the mentioned
Answer: Option C
This Question Belongs to Hadoop >> Advanced MapReduce Concepts
What is the purpose of the Hadoop Distributed Cache in MapReduce?
A. Store intermediate data
B. Cache files for tasks
C. Manage computation resources
D. Execute MapReduce jobs
In Hadoop MapReduce, what is the role of the Hadoop Counters?
A. Track the progress of MapReduce jobs
B. Manage computation resources
C. Execute MapReduce jobs
D. Manage Hadoop ecosystem tools
What is the function of the Hadoop InputSplit in MapReduce?
A. Represents a chunk of input data
B. Combine intermediate key-value pairs on the mapper side
C. Aggregate values on the reducer side
D. Convert data into a binary format
In advanced MapReduce, what is the significance of the Hadoop Combiner class?
A. Combine intermediate key-value pairs on the mapper side
B. Aggregate values on the reducer side
C. Sort and shuffle data
D. Distribute data to reducers
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