A. A MapReduce job usually splits the input data-set into independent chunks which are processed by the map tasks in a completely parallel manner
B. The MapReduce framework operates exclusively on <key, value> pairs
C. Applications typically implement the Mapper and Reducer interfaces to provide the map and reduce methods
D. None of the mentioned
Answer: Option D
This Question Belongs to Hadoop >> MapReduce Programming Model
What is the primary function of the MapReduce programming model in Hadoop?
A. Real-time data processing
B. Batch processing of large datasets
C. Querying structured data
D. High-speed data ingestion
In the MapReduce model, what does the Map phase handle?
A. Data ingestion
B. Data processing
C. Data storage
D. Task scheduling
What does the Shuffle phase in MapReduce involve?
A. Data compression
B. Data distribution to reducers
C. Data sorting and grouping
D. Data storage in HBase
What is the role of the Combiner in the MapReduce model?
A. Data compression
B. Combine intermediate key-value pairs on the mapper side
C. Aggregate values on the reducer side
D. Data sorting and grouping
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