Add ReservoirSampling algorithm to randomized module

src/main/java/com/thealgorithms/randomized/ReservoirSampling.java

@@ -0,0 +1,63 @@
+package com.thealgorithms.randomized;
+
+import java.util.Random;
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * Reservoir Sampling Algorithm
+ *
+ * Use Case:
+ * - Efficient for selecting k random items from a stream of unknown size
+ * - Used in streaming systems, big data, and memory-limited environments
+ *
+ * Time Complexity: O(n)
+ * Space Complexity: O(k)
+ *
+ * Author: Michael Alexander Montoya (@cureprotocols)
+ */
+public class ReservoirSampling {
+
+    /**
+     * Selects k random elements from a stream using reservoir sampling.
+     *
+     * @param stream     The input stream as an array of integers.
+     * @param sampleSize The number of elements to sample.
+     * @return A list containing k randomly selected elements.
+     */
+    public static List<Integer> sample(int[] stream, int sampleSize) {
+        if (sampleSize > stream.length) {
+            throw new IllegalArgumentException("Sample size cannot exceed stream size.");
+        }
+
+        List<Integer> reservoir = new ArrayList<>(sampleSize);
+        Random rand = new Random();
+
+        for (int i = 0; i < stream.length; i++) {
+            if (i < sampleSize) {
+                reservoir.add(stream[i]);
+            } else {
+                int j = rand.nextInt(i + 1);
+                if (j < sampleSize) {
+                    reservoir.set(j, stream[i]);
+                }
+            }
+        }
+
+        return reservoir;
+    }
+
+    // Demo usage
+    public static void main(String[] args) {
+        int[] streamData = new int[1000];
+        for (int i = 0; i < 1000; i++) {
+            streamData[i] = i + 1;
+        }
+
+        List<Integer> result = ReservoirSampling.sample(streamData, 10);
+        System.out.println("Random sample of 10 items:");
+        for (int value : result) {
+            System.out.print(value + " ");
+        }
+    }
+}