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refactor: improve code and test coverage for MapReduce example (#6348)

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refactor: improve code and test coverage for MapReduce example
This commit is contained in:
Oleksandr Klymenko
2025-07-06 23:19:50 +02:00
committed by GitHub
parent 350f149657
commit 4b6006c876
2 changed files with 30 additions and 39 deletions
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47
src/main/java/com/thealgorithms/misc/MapReduce.java
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@@ -7,35 +7,34 @@ import java.util.Map;
import java.util.function.Function;
import java.util.stream.Collectors;
/*
* MapReduce is a programming model for processing and generating large data sets with a parallel,
distributed algorithm on a cluster.
* It has two main steps: the Map step, where the data is divided into smaller chunks and processed in parallel,
and the Reduce step, where the results from the Map step are combined to produce the final output.
* Wikipedia link : https://en.wikipedia.org/wiki/MapReduce
*/
/**
* MapReduce is a programming model for processing and generating large data sets
* using a parallel, distributed algorithm on a cluster.
* It consists of two main phases:
* - Map: the input data is split into smaller chunks and processed in parallel.
* - Reduce: the results from the Map phase are aggregated to produce the final output.
*
* See also: https://en.wikipedia.org/wiki/MapReduce
*/
public final class MapReduce {
private MapReduce() {
}
/*
*Counting all the words frequency within a sentence.
/**
* Counts the frequency of each word in a given sentence using a simple MapReduce-style approach.
*
* @param sentence the input sentence
* @return a string representing word frequencies in the format "word: count,word: count,..."
*/
public static String mapreduce(String sentence) {
List<String> wordList = Arrays.stream(sentence.split(" ")).toList();
public static String countWordFrequencies(String sentence) {
// Map phase: split the sentence into words
List<String> words = Arrays.asList(sentence.trim().split("\\s+"));
// Map step
Map<String, Long> wordCounts = wordList.stream().collect(Collectors.groupingBy(Function.identity(), LinkedHashMap::new, Collectors.counting()));
// Group and count occurrences of each word, maintain insertion order
Map<String, Long> wordCounts = words.stream().collect(Collectors.groupingBy(Function.identity(), LinkedHashMap::new, Collectors.counting()));
// Reduce step
StringBuilder result = new StringBuilder();
wordCounts.forEach((word, count) -> result.append(word).append(": ").append(count).append(","));
// Removing the last ',' if it exists
if (!result.isEmpty()) {
result.setLength(result.length() - 1);
}
return result.toString();
// Reduce phase: format the result
return wordCounts.entrySet().stream().map(entry -> entry.getKey() + ": " + entry.getValue()).collect(Collectors.joining(","));
}
}