For the word count example, for the input of the Map function, keys are document IDs and values are document contents. For the output of the Map function, keys are words and values are counts of words (e.g., (a, 1)). After shuffling via a hashing function on keys of the output, we combine those values with the same key into a list, for example, (a, {1, 5}), which are used as the input of the Reduce function. Within the reduce function, it will count (sum up) the numbers in the value list of a key, and return the key/value pair (e.g., (a, 6)). How to Implement the WordCount example on Hadoop?

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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For the word count example, for the input of the Map function, keys are document

IDs and values are document contents. For the output of the Map function, keys are

words and values are counts of words (e.g., (a, 1)). After shuffling via a hashing

function on keys of the output, we combine those values with the same key into a

list, for example, (a, {1, 5}), which are used as the input of the Reduce function.

Within the reduce function, it will count (sum up) the numbers in the value list of a

key, and return the key/value pair (e.g., (a, 6)). How to Implement the WordCount example on Hadoop?

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