Table of Contents

Map Collections
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Lecture 36
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Java Programming (4343203)
Diploma in ICT - Semester IV
Gujarat Technological University

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Learning Objectives
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By the end of this lecture, you will be able to:

🗺️ Understand Map interface and key-value pair concepts
🔑 Master HashMap, LinkedHashMap, and TreeMap implementations
⚡ Compare performance characteristics of different Map types
🎯 Handle key collision and hashing strategies effectively
🔍 Navigate maps using various iteration techniques
📊 Apply maps for caching, indexing, and data organization
🛠️ Implement advanced map operations and transformations
💡 Choose appropriate Map implementation for specific use cases

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Map Interface Fundamentals
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Map Characteristics
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Key-Value Association
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Keys: Unique identifiers (no duplicates)
Values: Associated data (duplicates allowed)
Mappings: Key-value pairs (entries)
Not Part of Collection: Separate hierarchy

Core Map Operations
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import java.util.*;

public class MapBasicsDemo {
    public static void main(String[] args) {
        demonstrateBasicOperations();
        demonstrateBulkOperations();
        demonstrateViewOperations();
        demonstrateEntryOperations();
    }
    
    private static void demonstrateBasicOperations() {
        System.out.println("=== Basic Map Operations ===");
        
        Map<String, Integer> scores = new HashMap<>();
        
        // Adding key-value pairs
        scores.put("Alice", 95);
        scores.put("Bob", 87);
        scores.put("Charlie", 92);
        scores.put("Diana", 88);
        
        System.out.println("Scores map: " + scores);
        System.out.println("Map size: " + scores.size());
        
        // Accessing values
        Integer aliceScore = scores.get("Alice");
        System.out.println("Alice's score: " + aliceScore);
        
        Integer frankScore = scores.get("Frank"); // Non-existent key
        System.out.println("Frank's score: " + frankScore); // null
        
        // Default value for missing keys
        Integer defaultScore = scores.getOrDefault("Frank", 0);
        System.out.println("Frank's score (with default): " + defaultScore);
        
        // Checking for keys and values
        System.out.println("Contains key 'Bob': " + scores.containsKey("Bob"));
        System.out.println("Contains value 95: " + scores.containsValue(95));
        
        // Updating values
        Integer oldValue = scores.put("Bob", 90); // Updates existing key
        System.out.println("Bob's old score: " + oldValue);
        System.out.println("Updated scores: " + scores);
        
        // Removing entries
        Integer removedScore = scores.remove("Diana");
        System.out.println("Removed Diana's score: " + removedScore);
        System.out.println("After removal: " + scores);
        
        // putIfAbsent - only adds if key doesn't exist
        scores.putIfAbsent("Eve", 85); // Adds
        scores.putIfAbsent("Alice", 100); // Doesn't add (Alice exists)
        System.out.println("After putIfAbsent: " + scores);
    }
    
    private static void demonstrateBulkOperations() {
        System.out.println("\n=== Bulk Operations ===");
        
        Map<String, String> countries = new HashMap<>();
        countries.put("US", "United States");
        countries.put("UK", "United Kingdom");
        countries.put("CA", "Canada");
        
        Map<String, String> moreCountries = new HashMap<>();
        moreCountries.put("FR", "France");
        moreCountries.put("DE", "Germany");
        moreCountries.put("JP", "Japan");
        
        System.out.println("Original countries: " + countries);
        System.out.println("More countries: " + moreCountries);
        
        // putAll - adds all mappings from another map
        countries.putAll(moreCountries);
        System.out.println("After putAll: " + countries);
        
        // clear - removes all mappings
        Map<String, String> tempMap = new HashMap<>(countries);
        tempMap.clear();
        System.out.println("After clear: " + tempMap);
        System.out.println("Is empty: " + tempMap.isEmpty());
        
        // replaceAll - transforms all values
        Map<String, Integer> wordLengths = new HashMap<>();
        wordLengths.put("Java", 4);
        wordLengths.put("Python", 6);
        wordLengths.put("JavaScript", 10);
        
        System.out.println("Original word lengths: " + wordLengths);
        
        // Double all values
        wordLengths.replaceAll((key, value) -> value * 2);
        System.out.println("After replaceAll (doubled): " + wordLengths);
    }
    
    private static void demonstrateViewOperations() {
        System.out.println("\n=== View Operations ===");
        
        Map<String, Integer> inventory = new HashMap<>();
        inventory.put("Apples", 50);
        inventory.put("Bananas", 30);
        inventory.put("Cherries", 25);
        inventory.put("Dates", 15);
        
        System.out.println("Inventory: " + inventory);
        
        // Key set view
        Set<String> products = inventory.keySet();
        System.out.println("Products: " + products);
        
        // Values collection view
        Collection<Integer> quantities = inventory.values();
        System.out.println("Quantities: " + quantities);
        System.out.println("Total quantity: " + 
                          quantities.stream().mapToInt(Integer::intValue).sum());
        
        // Entry set view
        Set<Map.Entry<String, Integer>> entries = inventory.entrySet();
        System.out.println("Entries:");
        for (Map.Entry<String, Integer> entry : entries) {
            System.out.println("  " + entry.getKey() + " -> " + entry.getValue());
        }
        
        // Modifying views affects original map
        products.remove("Dates"); // Removes from original map
        System.out.println("After removing from key set: " + inventory);
        
        // Cannot add to key set or values collection
        try {
            // products.add("Grapes"); // UnsupportedOperationException
            // quantities.add(100);    // UnsupportedOperationException
        } catch (UnsupportedOperationException e) {
            System.out.println("Cannot add to views directly");
        }
    }
    
    private static void demonstrateEntryOperations() {
        System.out.println("\n=== Entry Operations ===");
        
        Map<String, Double> prices = new HashMap<>();
        prices.put("Coffee", 4.50);
        prices.put("Tea", 3.25);
        prices.put("Juice", 5.75);
        prices.put("Water", 2.00);
        
        System.out.println("Original prices: " + prices);
        
        // Working with entries
        for (Map.Entry<String, Double> entry : prices.entrySet()) {
            String product = entry.getKey();
            Double price = entry.getValue();
            
            // Apply 10% discount to expensive items
            if (price > 4.0) {
                entry.setValue(price * 0.9);
                System.out.println("Applied discount to " + product);
            }
        }
        
        System.out.println("After discounts: " + prices);
        
        // merge operation - combines values for same key
        Map<String, Integer> sales = new HashMap<>();
        sales.put("Monday", 100);
        sales.put("Tuesday", 150);
        
        // Add more sales data
        sales.merge("Monday", 50, Integer::sum);    // 100 + 50 = 150
        sales.merge("Wednesday", 75, Integer::sum); // New entry: 75
        
        System.out.println("Sales data: " + sales);
        
        // compute - calculate value for a key
        sales.compute("Thursday", (key, value) -> {
            return (value == null) ? 80 : value + 20;
        });
        
        sales.computeIfAbsent("Friday", key -> 90);
        sales.computeIfPresent("Monday", (key, value) -> value + 25);
        
        System.out.println("After compute operations: " + sales);
    }
}

HashMap Implementation
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HashMap Deep Dive
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import java.util.*;

public class HashMapDemo {
    public static void main(String[] args) {
        demonstrateHashingConcepts();
        demonstrateCollisionHandling();
        demonstratePerformanceCharacteristics();
        demonstrateCapacityAndLoadFactor();
    }
    
    private static void demonstrateHashingConcepts() {
        System.out.println("=== HashMap Hashing Concepts ===");
        
        Map<String, String> map = new HashMap<>();
        
        // Add some key-value pairs
        map.put("name", "John");
        map.put("age", "30");
        map.put("city", "New York");
        
        System.out.println("Map contents: " + map);
        
        // Demonstrate hash codes of keys
        System.out.println("\nHash codes of keys:");
        for (String key : map.keySet()) {
            System.out.println(key + " -> hash: " + key.hashCode());
        }
        
        // Show that hash code affects internal organization
        Map<Integer, String> numberMap = new HashMap<>();
        for (int i = 1; i <= 10; i++) {
            numberMap.put(i, "Value" + i);
        }
        
        System.out.println("\nNumber map: " + numberMap);
        System.out.println("Note: Order is not insertion order due to hashing");
    }
    
    private static void demonstrateCollisionHandling() {
        System.out.println("\n=== Collision Handling ===");
        
        // Custom class that demonstrates hash collisions
        Map<HashKey, String> collisionMap = new HashMap<>();
        
        HashKey key1 = new HashKey(1, "A");
        HashKey key2 = new HashKey(2, "B");
        HashKey key3 = new HashKey(3, "C");
        HashKey key4 = new HashKey(4, "A"); // Same hash as key1
        
        collisionMap.put(key1, "Value1");
        collisionMap.put(key2, "Value2");
        collisionMap.put(key3, "Value3");
        collisionMap.put(key4, "Value4"); // Hash collision with key1
        
        System.out.println("Map with hash collisions:");
        for (Map.Entry<HashKey, String> entry : collisionMap.entrySet()) {
            HashKey key = entry.getKey();
            System.out.println(key + " (hash: " + key.hashCode() + ") -> " + entry.getValue());
        }
        
        System.out.println("\nHashMap handles collisions using:");
        System.out.println("1. Chaining (linked list/tree for same hash bucket)");
        System.out.println("2. equals() method to distinguish between keys");
        System.out.println("3. Tree structure for long chains (Java 8+)");
    }
    
    private static void demonstratePerformanceCharacteristics() {
        System.out.println("\n=== Performance Characteristics ===");
        
        Map<Integer, String> hashMap = new HashMap<>();
        
        // Performance test: put operations
        long startTime = System.nanoTime();
        for (int i = 0; i < 100000; i++) {
            hashMap.put(i, "Value" + i);
        }
        long putTime = System.nanoTime() - startTime;
        
        // Performance test: get operations
        startTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {
            int randomKey = (int) (Math.random() * 100000);
            hashMap.get(randomKey);
        }
        long getTime = System.nanoTime() - startTime;
        
        // Performance test: containsKey operations
        startTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {
            int randomKey = (int) (Math.random() * 100000);
            hashMap.containsKey(randomKey);
        }
        long containsTime = System.nanoTime() - startTime;
        
        System.out.println("Performance results:");
        System.out.println("Put 100,000 elements: " + putTime + " ns");
        System.out.println("Get 10,000 elements: " + getTime + " ns");
        System.out.println("Contains 10,000 elements: " + containsTime + " ns");
        System.out.println("\nHashMap provides O(1) average-case performance");
        System.out.println("Worst case: O(n) if all keys hash to same bucket");
    }
    
    private static void demonstrateCapacityAndLoadFactor() {
        System.out.println("\n=== Capacity and Load Factor ===");
        
        // Default HashMap (capacity=16, load factor=0.75)
        Map<Integer, String> defaultMap = new HashMap<>();
        System.out.println("Default HashMap created");
        
        // HashMap with initial capacity
        Map<Integer, String> capacityMap = new HashMap<>(100);
        System.out.println("HashMap with initial capacity 100");
        
        // HashMap with capacity and load factor
        Map<Integer, String> customMap = new HashMap<>(50, 0.9f);
        System.out.println("HashMap with capacity 50 and load factor 0.9");
        
        // Demonstrate resizing effect
        Map<Integer, String> resizeTest = new HashMap<>(4); // Small initial capacity
        
        System.out.println("\nDemonstrating resize behavior:");
        for (int i = 0; i < 10; i++) {
            resizeTest.put(i, "Value" + i);
            if (i == 2 || i == 5 || i == 9) {
                System.out.println("After adding " + (i + 1) + " elements: " + 
                                 "size=" + resizeTest.size());
                // Internal capacity would have grown at load factor threshold
            }
        }
        
        System.out.println("\nLoad factor controls when HashMap resizes:");
        System.out.println("- Default load factor: 0.75");
        System.out.println("- Resize occurs when: size > capacity * load_factor");
        System.out.println("- New capacity: old_capacity * 2");
        System.out.println("- Choose initial capacity to minimize resizing");
    }
    
    // Helper class for collision demonstration
    static class HashKey {
        private int id;
        private String category;
        
        public HashKey(int id, String category) {
            this.id = id;
            this.category = category;
        }
        
        @Override
        public boolean equals(Object obj) {
            if (this == obj) return true;
            if (obj == null || getClass() != obj.getClass()) return false;
            HashKey hashKey = (HashKey) obj;
            return id == hashKey.id && Objects.equals(category, hashKey.category);
        }
        
        @Override
        public int hashCode() {
            // Deliberately simple hash function to create collisions
            return category.hashCode() % 3;
        }
        
        @Override
        public String toString() {
            return "HashKey{id=" + id + ", category='" + category + "'}";
        }
    }
}

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LinkedHashMap and TreeMap
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LinkedHashMap Implementation
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LinkedHashMap Features
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import java.util.*;

public class LinkedHashMapDemo {
    public static void main(String[] args) {
        demonstrateInsertionOrder();
        demonstrateAccessOrder();
        demonstrateLRUCache();
        demonstratePerformanceComparison();
    }
    
    private static void demonstrateInsertionOrder() {
        System.out.println("=== LinkedHashMap Insertion Order ===");
        
        // HashMap - no guaranteed order
        Map<String, Integer> hashMap = new HashMap<>();
        hashMap.put("Zebra", 1);
        hashMap.put("Apple", 2);
        hashMap.put("Banana", 3);
        hashMap.put("Cherry", 4);
        
        System.out.println("HashMap order: " + hashMap);
        
        // LinkedHashMap - maintains insertion order
        Map<String, Integer> linkedHashMap = new LinkedHashMap<>();
        linkedHashMap.put("Zebra", 1);
        linkedHashMap.put("Apple", 2);
        linkedHashMap.put("Banana", 3);
        linkedHashMap.put("Cherry", 4);
        
        System.out.println("LinkedHashMap order: " + linkedHashMap);
        
        // Order preserved during iteration
        System.out.print("Iteration order: ");
        for (Map.Entry<String, Integer> entry : linkedHashMap.entrySet()) {
            System.out.print(entry.getKey() + " ");
        }
        System.out.println();
        
        // Updating value doesn't change order
        linkedHashMap.put("Apple", 22); // Update existing key
        linkedHashMap.put("Date", 5);   // Add new key
        System.out.println("After update and addition: " + linkedHashMap);
    }
    
    private static void demonstrateAccessOrder() {
        System.out.println("\n=== LinkedHashMap Access Order ===");
        
        // LinkedHashMap with access order (true parameter)
        Map<String, String> accessOrderMap = new LinkedHashMap<>(16, 0.75f, true);
        
        accessOrderMap.put("First", "1st");
        accessOrderMap.put("Second", "2nd");
        accessOrderMap.put("Third", "3rd");
        accessOrderMap.put("Fourth", "4th");
        
        System.out.println("Initial order: " + accessOrderMap);
        
        // Access elements (get operations change order)
        accessOrderMap.get("Second"); // Moves "Second" to end
        System.out.println("After accessing 'Second': " + accessOrderMap);
        
        accessOrderMap.get("First");  // Moves "First" to end
        System.out.println("After accessing 'First': " + accessOrderMap);
        
        // put operation also counts as access
        accessOrderMap.put("Third", "3rd updated"); // Moves "Third" to end
        System.out.println("After updating 'Third': " + accessOrderMap);
        
        System.out.println("\nAccess order maintains recently accessed items at the end");
    }
    
    private static void demonstrateLRUCache() {
        System.out.println("\n=== LRU Cache Implementation ===");
        
        // LRU Cache with maximum capacity of 3
        LRUCache<String, String> cache = new LRUCache<>(3);
        
        System.out.println("Adding items to LRU cache (capacity=3):");
        
        cache.put("Page1", "Content1");
        System.out.println("Added Page1: " + cache);
        
        cache.put("Page2", "Content2");
        System.out.println("Added Page2: " + cache);
        
        cache.put("Page3", "Content3");
        System.out.println("Added Page3: " + cache);
        
        // Access Page1 (moves to end)
        cache.get("Page1");
        System.out.println("Accessed Page1: " + cache);
        
        // Add Page4 (should evict Page2 - least recently used)
        cache.put("Page4", "Content4");
        System.out.println("Added Page4 (Page2 evicted): " + cache);
        
        // Access Page3 and add Page5
        cache.get("Page3");
        cache.put("Page5", "Content5");
        System.out.println("Added Page5 (Page1 evicted): " + cache);
    }
    
    private static void demonstratePerformanceComparison() {
        System.out.println("\n=== Performance Comparison ===");
        
        int operations = 100000;
        
        // HashMap performance
        Map<Integer, String> hashMap = new HashMap<>();
        long startTime = System.nanoTime();
        for (int i = 0; i < operations; i++) {
            hashMap.put(i, "Value" + i);
        }
        long hashMapTime = System.nanoTime() - startTime;
        
        // LinkedHashMap performance
        Map<Integer, String> linkedHashMap = new LinkedHashMap<>();
        startTime = System.nanoTime();
        for (int i = 0; i < operations; i++) {
            linkedHashMap.put(i, "Value" + i);
        }
        long linkedHashMapTime = System.nanoTime() - startTime;
        
        System.out.println("Performance for " + operations + " put operations:");
        System.out.println("HashMap: " + hashMapTime + " ns");
        System.out.println("LinkedHashMap: " + linkedHashMapTime + " ns");
        System.out.println("Overhead: " + 
                          ((double) linkedHashMapTime / hashMapTime) + "x");
        
        System.out.println("\nLinkedHashMap trades performance for order preservation");
        System.out.println("Additional memory overhead for maintaining doubly-linked list");
    }
    
    // LRU Cache implementation using LinkedHashMap
    static class LRUCache<K, V> extends LinkedHashMap<K, V> {
        private final int capacity;
        
        public LRUCache(int capacity) {
            super(capacity + 1, 1.0f, true); // access-order = true
            this.capacity = capacity;
        }
        
        @Override
        protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
            return size() > capacity;
        }
        
        @Override
        public String toString() {
            return "LRUCache" + super.toString();
        }
    }
}

TreeMap Implementation
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TreeMap Features
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import java.util.*;
import java.util.concurrent.ConcurrentSkipListMap;

public class TreeMapDemo {
    public static void main(String[] args) {
        demonstrateNaturalOrdering();
        demonstrateCustomOrdering();
        demonstrateNavigationMethods();
        demonstrateSubMapOperations();
        demonstratePerformanceAnalysis();
    }
    
    private static void demonstrateNaturalOrdering() {
        System.out.println("=== TreeMap Natural Ordering ===");
        
        TreeMap<String, Integer> wordCounts = new TreeMap<>();
        
        // Add words in random order
        wordCounts.put("zebra", 1);
        wordCounts.put("apple", 5);
        wordCounts.put("banana", 3);
        wordCounts.put("cherry", 7);
        wordCounts.put("date", 2);
        
        System.out.println("TreeMap (alphabetically sorted): " + wordCounts);
        
        // Numeric keys are sorted numerically
        TreeMap<Integer, String> scores = new TreeMap<>();
        scores.put(85, "Bob");
        scores.put(92, "Alice");
        scores.put(78, "Charlie");
        scores.put(95, "Diana");
        
        System.out.println("Score TreeMap (numerically sorted): " + scores);
        
        // Iteration is in sorted order
        System.out.println("Iteration order:");
        for (Map.Entry<Integer, String> entry : scores.entrySet()) {
            System.out.println("  Score " + entry.getKey() + ": " + entry.getValue());
        }
    }
    
    private static void demonstrateCustomOrdering() {
        System.out.println("\n=== TreeMap Custom Ordering ===");
        
        // Reverse order comparator
        TreeMap<String, Integer> reverseMap = new TreeMap<>(Collections.reverseOrder());
        reverseMap.put("Alpha", 1);
        reverseMap.put("Beta", 2);
        reverseMap.put("Gamma", 3);
        reverseMap.put("Delta", 4);
        
        System.out.println("Reverse alphabetical order: " + reverseMap);
        
        // Custom comparator - by string length
        TreeMap<String, Integer> lengthMap = new TreeMap<>(
            Comparator.comparing(String::length).thenComparing(String::compareTo)
        );
        
        lengthMap.put("Java", 1);
        lengthMap.put("C", 2);
        lengthMap.put("Python", 3);
        lengthMap.put("Go", 4);
        lengthMap.put("JavaScript", 5);
        lengthMap.put("C++", 6);
        
        System.out.println("Length-based ordering: " + lengthMap);
        
        // Complex object sorting
        TreeMap<Person, String> personMap = new TreeMap<>(
            Comparator.comparing(Person::getAge)
                     .thenComparing(Person::getName)
        );
        
        personMap.put(new Person("Alice", 30), "Engineer");
        personMap.put(new Person("Bob", 25), "Designer");
        personMap.put(new Person("Charlie", 30), "Manager"); // Same age as Alice
        personMap.put(new Person("Diana", 28), "Analyst");
        
        System.out.println("Person map (by age, then name):");
        for (Map.Entry<Person, String> entry : personMap.entrySet()) {
            System.out.println("  " + entry.getKey() + " -> " + entry.getValue());
        }
    }
    
    private static void demonstrateNavigationMethods() {
        System.out.println("\n=== TreeMap Navigation Methods ===");
        
        NavigableMap<Integer, String> treeMap = new TreeMap<>();
        treeMap.put(10, "Ten");
        treeMap.put(20, "Twenty");
        treeMap.put(30, "Thirty");
        treeMap.put(40, "Forty");
        treeMap.put(50, "Fifty");
        
        System.out.println("TreeMap: " + treeMap);
        
        // Navigation methods
        System.out.println("firstKey(): " + treeMap.firstKey());
        System.out.println("lastKey(): " + treeMap.lastKey());
        System.out.println("lowerKey(35): " + treeMap.lowerKey(35));   // < 35
        System.out.println("floorKey(35): " + treeMap.floorKey(35));   // <= 35
        System.out.println("ceilingKey(35): " + treeMap.ceilingKey(35)); // >= 35
        System.out.println("higherKey(35): " + treeMap.higherKey(35)); // > 35
        
        // Entry methods
        Map.Entry<Integer, String> firstEntry = treeMap.firstEntry();
        Map.Entry<Integer, String> lastEntry = treeMap.lastEntry();
        
        System.out.println("firstEntry(): " + firstEntry);
        System.out.println("lastEntry(): " + lastEntry);
        
        // Poll methods (remove and return)
        System.out.println("pollFirstEntry(): " + treeMap.pollFirstEntry());
        System.out.println("pollLastEntry(): " + treeMap.pollLastEntry());
        System.out.println("After polling: " + treeMap);
        
        // Descending view
        NavigableMap<Integer, String> descendingMap = treeMap.descendingMap();
        System.out.println("Descending view: " + descendingMap);
        
        // Descending key set
        NavigableSet<Integer> descendingKeys = treeMap.descendingKeySet();
        System.out.println("Descending keys: " + descendingKeys);
    }
    
    private static void demonstrateSubMapOperations() {
        System.out.println("\n=== TreeMap SubMap Operations ===");
        
        TreeMap<Integer, String> fullMap = new TreeMap<>();
        for (int i = 10; i <= 100; i += 10) {
            fullMap.put(i, "Value" + i);
        }
        
        System.out.println("Full map: " + fullMap);
        
        // SubMap operations
        SortedMap<Integer, String> headMap = fullMap.headMap(50); // < 50
        SortedMap<Integer, String> tailMap = fullMap.tailMap(50); // >= 50
        SortedMap<Integer, String> subMap = fullMap.subMap(30, 70); // [30, 70)
        
        System.out.println("headMap(50): " + headMap);
        System.out.println("tailMap(50): " + tailMap);
        System.out.println("subMap(30, 70): " + subMap);
        
        // NavigableMap versions with inclusive/exclusive bounds
        NavigableMap<Integer, String> navMap = fullMap;
        
        NavigableMap<Integer, String> headMapInclusive = navMap.headMap(50, true); // <= 50
        NavigableMap<Integer, String> subMapCustom = navMap.subMap(30, false, 70, true); // (30, 70]
        
        System.out.println("headMap(50, inclusive): " + headMapInclusive);
        System.out.println("subMap(30, false, 70, true): " + subMapCustom);
        
        // SubMaps are views - changes reflect in original
        headMap.put(25, "Value25"); // Adds to original map
        System.out.println("After adding to headMap: " + fullMap);
        
        // Range validation
        try {
            headMap.put(60, "Value60"); // Outside range
        } catch (IllegalArgumentException e) {
            System.out.println("Cannot add 60 to headMap: outside range");
        }
    }
    
    private static void demonstratePerformanceAnalysis() {
        System.out.println("\n=== Performance Analysis ===");
        
        int operations = 100000;
        
        // TreeMap performance
        Map<Integer, String> treeMap = new TreeMap<>();
        long startTime = System.nanoTime();
        for (int i = 0; i < operations; i++) {
            treeMap.put(i, "Value" + i);
        }
        long treeMapTime = System.nanoTime() - startTime;
        
        // HashMap performance for comparison
        Map<Integer, String> hashMap = new HashMap<>();
        startTime = System.nanoTime();
        for (int i = 0; i < operations; i++) {
            hashMap.put(i, "Value" + i);
        }
        long hashMapTime = System.nanoTime() - startTime;
        
        System.out.println("Performance for " + operations + " put operations:");
        System.out.println("TreeMap: " + treeMapTime + " ns (O(log n) per operation)");
        System.out.println("HashMap: " + hashMapTime + " ns (O(1) average per operation)");
        System.out.println("HashMap is " + ((double) treeMapTime / hashMapTime) + "x faster");
        
        // Search performance comparison
        startTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {
            int key = (int) (Math.random() * operations);
            treeMap.containsKey(key);
        }
        long treeMapSearchTime = System.nanoTime() - startTime;
        
        startTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {
            int key = (int) (Math.random() * operations);
            hashMap.containsKey(key);
        }
        long hashMapSearchTime = System.nanoTime() - startTime;
        
        System.out.println("\nSearch performance (10,000 operations):");
        System.out.println("TreeMap: " + treeMapSearchTime + " ns");
        System.out.println("HashMap: " + hashMapSearchTime + " ns");
        
        System.out.println("\nTreeMap advantages:");
        System.out.println("- Sorted order iteration");
        System.out.println("- Range queries (subMap, headMap, tailMap)");
        System.out.println("- Navigation methods (floor, ceiling, etc.)");
        System.out.println("- Consistent O(log n) performance");
        
        System.out.println("\nHashMap advantages:");
        System.out.println("- Faster basic operations O(1) average");
        System.out.println("- Lower memory overhead");
        System.out.println("- No ordering requirements");
    }
    
    static class Person {
        private String name;
        private int age;
        
        public Person(String name, int age) {
            this.name = name;
            this.age = age;
        }
        
        public String getName() { return name; }
        public int getAge() { return age; }
        
        @Override
        public String toString() {
            return name + "(" + age + ")";
        }
    }
}

layout: default
#

Advanced Map Operations and Patterns
#

Map Utility Methods and Patterns
#

Modern Map Operations (Java 8+)
#

import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.Function;
import java.util.stream.Collectors;

public class AdvancedMapOperations {
    public static void main(String[] args) {
        demonstrateComputeMethods();
        demonstrateMergeMethods();
        demonstrateStreamOperations();
        demonstratePatterns();
    }
    
    private static void demonstrateComputeMethods() {
        System.out.println("=== Compute Methods ===");
        
        Map<String, Integer> wordCount = new HashMap<>();
        String[] words = {"java", "python", "java", "javascript", "python", "java", "go"};
        
        // Traditional approach
        for (String word : words) {
            if (wordCount.containsKey(word)) {
                wordCount.put(word, wordCount.get(word) + 1);
            } else {
                wordCount.put(word, 1);
            }
        }
        System.out.println("Traditional word count: " + wordCount);
        
        // Using compute methods
        Map<String, Integer> betterWordCount = new HashMap<>();
        
        for (String word : words) {
            // compute: always calculates new value
            betterWordCount.compute(word, (key, value) -> 
                (value == null) ? 1 : value + 1);
        }
        System.out.println("Using compute: " + betterWordCount);
        
        // Using merge for same result
        Map<String, Integer> mergeWordCount = new HashMap<>();
        for (String word : words) {
            mergeWordCount.merge(word, 1, Integer::sum);
        }
        System.out.println("Using merge: " + mergeWordCount);
        
        // computeIfAbsent - for caching pattern
        Map<String, List<String>> categories = new HashMap<>();
        
        // Add items to categories
        addToCategory(categories, "programming", "Java");
        addToCategory(categories, "programming", "Python");
        addToCategory(categories, "database", "MySQL");
        addToCategory(categories, "programming", "JavaScript");
        addToCategory(categories, "database", "PostgreSQL");
        
        System.out.println("Categories: " + categories);
    }
    
    private static void addToCategory(Map<String, List<String>> categories, 
                                    String category, String item) {
        // Old way
        // List<String> items = categories.get(category);
        // if (items == null) {
        //     items = new ArrayList<>();
        //     categories.put(category, items);
        // }
        // items.add(item);
        
        // New way with computeIfAbsent
        categories.computeIfAbsent(category, k -> new ArrayList<>()).add(item);
    }
    
    private static void demonstrateMergeMethods() {
        System.out.println("\n=== Merge Methods ===");
        
        // Merging two maps
        Map<String, Integer> sales1 = new HashMap<>();
        sales1.put("Product A", 100);
        sales1.put("Product B", 150);
        sales1.put("Product C", 80);
        
        Map<String, Integer> sales2 = new HashMap<>();
        sales2.put("Product B", 120); // Overlapping key
        sales2.put("Product C", 90);  // Overlapping key
        sales2.put("Product D", 200); // New key
        
        System.out.println("Sales Q1: " + sales1);
        System.out.println("Sales Q2: " + sales2);
        
        // Merge sales2 into sales1
        Map<String, Integer> totalSales = new HashMap<>(sales1);
        sales2.forEach((product, amount) -> 
            totalSales.merge(product, amount, Integer::sum));
        
        System.out.println("Total sales: " + totalSales);
        
        // Replace vs merge behavior
        Map<String, String> config1 = new HashMap<>();
        config1.put("timeout", "30");
        config1.put("retries", "3");
        
        Map<String, String> config2 = new HashMap<>();
        config2.put("timeout", "60");
        config2.put("cache", "true");
        
        // Using putAll (replaces values)
        Map<String, String> combinedReplace = new HashMap<>(config1);
        combinedReplace.putAll(config2);
        System.out.println("putAll result: " + combinedReplace);
        
        // Using merge (can combine values)
        Map<String, String> combinedMerge = new HashMap<>(config1);
        config2.forEach((key, value) -> 
            combinedMerge.merge(key, value, (oldVal, newVal) -> oldVal + "," + newVal));
        System.out.println("merge result: " + combinedMerge);
    }
    
    private static void demonstrateStreamOperations() {
        System.out.println("\n=== Stream Operations with Maps ===");
        
        Map<String, Integer> inventory = new HashMap<>();
        inventory.put("Laptops", 15);
        inventory.put("Smartphones", 32);
        inventory.put("Tablets", 8);
        inventory.put("Monitors", 22);
        inventory.put("Keyboards", 45);
        
        System.out.println("Inventory: " + inventory);
        
        // Filter entries
        Map<String, Integer> lowStock = inventory.entrySet().stream()
            .filter(entry -> entry.getValue() < 20)
            .collect(Collectors.toMap(
                Map.Entry::getKey, 
                Map.Entry::getValue));
        System.out.println("Low stock items: " + lowStock);
        
        // Transform values
        Map<String, String> stockStatus = inventory.entrySet().stream()
            .collect(Collectors.toMap(
                Map.Entry::getKey,
                entry -> entry.getValue() > 20 ? "High" : "Low"));
        System.out.println("Stock status: " + stockStatus);
        
        // Group by value ranges
        Map<String, List<String>> stockRanges = inventory.entrySet().stream()
            .collect(Collectors.groupingBy(
                entry -> {
                    int qty = entry.getValue();
                    if (qty < 15) return "Low";
                    else if (qty < 30) return "Medium";
                    else return "High";
                },
                Collectors.mapping(Map.Entry::getKey, Collectors.toList())
            ));
        System.out.println("Stock ranges: " + stockRanges);
        
        // Calculate statistics
        IntSummaryStatistics stats = inventory.values().stream()
            .mapToInt(Integer::intValue)
            .summaryStatistics();
        
        System.out.println("Inventory statistics:");
        System.out.println("  Total items: " + stats.getSum());
        System.out.println("  Average: " + String.format("%.1f", stats.getAverage()));
        System.out.println("  Min: " + stats.getMin());
        System.out.println("  Max: " + stats.getMax());
    }
    
    private static void demonstratePatterns() {
        System.out.println("\n=== Common Map Patterns ===");
        
        // Pattern 1: Frequency counter
        String text = "the quick brown fox jumps over the lazy dog the fox";
        Map<String, Long> wordFrequency = Arrays.stream(text.split("\\s+"))
            .collect(Collectors.groupingBy(
                Function.identity(),
                Collectors.counting()));
        System.out.println("Word frequency: " + wordFrequency);
        
        // Pattern 2: Index building
        List<String> words = Arrays.asList("apple", "banana", "apricot", "blueberry", "cherry");
        Map<Character, List<String>> index = words.stream()
            .collect(Collectors.groupingBy(word -> word.charAt(0)));
        System.out.println("First letter index: " + index);
        
        // Pattern 3: Lookup table
        Map<Integer, String> statusCodes = Map.of(
            200, "OK",
            404, "Not Found",
            500, "Internal Server Error",
            403, "Forbidden"
        );
        
        int[] codes = {200, 404, 418, 500};
        for (int code : codes) {
            String status = statusCodes.getOrDefault(code, "Unknown Status");
            System.out.println("HTTP " + code + ": " + status);
        }
        
        // Pattern 4: Multi-value map
        Map<String, Set<String>> authorBooks = new HashMap<>();
        addBook(authorBooks, "Martin Fowler", "Refactoring");
        addBook(authorBooks, "Martin Fowler", "Patterns of Enterprise Application Architecture");
        addBook(authorBooks, "Robert Martin", "Clean Code");
        addBook(authorBooks, "Robert Martin", "Clean Architecture");
        addBook(authorBooks, "Martin Fowler", "Domain-Specific Languages");
        
        System.out.println("Author books: " + authorBooks);
        
        // Pattern 5: Caching with computeIfAbsent
        Map<String, ExpensiveResult> cache = new HashMap<>();
        
        String[] queries = {"query1", "query2", "query1", "query3", "query2"};
        for (String query : queries) {
            ExpensiveResult result = cache.computeIfAbsent(query, 
                key -> performExpensiveOperation(key));
            System.out.println("Query: " + query + " -> " + result.getValue() + 
                             " (cached: " + result.isCached() + ")");
        }
    }
    
    private static void addBook(Map<String, Set<String>> authorBooks, 
                              String author, String book) {
        authorBooks.computeIfAbsent(author, k -> new HashSet<>()).add(book);
    }
    
    private static ExpensiveResult performExpensiveOperation(String query) {
        // Simulate expensive operation
        try {
            Thread.sleep(100);
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
        return new ExpensiveResult("Result for " + query, false);
    }
    
    static class ExpensiveResult {
        private String value;
        private boolean cached;
        
        public ExpensiveResult(String value, boolean cached) {
            this.value = value;
            this.cached = cached;
        }
        
        public String getValue() { return value; }
        public boolean isCached() { return cached; }
    }
}

Thread-Safe Maps and Concurrent Operations
#

Concurrent Map Implementations
#

import java.util.*;
import java.util.concurrent.*;

public class ConcurrentMapDemo {
    public static void main(String[] args) throws InterruptedException {
        demonstrateConcurrentHashMap();
        demonstrateAtomicOperations();
        demonstrateParallelOperations();
        comparePerformance();
    }
    
    private static void demonstrateConcurrentHashMap() throws InterruptedException {
        System.out.println("=== ConcurrentHashMap Demo ===");
        
        // Problem with regular HashMap in concurrent environment
        Map<String, Integer> unsafeMap = new HashMap<>();
        
        // Safe concurrent map
        ConcurrentMap<String, Integer> safeMap = new ConcurrentHashMap<>();
        
        int threadCount = 10;
        int operationsPerThread = 1000;
        CountDownLatch latch = new CountDownLatch(threadCount);
        
        // Launch threads that modify the maps
        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            new Thread(() -> {
                try {
                    for (int j = 0; j < operationsPerThread; j++) {
                        String key = "key" + (j % 100);
                        
                        // Unsafe operation on HashMap
                        try {
                            unsafeMap.merge(key, 1, Integer::sum);
                        } catch (Exception e) {
                            // May throw ConcurrentModificationException or cause corruption
                        }
                        
                        // Safe operation on ConcurrentHashMap
                        safeMap.merge(key, 1, Integer::sum);
                    }
                } finally {
                    latch.countDown();
                }
            }).start();
        }
        
        latch.await(); // Wait for all threads to complete
        
        System.out.println("Expected total operations: " + (threadCount * operationsPerThread));
        System.out.println("Unsafe map size: " + unsafeMap.size());
        System.out.println("Safe map size: " + safeMap.size());
        
        // Verify safe map integrity
        int totalOperations = safeMap.values().stream().mapToInt(Integer::intValue).sum();
        System.out.println("Safe map total operations: " + totalOperations);
    }
    
    private static void demonstrateAtomicOperations() {
        System.out.println("\n=== Atomic Operations ===");
        
        ConcurrentMap<String, AtomicInteger> counters = new ConcurrentHashMap<>();
        
        // Thread-safe counter increment
        String[] events = {"login", "logout", "purchase", "login", "purchase", "login"};
        
        for (String event : events) {
            // Old way - not atomic
            // counters.putIfAbsent(event, new AtomicInteger(0));
            // counters.get(event).incrementAndGet();
            
            // New way - atomic
            counters.computeIfAbsent(event, k -> new AtomicInteger(0))
                   .incrementAndGet();
        }
        
        System.out.println("Event counters: " + counters);
        
        // Demonstrate putIfAbsent atomicity
        ConcurrentMap<String, String> cache = new ConcurrentHashMap<>();
        
        // Atomic "get or create" pattern
        String result = cache.putIfAbsent("key1", "value1");
        System.out.println("First putIfAbsent result: " + result); // null
        
        result = cache.putIfAbsent("key1", "value2");
        System.out.println("Second putIfAbsent result: " + result); // value1
        System.out.println("Cache contents: " + cache);
        
        // replace operations
        boolean replaced = cache.replace("key1", "value1", "newValue1");
        System.out.println("Replaced: " + replaced);
        System.out.println("After replace: " + cache);
    }
    
    private static void demonstrateParallelOperations() {
        System.out.println("\n=== Parallel Operations ===");
        
        ConcurrentHashMap<String, Integer> map = new ConcurrentHashMap<>();
        
        // Populate map
        for (int i = 1; i <= 1000; i++) {
            map.put("key" + i, i);
        }
        
        // Parallel forEach
        System.out.println("Parallel forEach (sum of values):");
        LongAdder sum = new LongAdder();
        map.forEach(100, (key, value) -> sum.add(value)); // parallelism threshold = 100
        System.out.println("Sum: " + sum.sum());
        
        // Parallel search
        String found = map.search(100, (key, value) -> 
            value > 500 ? key : null);
        System.out.println("First key with value > 500: " + found);
        
        // Parallel reduce
        Integer maxValue = map.reduce(100, 
            (key, value) -> value, // transformer
            Integer::max);         // reducer
        System.out.println("Maximum value: " + maxValue);
        
        // reduceValues
        Integer totalSum = map.reduceValues(100, Integer::sum);
        System.out.println("Total sum (reduceValues): " + totalSum);
        
        // Parallel key operations
        Set<String> longKeys = ConcurrentHashMap.newKeySet();
        map.forEachKey(100, key -> {
            if (key.length() > 4) {
                longKeys.add(key);
            }
        });
        System.out.println("Keys longer than 4 chars: " + longKeys.size());
    }
    
    private static void comparePerformance() throws InterruptedException {
        System.out.println("\n=== Performance Comparison ===");
        
        int threadCount = 8;
        int operationsPerThread = 100000;
        
        // Test ConcurrentHashMap
        Map<Integer, Integer> concurrentMap = new ConcurrentHashMap<>();
        long startTime = System.nanoTime();
        runConcurrentTest(concurrentMap, threadCount, operationsPerThread);
        long concurrentTime = System.nanoTime() - startTime;
        
        // Test synchronized HashMap
        Map<Integer, Integer> syncMap = Collections.synchronizedMap(new HashMap<>());
        startTime = System.nanoTime();
        runConcurrentTest(syncMap, threadCount, operationsPerThread);
        long syncTime = System.nanoTime() - startTime;
        
        // Test Hashtable
        Map<Integer, Integer> hashtable = new Hashtable<>();
        startTime = System.nanoTime();
        runConcurrentTest(hashtable, threadCount, operationsPerThread);
        long hashtableTime = System.nanoTime() - startTime;
        
        System.out.println("Performance results (" + threadCount + " threads, " + 
                          operationsPerThread + " ops/thread):");
        System.out.println("ConcurrentHashMap: " + concurrentTime / 1_000_000 + " ms");
        System.out.println("Synchronized HashMap: " + syncTime / 1_000_000 + " ms");
        System.out.println("Hashtable: " + hashtableTime / 1_000_000 + " ms");
        
        System.out.println("\nPerformance ratios:");
        System.out.println("ConcurrentHashMap vs Synchronized: " + 
                          String.format("%.2fx faster", (double) syncTime / concurrentTime));
        System.out.println("ConcurrentHashMap vs Hashtable: " + 
                          String.format("%.2fx faster", (double) hashtableTime / concurrentTime));
        
        System.out.println("\nConcurrentHashMap advantages:");
        System.out.println("- Lock-free reads in most cases");
        System.out.println("- Segmented locking for writes");
        System.out.println("- Better scalability with multiple threads");
        System.out.println("- Atomic compound operations");
    }
    
    private static void runConcurrentTest(Map<Integer, Integer> map, 
                                        int threadCount, 
                                        int operationsPerThread) throws InterruptedException {
        CountDownLatch latch = new CountDownLatch(threadCount);
        
        for (int i = 0; i < threadCount; i++) {
            new Thread(() -> {
                try {
                    for (int j = 0; j < operationsPerThread; j++) {
                        int key = j % 1000; // Reuse keys to create contention
                        
                        // Mix of operations
                        if (j % 3 == 0) {
                            map.put(key, j);
                        } else if (j % 3 == 1) {
                            map.get(key);
                        } else {
                            map.remove(key);
                        }
                    }
                } finally {
                    latch.countDown();
                }
            }).start();
        }
        
        latch.await();
    }
}

// Weak reference map for memory-sensitive caching
class WeakValueMap<K, V> {
    private final ConcurrentHashMap<K, WeakReference<V>> map = new ConcurrentHashMap<>();
    private final ReferenceQueue<V> queue = new ReferenceQueue<>();
    
    public void put(K key, V value) {
        cleanUp();
        map.put(key, new WeakReference<>(value, queue));
    }
    
    public V get(K key) {
        cleanUp();
        WeakReference<V> ref = map.get(key);
        if (ref != null) {
            V value = ref.get();
            if (value == null) {
                map.remove(key); // Clean up stale reference
            }
            return value;
        }
        return null;
    }
    
    private void cleanUp() {
        Reference<? extends V> ref;
        while ((ref = queue.poll()) != null) {
            // Remove stale entries
            map.values().remove(ref);
        }
    }
    
    public int size() {
        cleanUp();
        return map.size();
    }
}

layout: default
#

Summary and Key Takeaways
#

What We Learned
#

🗺️ Map Interface: Key-value pair storage with unique keys
🔑 HashMap: Hash table implementation with O(1) average performance
⚡ LinkedHashMap: HashMap with insertion/access order preservation
🌳 TreeMap: Red-black tree with sorted key ordering
🎯 ConcurrentHashMap: Thread-safe map with excellent scalability
🔍 Navigation: TreeMap’s NavigableMap methods for range operations
📊 Modern Operations: compute, merge, stream integration
💡 Patterns: Caching, indexing, counting, grouping

Map Implementation Comparison
#

Feature	HashMap	LinkedHashMap	TreeMap	ConcurrentHashMap
Ordering	None	Insertion/Access	Sorted	None
Null Keys	1 allowed	1 allowed	Not allowed	Not allowed
Null Values	Allowed	Allowed	Allowed	Not allowed
Performance	O(1) avg	O(1) avg	O(log n)	O(1) avg
Thread Safe	No	No	No	Yes
Memory	Low	Medium	High	Medium

Key Operations Performance
#

HashMap/LinkedHashMap/ConcurrentHashMap
#

get(): O(1) average, O(n) worst case
put(): O(1) average, O(n) worst case
remove(): O(1) average, O(n) worst case
containsKey(): O(1) average, O(n) worst case

TreeMap
#

get(): O(log n)
put(): O(log n)
remove(): O(log n)
containsKey(): O(log n)

Important Concepts Recap
#

Hash Function: Maps keys to array indices for O(1) access
Collision Resolution: Chaining and tree structure for same-hash keys
Load Factor: Ratio that triggers resize (default 0.75)
Fail-Fast Iterators: Detect concurrent modifications
View Collections: keySet(), values(), entrySet() are live views
Navigation Methods: TreeMap’s floor, ceiling, higher, lower
Atomic Operations: ConcurrentMap’s thread-safe compound operations
Weak References: Memory-sensitive caching patterns

Modern Map Patterns (Java 8+)
#

Compute Operations
#

// Frequency counting
map.merge(key, 1, Integer::sum);

// Caching pattern
map.computeIfAbsent(key, k -> expensiveOperation(k));

// Update if present
map.computeIfPresent(key, (k, v) -> transform(v));

Stream Integration
#

// Transform to new map
Map<K, V2> transformed = originalMap.entrySet()
    .stream()
    .collect(Collectors.toMap(
        Map.Entry::getKey,
        entry -> transform(entry.getValue())
    ));

// Group by criteria
Map<String, List<Person>> byAge = people.stream()
    .collect(Collectors.groupingBy(Person::getAgeGroup));

When to Use Each Map
#

HashMap
#

General-purpose mapping
Fast access required
Order not important
Single-threaded access

LinkedHashMap
#

Need predictable iteration order
LRU cache implementation
Debugging/logging scenarios

TreeMap
#

Need sorted keys
Range queries required
Navigation operations needed
Consistent performance preferred

ConcurrentHashMap
#

Multi-threaded environment
High-performance concurrent access
Atomic compound operations needed

layout: center class: text-center
#

Thank You!
#

Map Collections Complete
#

Lecture 36 Successfully Completed!
You now master Map collections and their practical applications

Ready for Collections Utilities!

Map Collections#

Lecture 36#

layout: default#

Learning Objectives#

layout: default#

Map Interface Fundamentals#

Map Characteristics#

Key-Value Association#

Core Map Operations#

HashMap Implementation#

HashMap Deep Dive#

layout: default#

LinkedHashMap and TreeMap#

LinkedHashMap Implementation#

LinkedHashMap Features#

TreeMap Implementation#

TreeMap Features#

layout: default#

Advanced Map Operations and Patterns#

Map Utility Methods and Patterns#

Modern Map Operations (Java 8+)#

Thread-Safe Maps and Concurrent Operations#

Concurrent Map Implementations#

layout: default#

Summary and Key Takeaways#

What We Learned#

Map Implementation Comparison#

Key Operations Performance#

HashMap/LinkedHashMap/ConcurrentHashMap#

TreeMap#

Important Concepts Recap#

Modern Map Patterns (Java 8+)#

Compute Operations#

Stream Integration#

When to Use Each Map#

HashMap#

LinkedHashMap#

TreeMap#

ConcurrentHashMap#

layout: center class: text-center#

Thank You!#

Map Collections Complete#

Map Collections
#

Lecture 36
#

layout: default
#

Learning Objectives
#

layout: default
#

Map Interface Fundamentals
#

Map Characteristics
#

Key-Value Association
#

Core Map Operations
#

HashMap Implementation
#

HashMap Deep Dive
#

layout: default
#

LinkedHashMap and TreeMap
#

LinkedHashMap Implementation
#

LinkedHashMap Features
#

TreeMap Implementation
#

TreeMap Features
#

layout: default
#

Advanced Map Operations and Patterns
#

Map Utility Methods and Patterns
#

Modern Map Operations (Java 8+)
#

Thread-Safe Maps and Concurrent Operations
#

Concurrent Map Implementations
#

layout: default
#

Summary and Key Takeaways
#

What We Learned
#

Map Implementation Comparison
#

Key Operations Performance
#

HashMap/LinkedHashMap/ConcurrentHashMap
#

TreeMap
#

Important Concepts Recap
#

Modern Map Patterns (Java 8+)
#

Compute Operations
#

Stream Integration
#

When to Use Each Map
#

HashMap
#

LinkedHashMap
#

TreeMap
#

ConcurrentHashMap
#

layout: center class: text-center
#

Thank You!
#

Map Collections Complete
#