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What Is the Role of the Reduce Function in a Hadoop Word Count Program?
Learn the exact role of the Reduce function in Hadoop’s Word Count program for your Big Data certification. Understand how it aggregates intermediate key-value pairs emitted by the Mapper to calculate final word frequencies.
Question
What is the role of the Reduce function in Word Count?
A. It splits text into tokens
B. It aggregates the counts of words emitted by the Map function
C. It replicates data across DataNodes
D. It stores metadata in the NameNode
Answer
B. It aggregates the counts of words emitted by the Map function
Explanation
In the Word Count program, the Reduce function takes the intermediate key-value pairs generated by the Map function and aggregates them based on their keys. Because the framework automatically groups all identical keys (words) together, the Reducer receives each unique word along with a list of its corresponding counts (e.g., <“Hadoop”, [1, 1, 1]>). The Reduce method then iterates through this list, summing the values to produce a final, aggregated key-value pair that represents the total frequency of that specific word in the input text. It does not split text (which is the Mapper’s job), replicate data, or store metadata.