HashMap Interview Questions and Answers for 2023 Programming

• Hashtable is synchronized, HashMap is not. 
• Null keys and values are acceptable in HashMap but not in Hashtable. 
• HashMap is generally faster than Hashtable due to its lack of synchronization. 
• HashMap is part of the Java Collection Framework, while Hashtable is a legacy class. 

I would recommended HashMap to Hashtable unless someone specifically need the synchronized behavior of Hashtable or are using an older version of Java that does not include Java Collection Framework. 

To synchronize access to a HashMap in Java, I will use the Collections.synchronizedMap method to wrap the HashMap object in a synchronized version of the map. This will ensure that all operations on the map are thread-safe and can be used concurrently from multiple threads without causing data corruption or race conditions. 

Below is an example of how to use Collections.synchronizedMap to synchronize access to a HashMap:

Expect to come across this popular question in Java Hashmap interview questions.  

The load factor of a HashMap is a measure of how full the map is, and it determines how much the map will grow when it reaches capacity. When the number of elements in the map exceeds the current capacity of the map multiplied by the load factor, the map will increase its capacity and rehash all of its elements to new locations in the map. 

A higher load factor means that the map will reach capacity and need to be resized more frequently, which can lead to slower performance. On the other hand, a lower load factor means that the map will have a larger capacity and will need to be resized less frequently, which can lead to faster performance. 

In general, a load factor of 0.75 is a good compromise between the need to keep the map relatively small and the need to avoid frequent resizing operations. However, the optimal load factor will depend on the specific characteristics of your application and the usage patterns of the map. 

We can specify the load factor when creating a HashMap like this: 

The initial capacity of a HashMap is the number of buckets that the map is initially created with. Each bucket is a linked list that stores the key-value pairs that map to that bucket.

A larger initial capacity means that the map will have more buckets, which can reduce the number of collisions (when two keys map to the same bucket) and improve the performance of the map. On the other hand, a smaller initial capacity means that the map will have fewer buckets, which can increase the number of collisions and degrade the performance of the map.

In general, a larger initial capacity will lead to better performance, as long as it is not too large. If the initial capacity is set too high, it can waste memory and increase the time required to rehash the map when it needs to be resized.

No, a HashMap cannot have a negative capacity in Java. Here are the reasons why: 

• The capacity of a HashMap is specified as an integer value, and negative integers are not valid values for the capacity. 
• The HashMap class includes a constructor that takes an initial capacity as an argument, but the capacity is specified as a positive integer. The constructor does not allow negative values for the capacity. 

Here is the signature of the HashMap constructor that takes an initial capacity as an argument: 

As seen, the initialCapacity argument is an int, which cannot be negative. 

Therefore, it is not possible to create a HashMap with a negative capacity in Java. 

A must-know for anyone heading into a Hashmap coding interview, this question is frequently asked in programming interview questions on Hashmap on Java.  

I will use the keySet method to get a Set of the keys in the HashMap, and then use an iterator to iterate over the keys: 

import java.util.HashMap; 
import java.util.Iterator; 
import java.util.Map; 
import java.util.Set; 
public class HashMapIterationExample { 
public static void main(String[] args) { 
    Map<String, Integer> map = new HashMap<>(); 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Get a set of the keys 
    Set<String> keys = map.keySet(); 
    // Use an iterator to iterate over the keys 
    Iterator<String> iterator = keys.iterator(); 
    while (iterator.hasNext()) { 
        String key = iterator.next(); 
        Integer value = map.get(key); 
        System.out.println(key + ": " + value); 
    } 
} 
} 

It's no surprise that this one pops up often in Hashmap tricky interview questions.  

The order of the elements in a HashMap may change during its lifetime in Java, due to the way the map is implemented. 

A HashMap is a data structure that uses a hash function to map keys to values and store them in an array of buckets. The position of a key-value pair in the array is determined by the hash code of the key, which is calculated using the key's value and the map's capacity. 

As a result, the order of the elements in a HashMap is not guaranteed to be consistent over time. If the map is resized or if the keys are rehashed due to changes in the map's capacity or load factor, the order of the elements may change. 

Therefore, if we need to preserve the order of elements in a Map, we should use a different data structure, such as a LinkedHashMap, which maintains the order of elements as they are inserted into the map. 

To clear an entire HashMap in Java, I will use the clear method of the HashMap class. This method removes all of the key-value pairs from the map and resets the size of the map to 0. 

Here is an example of how I will use the clear method to clear a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class ClearHashMapExample { 
public static void main(String[] args) { 
    Map<String, Integer> map = new HashMap<>(); 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Clear the map 
    map.clear(); 
    // The map is now empty 
    System.out.println(map.size()); // prints 0 
} 
} 

Note that the clear method is not thread-safe, so if the HashMap may be modified concurrently by multiple threads, I would synchronize access to the map using the Collections.synchronizedMap method or the synchronized keyword.

To create a thread-safe HashMap in Java, I will use the Collections.synchronizedMap method to wrap the HashMap object in a synchronized version of the map. This will ensure that all operations on the map are thread-safe and can be used concurrently from multiple threads without causing data corruption or race conditions. 

Here is an example of how to use Collections.synchronizedMap to create a thread-safe HashMap: 

import java.util.Collections; 
import java.util.HashMap; 
import java.util.Map; 
public class SynchronizedHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, String> map = new HashMap<>(); 
    // Wrap the map in a synchronized version of the map 
    Map<String, String> synchronizedMap = Collections.synchronizedMap(map); 
    // Now you can use the synchronized map just like a regular map, but all operations will be thread-safe 
    synchronizedMap.put("key", "value"); 
    String value = synchronizedMap.get("key"); 
} 
} 

A HashMap in Java is a data structure that stores key-value pairs and allows us to look up the value associated with a particular key in constant time on average. It is part of java.util package and is part of the Java Collection Framework.

A HashMap works by using a hash function to map the keys to indices in an array and then storing the key-value pairs in the array using the calculated indices. This allows the HashMap to efficiently store and retrieve data without having to search through all of the key-value pairs to find the one we are looking for.

A common question in Hashmap coding interview questions, don't miss this one.  

Here is how it works: 

• When you add a new key-value pair to a HashMap, the HashMap uses a special function called a "hash function" to calculate a number (called a "hash code") based on the value of the key. The HashMap then uses this hash code to determine which "bucket" in the HashMap the key-value pair should be stored in. 
• When we look up a value using a key, the HashMap uses the same hash function to calculate the hash code for the key, and then it looks in the corresponding bucket to see if the key-value pair is there. If it is, the HashMap returns the value; if it isn't, the HashMap returns null.
• This process is very fast because HashMap can find the bucket for a key using the hash code without having to look through every single key-value pair in the HashMap. It is like finding a book in a library by looking up the call number instead of searching through every single shelf. 

One of the most frequently posed Hashmap interview questions, be ready for it.  

A HashMap in Java is implemented using an array of linked lists. The HashMap class includes an array called a table that stores the key-value pairs in the map. Each element of the array is a linked list that stores the key-value pairs that map to that element.

When we add a new key-value pair to the HashMap, the HashMap calculates the hash code of the key and uses it to determine the index of the element in the table array that the key-value pair should be stored in. The HashMap then adds the key-value pair to the linked list at that index. 

When we look up a value using a key, the HashMap calculates the hash code of the key and uses it to determine the index of the element in the table array that the key-value pair should be stored in. The HashMap then searches the linked list at that index for the key-value pair and returns the value if it is found or null if it is not found.

This data structure allows HashMap to store and retrieve data very efficiently because it can find the bucket for a key using the hash code without having to search through every single key-value pair in the map. 

A staple in Java Hashmap interview questions, be prepared to answer this one.  

Java's HashMap is a class that implements the Map interface and is used to store key-value pairs, while ArrayList is a class that implements the List interface and is used to store a collection of items in a specific order.

When you need to store key-value pairs, you would use a HashMap. The key is used to quickly locate the corresponding value in the map, making lookups efficient. 

When you need to store a collection of items, and you don't need to maintain any specific order of the items, you would use an ArrayList. ArrayList has fast iteration and random access, but it does not provide a way to access elements by key.

Here is an example of how you can use a HashMap in Java:

In this example, we create a HashMap called map and add three key-value pairs to it. We then use the get method to look up the value for the key "apple" and print it to the screen. 

A HashMap is a very fast and efficient way to store and retrieve data, and it is used in many different kinds of computer programs. 

To populate a HashMap in Java, I will use the put method to add key-value pairs to the map. Here's an example of how I will do this: 

import java.util.HashMap; 
import java.util.Map; 
public class PopulateHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Populate the map by adding some key-value pairs 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // The map now contains the following key-value pairs: 
    //   A -> 1 
    //   B -> 2 
    //   C -> 3 
} 
} 

To retrieve an element from a HashMap in Java, I will use the get method and pass in the key for the element I want to retrieve as an argument. The get method will return the value associated with the key, or null if the key is not found in the HashMap. 

Here's an example of how to use the get method to retrieve an element from a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class GetElementFromHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Retrieve an element from the map using the get method 
    int value = map.get("B"); // value will be 2 
} 
} 

This question is a regular feature in Hashmap programming interview questions, be ready to tackle it.  

To update an element in a HashMap in Java, I will use the put method and pass in the key of the element I want to update and the new value as arguments. The put method will replace the existing value for the key with the new value. 

Here's an example of how I will use the put method to update an element in a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class UpdateElementInHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Update an element in the map using the put method 
    map.put("B", 4); // the value for "B" is now 4 
    // The map now contains the following key-value pairs: 
    //   A -> 1 
    //   B -> 4 
    //   C -> 3 
} 
} 

To remove an element from a HashMap in Java, I will use the remove method and pass in the key of the element I want to remove as an argument. The remove method will return the value associated with the key, or null if the key is not found in the HashMap. 

Here's an example of how I will use the remove method to remove an element from a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class RemoveElementFromHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Remove an element from the map using the remove method 
    int value = map.remove("B"); // value is 2 
    // The map now contains the following key-value pairs: 
    //   A -> 1 
    //   C -> 3 
} 
} 

To check if a key or value exists in a HashMap in Java, I can use the containsKey and containsValue methods, respectively. 

• The containsKey method takes a key as an argument and returns true if the key is found in the HashMap, or false if it is not found.  
• The containsValue method takes a value as an argument and returns true if the value is found in the HashMap, or false if it is not found. 

Here's an example of how I will use the containsKey and containsValue methods to check if a key or value exists in a HashMap:

This is a frequently asked question in Hashmap coding interview questions.  

To get the size of a HashMap in Java, I will use the size method. This method returns the number of key-value pairs in the HashMap. 

Here's an example of how I will use the size method to get the size of a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class GetSizeOfHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Get the size of the map 
    int size = map.size(); // size is 3 
} 
} 

I can use the isEmpty method to check if the HashMap is empty. This method returns true if the HashMap is empty, or false if it is not empty. 

Here's an example of how I will use the isEmpty method to check if a HashMap is empty: 

import java.util.HashMap; 
import java.util.Map; 
public class GetSizeOfHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Check if the map is empty 
    boolean isEmpty = map.isEmpty(); // isEmpty is true 
    // Add a key-value pair to the map 
    map.put("A", 1); 
    // Check if the map is empty again 
    isEmpty = map.isEmpty(); // isEmpty is false 
} 
} 

Expect to come across this popular question in Hashmap interview coding questions.  

To clear a HashMap in Java, I will use the clear method. This method removes all key-value pairs from the HashMap, leaving it empty. 

Here's an example of how I will use the clear method to clear a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
public class ClearHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Clear the map 
    map.clear(); 
    // The map is now empty 
} 
}  

One way is to use the entrySet method to get a Set of Map.Entry objects, and then use an iterator to iterate over the set. 

Here's an example of how I will use the entrySet method and an iterator to iterate over the elements of a HashMap: 

import java.util.HashMap; 
import java.util.Map; 
import java.util.Set; 
public class IterateOverElementsOfHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("A", 1); 
    map.put("B", 2); 
    map.put("C", 3); 
    // Get the set of Map.Entry objects 
    Set<Map.Entry<String, Integer>> set = map.entrySet(); 
    // Iterate over the set using an iterator 
    for (Map.Entry<String, Integer> entry : set) { 
        String key = entry.getKey(); 
        Integer value = entry.getValue(); 
        System.out.println(key + " -> " + value); 
    } 
} 
} 

This will print the following output:

Yes, a HashMap in Java can have multiple keys with the same value.

A HashMap is a data structure that maps keys to values, and each key can have exactly one associated value. However, multiple keys can have the same value.

Yes, a HashMap in Java can have null keys and null values.

A HashMap is a data structure that maps keys to values, and both the keys and the values can be null. However, you can only have one null key in a HashMap, because multiple keys with the same value are not allowed.

A must-know for anyone heading into a Hashmap interview, this question is frequently asked in Java Hashmap interview questions.  

The time complexity of the basic operations of a HashMap in Java depends on the size of the map and the distribution of the keys. 

The put operation has an average time complexity of O(1), which means that it takes constant time on average to add a new key-value pair to the HashMap. However, in the worst case, the time complexity can be as high as O(n), where n is the number of key-value pairs in the HashMap.

The get operation has an average time complexity of O(1), which means that it takes constant time on average to retrieve the value for a given key from the HashMap. However, in the worst case, the time complexity can be as high as O(n). 

The remove operation has an average time complexity of O(1), which means that it takes constant time on average to remove a key-value pair from the HashMap. However, in the worst case, the time complexity can be as high as O(n).

Overall, the HashMap is a very efficient data structure for storing and retrieving data, with an average time complexity of O(1) for the basic operations. However, it is important to note that the performance of the HashMap can degrade in the worst case if the keys are poorly distributed, which can cause the time complexity to increase to O(n).

When a HashMap in Java reaches its maximum capacity, it will need to rehash its keys and values to a new backing array with a larger capacity. This process is called resizing. 

The maximum capacity of a HashMap is determined by its load factor, which is a value between 0.0 and 1.0 that determines when the HashMap should be resized. The default load factor for a HashMap is 0.75, which means that the HashMap will be resized when it reaches 75% capacity. 

When the HashMap is resized, it will create a new backing array with a larger capacity and rehash all of its keys and values to the new array. This process can take some time, depending on the size of the HashMap, but it is necessary to ensure that HashMap remains efficient as it grows. 

It's no surprise that this one pops up often in Hashmap interview questions.  

Yes, a HashMap in Java can be sorted. However, the HashMap itself is not a sorted data structure, so I will need to use a different approach to sort it. 

One way to sort a HashMap is to first convert it to a TreeMap, which is a sorted map data structure. I can do this by using the putAll method to add the key-value pairs from the HashMap to a new TreeMap. 

Here's an example of how to sort a HashMap by converting it to a TreeMap: 

import java.util.HashMap; 
import java.util.Map; 
import java.util.TreeMap; 
public class SortHashMapExample { 
public static void main(String[] args) { 
    // Create a new HashMap 
    Map<String, Integer> map = new HashMap<>(); 
    // Add some key-value pairs to the map 
    map.put("B", 2); 
    map.put("A", 1); 
    map.put("D", 4); 
    map.put("C", 3); 
    // Convert the HashMap to a TreeMap 
    Map<String, Integer> sortedMap = new TreeMap<>(map); 
    // The sortedMap is now sorted by key in ascending order: 
    //   A -> 1 
    //   B -> 2 
    //   C -> 3 
    //   D -> 4 
} 
} 

HashMaps are used in many real-world applications to store and retrieve data efficiently. Some examples of how HashMaps are used in real-world applications include: 

• Caching: HashMaps can be used to store frequently accessed data in memory, so that it can be retrieved quickly without having to go to a slower storage medium like a database or a file. 
• Indexing: HashMaps can be used to create an index for a large data set, allowing you to look up specific data quickly without having to search through the entire data set. 
• Mapping: HashMaps can be used to create a mapping between two sets of data, such as a mapping between IDs and names, or between names and addresses. 
• In-memory Data Storage: HashMaps can be used to store data in memory, allowing you to manipulate and process the data quickly. 
• Data Grouping: HashMaps can be used to group data by a specific key, making it easy to perform operations on the data based on the key. 

Yes, a HashMap in Java can have multiple keys with the same value. There is no special implementation required to allow this, as a HashMap is designed to allow multiple keys to map to the same value.

To implement this, I  can simply add multiple key-value pairs to the HashMap where the value is the same. For example:

In this example, we create a new HashMap and add four key-value pairs to it, where the value is the same for all four pairs. 

The time complexity of the basic operations (put, get, remove) in a HashMap is dependent on the hash function used to hash the keys and the distribution of the keys in the backing array of the HashMap. In the best case, the time complexity is O(1), but in the worst case, it can be as high as O(n). However, the average time complexity is O(1), making HashMap an efficient data structure for storing and retrieving data. 

To use a custom key class with a HashMap in Java, I need to ensure that the key class overrides the hashCode and equals methods. The hashCode method is used to generate a hash code for the key, which is used to determine the bucket in the backing array of the HashMap where the key-value pair will be stored. The equals method is used to determine if two keys are equal, which is important when looking up values in the HashMap or when determining if a key is already present in the map. 

Here is an example of a custom key class that can be used with a HashMap: 

public class Person { 
private String firstName; 
private String lastName; 
public Person(String firstName, String lastName) { 
    this.firstName = firstName; 
    this.lastName = lastName; 
} 
@Override 
public int hashCode() { 
    // Use the hash codes of the firstName and lastName fields to generate 
    // a hash code for the Person object 
    return Objects.hash(firstName, lastName); 
} 
@Override 
public boolean equals(Object o) { 
    // Check if the object is an instance of Person 
    if (!(o instanceof Person)) { 
        return false; 
    } 
    // Cast the object to a Person 
    Person p = (Person) o; 
  // Compare the firstName and lastName fields of the two Person objects 
    return p.firstName.equals(firstName) && p.lastName.equals(lastName); 
} 
} 

One of the most frequently posed Java Hashmap interview questions, be ready for it.  

Both HashMap and LinkedHashMap are implementations of the Map interface in Java, and they both allow us to store key-value pairs and retrieve values based on their keys. However, there are a few differences between the two:

HashMap stores its elements in a hash table, which allows it to achieve a constant time complexity of O(1) for the basic operations (put, get, remove). LinkedHashMap, on the other hand, stores its elements in a doubly-linked list in addition to a hash table, which allows it to maintain the insertion order of the elements. 

HashMap does not guarantee the order of its elements, while LinkedHashMap maintains the insertion order of the elements. This means that if I iterate over the elements of a HashMap, the order of the elements may not be the same as the order in which they were added to the map. In a LinkedHashMap, the elements are returned in the order in which they were added to the map.

LinkedHashMap has a slightly higher memory overhead compared to HashMap, as it stores the elements in both a hash table and a linked list.

A collision in a HashMap occurs when two or more keys have the same hash code and are mapped to the same bucket in the backing array of the HashMap. When a collision occurs, the HashMap needs to handle the collision in a way that allows it to efficiently store and retrieve the key-value pairs that are involved in the collision.

Open addressing is a collision handling strategy where the HashMap tries to find an empty bucket in the backing array to store the key-value pair. If an empty bucket is not found, the HashMap uses a probing sequence to determine the next bucket to search for an empty slot. There are several probing sequences that can be used, including linear probing and quadratic probing. The time complexity of the basic operations (put, get, remove) in a HashMap using open addressing is O(1) in the average case, and O(n) in the worst case.

TreeMap is a map data structure that uses a red-black tree to store its elements. It provides guaranteed log(n) time complexity for the basic operations (put, get, remove). However, it does not allow null keys or values, and it requires the keys to be comparable.

LinkedHashMap is a map data structure that maintains the insertion order of its elements in a doubly-linked list in addition to a hash table. It provides constant time complexity for the basic operations (put, get, remove). However, it has a slightly higher memory overhead compared to a HashMap.

To create a thread-safe HashMap in Java, I will use the Collections.synchronizedMap method. This method returns a thread-safe map backed by the specified map. Here is an example: 

Map<String, Integer> map = Collections.synchronizedMap(new HashMap<>()); 

I can also use ConcurrentHashMap class, which is a thread-safe implementation of the Map interface. It uses fine-grained locks and does not require external synchronization. 

This question is a regular feature in Hashmap interview questions, be ready to tackle it.  

An LRU (Least Recently Used) cache can be implemented in Java using a HashMap and a doubly-linked list.

Here is an example of how I will implement an LRU cache in Java using a HashMap and a doubly-linked list: 

import java.util.HashMap; 
public class LRUCache<K, V> { 
    private final int capacity; 
    private HashMap<K, Node> map; 
    private Node head; 
    private Node tail; 
    public LRUCache(int capacity) { 
        this.capacity = capacity; 
        this.map = new HashMap<>(capacity); 
        this.head = new Node(); 
        this.tail = new Node(); 
        head.next = tail; 
        tail.prev = head; 
    }
    public V get(K key) { 
        if (!map.containsKey(key)) { 
            return null; 
        } 
        Node node = map.get(key); 
        moveToHead(node); 
        return node.value; 
    } 
    public void put(K key, V value) { 
        if (map.containsKey(key)) { 
            Node node = map.get(key); 
            node.value = value; 
            moveToHead(node); 
        } else { 
            Node node = new Node(key, value); 
            map.put(key, node); 
            addToHead(node); 
            if (map.size() > capacity) { 
                Node removed = removeTail(); 
                map.remove(removed.key); 
            } 
        } 
    } 
    private void moveToHead(Node node) { 
        removeNode(node); 
        addToHead(node); 
    } 
    private void addToHead(Node node) { 
        node.next = head.next; 
        node.prev = head; 
        head.next.prev = node; 
        head.next = node; 
    } 
    private void removeNode(Node node) { 
        node.prev.next = node.next; 
        node.next.prev = node.prev; 
    } 
    private Node removeTail() { 
        Node removed = tail.prev; 
        removeNode(removed); 
        return removed; 
    } 
    private class Node { 
        K key; 
        V value; 
        Node prev; 
        Node next;
        public Node(K key, V value) { 
            this.key = key; 
            this.value = value; 
        } 
        public Node() { 
            this(null, null); 
        } 
    } 
} 

The cache has a fixed capacity and it uses a HashMap to store the key-value pairs, with the key being the key of the pair and the value being the Node object, which contains the value and also links to the previous and next element in the doubly-linked list. 

The doubly-linked list is used to keep track of the order of elements in the cache, with the head node representing the most recently used element, and the tail node representing the least recently used element.

This is a frequently asked question in Hashmap interview questions.  

To create a HashMap with a custom comparator in Java, I will use the TreeMap class, which is an implementation of the Map interface that uses a red-black tree to store the keys. I can specify a custom comparator when creating a TreeMap to control the order in which the keys are stored and retrieved. 

Here is an example of creating a TreeMap with a custom comparator that compares User objects based on their username field: 

Comparator<User> comparator = new Comparator<User>() { 
@Override 
public int compare(User u1, User u2) { 
    return u1.getUsername().compareTo(u2.getUsername()); 
} 
}; 
Map<User, Integer> map = new TreeMap<>(comparator); 

The order of the elements in a HashMap can change during its lifetime in Java due to the way the map is implemented. A HashMap is a hash table-based implementation of the Map interface. It uses a hash function to map keys to indices in an internal array, and stores the key-value pairs in the corresponding array cells. When multiple keys hash to the same index, they are stored in a linked list at that index.

The order of the elements in a HashMap is not guaranteed to be stable over time. In particular, the order of the elements may change as the map is modified, such as when new key-value pairs are added or existing pairs are removed. The order may also change if the map is resized, which can occur if the number of key-value pairs in the map exceeds the capacity of the internal array.

If we need to maintain the insertion order of the elements in a map, we can use the LinkedHashMap class, which is a subclass of HashMap that maintains a doubly-linked list running through all of its entries. This linked list defines the iteration order, which is the order in which elements were inserted into the map.

import java.util.HashMap; 
import java.util.Map;
public class WordCounter { 
public static Map<String, Integer> countWords(String text) { 
    // Normalize the text by converting it to lowercase and removing 
    // punctuation and whitespace. 
    text = text.toLowerCase().replaceAll("[^a-z]", "");
    // Split the text into words. 
    String[] words = text.split("\\s+"); 
    // Count the occurrences of each word. 
    Map<String, Integer> wordCounts = new HashMap<>(); 
    for (String word : words) { 
        if (wordCounts.containsKey(word)) { 
            wordCounts.put(word, wordCounts.get(word) + 1); 
        } else { 
            wordCounts.put(word, 1); 
        } 
    } 
    return wordCounts; 
} 
} 

HashMaps in Java outperform TreeMaps and LinkedHashMaps in terms of performance for the vast majority of operations, especially when dealing with huge maps.

Typical HashMap operations, including get and put, have an average-case time complexity of O(1) since they are implemented using a hash table. As a result, these procedures take roughly the same amount of time on average regardless of the size of the map. If the hash function assigns every key to the same index or if the map needs to be enlarged, the worst-case time complexity is O(n).

Alternatively, a TreeMap uses a red-black tree, which provides O(log n) time complexity for most operations. The time required for such processes grows logarithmically with the map's size.

A LinkedHashMap is a hash table that uses a linked list as its internal data structure to preserve the order in which keys and values were added. The temporal complexity is O(1) for most operations, which is comparable to that of a HashMap.

Therefore, a HashMap is typically the best option if fast access to the map's contents is required and the order of the elements is irrelevant. A LinkedHashMap is useful if you need to keep the elements in the order they were added. Using a TreeMap is a good option if you need to keep the items in some kind of order. It's important to remember that the performance of various map implementations can differ based on the operations you need to execute and the properties of the keys and values stored in the map.

To convert a HashMap to a List or Set in Java, you can use the entrySet method of the Map interface, which returns a Set view of the map that contains all of the key-value pairs in the map. I can then create a new List or Set and add the elements of the Set view to it. 

Here is an example of converting a HashMap to a List of keys: 

Map<String, Integer> map = new HashMap<>(); 
map.put("a", 1); 
map.put("b", 2); 
map.put("c", 3); 
List<String> keys = new ArrayList<>(); 
keys.addAll(map.keySet()); 

A must-know for anyone heading into a Hashmap interview, this question is frequently asked in Java Hashmap interview questions.  

To merge two HashMap objects in Java, you can use the putAll() method. This method is defined in the Map interface, which HashMap implements, and it allows you to add all of the key-value pairs from one map to another. 

Here is an example of how I can use the putAll() method to merge two HashMap objects: 

import java.util.HashMap; 
public class Main { 
  public static void main(String[] args) { 
HashMap<String, Integer> map1 = new HashMap<>(); 
map1.put("A", 1); 
map1.put("B", 2); 
map1.put("C", 3); 
HashMap<String, Integer> map2 = new HashMap<>(); 
map2.put("D", 4); 
map2.put("E", 5); 
map2.put("F", 6); 
// merge map2 into map1 
map1.putAll(map2); 
// print out map1 
for (String key : map1.keySet()) { 
  System.out.println(key + ": " + map1.get(key)); 
} 
  } 
} 

This code will output the following: 

It is not possible to create a HashMap object with a fixed size in Java. The HashMap class is implemented as a dynamic data structure that automatically resizes itself when the number of elements it contains exceeds its capacity.

If I want to create a map-like data structure with a fixed size, I can use the java.util.LinkedHashMap class instead. This class is a variant of HashMap that maintains a linked list of the entries in the map, in the order in which they were inserted. I can use the LinkedHashMap constructor that takes a maximum capacity as an argument to create a map with a fixed size.

To create a HashMap object in Java that automatically removes expired entries, we can use the java.util.concurrent.ConcurrentHashMap class and the java.util.concurrent.TimeUnit class. 

The ConcurrentHashMap class is a thread-safe variant of HashMap that provides atomic operations for adding, removing, and updating elements. It also has a method called putIfAbsent() that allows us to add a key-value pair to the map only if the key is not already present.

The TimeUnit class is a utility class that defines a set of time units (such as seconds, minutes, and hours) and provides methods for converting between them. It has a method called toNanos() that converts a time value from a given time unit to nanoseconds.

Here is an example of how we can use the ConcurrentHashMap and TimeUnit classes to create a map that automatically removes expired entries:

It's no surprise that this one pops up often in Hashmap coding interview questions.  

For example, the input array {1, 2, 3, 1, 2, 3, 4} should produce the following output:

import java.util.HashMap; 
public class Main { 
  public static int[] removeDuplicates(int[] array) { 
HashMap<Integer, Boolean> seen = new HashMap<>(); 
int[] result = new int[array.length]; 
int count = 0; 
for (int element : array) { 
  if (!seen.containsKey(element)) { 
    result[count] = element; 
    count++; 
    seen.put(element, true); 
  } 
} 
return result; 
  } 
  public static void main(String[] args) { 
int[] array = {1, 2, 3, 1, 2, 3, 4}; 
int[] result = removeDuplicates(array); 
for (int element : result) { 
  System.out.print(element + " ");  // prints 1 2 3 4 
} 
  } 
} 

To create a HashMap object with weak keys in Java, I will use the java.util.WeakHashMap class. This class is a variant of HashMap that uses weak references for its keys.

A WeakHashMap is a type of hash map in the Java collections framework that is similar to a regular HashMap, but with an important difference: the keys in a WeakHashMap are held weakly. This means that the keys are eligible for garbage collection as soon as there are no other strong references to them. Once the key is garbage collected, its corresponding value will be automatically removed from the WeakHashMap.

The main use case for a WeakHashMap is to implement a cache. For example, if I have a large data set that I need to cache, but I don't want the cache to consume too much memory, I will use a WeakHashMap. Because the keys in the WeakHashMap are held weakly, they will be automatically removed as soon as they are no longer being used, which helps to keep the memory usage of the cache under control.

A weak reference is a special kind of reference that does not prevent an object from being garbage collected. When an object is only weakly reachable, it can be garbage collected at any time, even if the WeakHashMap object is still in use. This means that if the only reference to an object is stored in a WeakHashMap, the object may be automatically removed from the map by the garbage collector when the object is no longer needed.

import java.util.WeakHashMap; 
public class Main { 
  public static void main(String[] args) { 
WeakHashMap<String, Integer> map = new WeakHashMap<>(); 
String key = new String("Hello"); 
map.put(key, 1); 
key = null;  // the only reference to the key object is now stored in the map 
System.gc();  // run the garbage collector 
System.out.println(map.containsKey("Hello"));  // prints "false" 
  } 
} 

To create a HashMap object with soft values in Java, you can use the java.util.SoftReference class and the java.util.HashMap class. 

A soft reference is a special kind of reference that does not prevent an object from being garbage collected when the Java heap is running low on memory. When an object is only softly reachable, it can be garbage collected at any time if the garbage collector determines that it is necessary to free up memory. 

Here is an example of how you can use the SoftReference class and the HashMap class to create a map with soft values: 

import java.lang.ref.SoftReference; 
import java.util.HashMap; 
public class Main { 
  public static void main(String[] args) { 
HashMap<String, SoftReference<Object>> map = new HashMap<>(); 
Object value = new Object(); 
map.put("A", new SoftReference<>(value)); 
value = null;  // the only reference to the value object is now stored in the map 
System.gc();  // run the garbage collector 
System.out.println(map.containsKey("A"));  // prints "true" 
System.out.println(map.get("A").get());  // may print "null" 
  } 
} 

A common question in Hashmap programming interview questions, don't miss this one.  

For example, the input string "abcabcbb" should produce the following output: 3 

One way to solve this problem is to use a HashMap to track the last occurrence of each character in the input string, and a sliding window to keep track of the current substring. Here is an example of how this could be done: 

import java.util.HashMap; 
public class Main { 
  public static int longestSubstring(String s) { 
int maxLength = 0; 
HashMap<Character, Integer> map = new HashMap<>(); 
int start = 0; 
for (int i = 0; i < s.length(); i++) { 
  char c = s.charAt(i); 
  if (map.containsKey(c)) { 
    start = Math.max(start, map.get(c) + 1); 
  } 
  maxLength = Math.max(maxLength, i - start + 1); 
  map.put(c, i); 
} 
return maxLength; 
  } 
  public static void main(String[] args) { 
String s = "abcabcbb"; 
int length = longestSubstring(s); 
System.out.println(length);  // prints 3 
  } 
} 

To implement a distributed HashMap in Java, I will use a distributed hash table (DHT) data structure. A distributed hash table is a distributed data structure that allows us to store key-value pairs on a group of nodes in a way that is efficient and easy to scale.

There are several ways to implement a distributed hash table in Java. One popular way is to use the java.util.concurrent.ConcurrentHashMap class as the underlying data structure and use a consistent hashing algorithm to map keys to nodes. 

Below is an example of how I will implement a distributed HashMap using a ConcurrentHashMap and consistent hashing: 

import java.util.concurrent.ConcurrentHashMap; 
public class DistributedHashMap { 
  private final int numNodes; 
  private final ConcurrentHashMap<Integer, ConcurrentHashMap<String, Object>> data; 
  public DistributedHashMap(int numNodes) { 
this.numNodes = numNodes; 
this.data = new ConcurrentHashMap<>(); 
  } 
  public void put(String key, Object value) { 
int node = hash(key); 
data.putIfAbsent(node, new ConcurrentHashMap<>()); 
data.get(node).put(key, value); 
  } 
  public Object get(String key) { 
int node = hash(key); 
ConcurrentHashMap<String, Object> nodeData = data.get(node); 
if (nodeData == null) { 
  return null; 
} 
return nodeData.get(key); 
  } 
  private int hash(String key) { 
// use a consistent hashing algorithm to map the key to a node 
  } 
} 

There are a few ways to implement a HashMap with persistence in Java, depending on my specific use case and requirements. One way to do this is by serializing the HashMap and storing it to disk. This can be done using the Serializable interface, which is built into Java. 

Here is an example of how I can implement a persistent HashMap using serialization:  

import java.io.*; 
import java.util.HashMap; 
public class PersistentHashMap { 
    private HashMap<String, String> map; 
    private final String fileName; 
    public PersistentHashMap(String fileName) { 
        this.fileName = fileName; 
        map = new HashMap<>(); 
        readFromFile(); 
    } 
    public void put(String key, String value) { 
        map.put(key, value); 
        writeToFile(); 
    } 
    public String get(String key) { 
        return map.get(key); 
    } 
    private void writeToFile() { 
        try { 
            FileOutputStream fos = new FileOutputStream(fileName); 
            ObjectOutputStream oos = new ObjectOutputStream(fos); 
            oos.writeObject(map); 
            oos.close(); 
            fos.close(); 
        } catch (IOException e) { 
            e.printStackTrace(); 
        } 
    } 
    @SuppressWarnings("unchecked") 
    private void readFromFile() { 
        try { 
            FileInputStream fis = new FileInputStream(fileName); 
            ObjectInputStream ois = new ObjectInputStream(fis); 
            map = (HashMap<String, String>) ois.readObject(); 
            ois.close(); 
            fis.close(); 
        } catch (IOException | ClassNotFoundException e) { 
            e.printStackTrace(); 
        } 
    } 
} 

This is a simple example, you can use different techniques like Database or File System to persist it on disk. But keep in mind that reading and writing large HashMaps to disk can be slow and can consume a lot of resources, so I may want to consider other solutions if my use case requires a high performance. 

To implement a HashMap with transactions in Java, we can use the java.util.concurrent.ConcurrentHashMap class and the java.util.concurrent.locks.ReentrantLock class.

The ConcurrentHashMap class is a thread-safe variant of HashMap that provides atomic operations for adding, removing, and updating elements. The ReentrantLock class is a type of lock that can be used to synchronize access to shared resources in a multi-threaded environment.

I can use these classes to implement a HashMap with transactions by creating a ReentrantLock for each key in the map and acquiring the lock whenever I want to update the value for a key. This will ensure that only one thread can update the value for a key at a time, and that the update is atomic. 

A staple in Hashmap interview coding questions, be prepared to answer this one.  

Lazy loading is a technique in software development where a component or feature is only loaded or initialized when it is needed rather than at the start of the application. This can help to improve performance and reduce the memory footprint of the application because resources are only allocated when they are actually needed. 

To implement a HashMap with lazy loading in Java, I can use the java.util.concurrent.ConcurrentHashMap class and a java.util.function.Supplier functional interface.

I can use these classes to implement a HashMap with lazy loading by creating a Supplier for each key in the map and using it to generate the value for the key on demand. This will allow me to delay the computation of the value until it is actually needed, improving the performance of the map when the values are expensive to compute. 

Here is an example of how I can implement a HashMap with lazy loading using a ConcurrentHashMap and Supplier objects: 

import java.util.concurrent.ConcurrentHashMap; 
import java.util.function.Supplier; 
public class LazyLoadingHashMap { 
  private final ConcurrentHashMap<String, Supplier<Object>> data; 
  public LazyLoadingHashMap() { 
this.data = new ConcurrentHashMap<>(); 
  } 
  public void put(String key, Supplier<Object> valueSupplier) { 
data.put(key, valueSupplier); 
  } 
  public Object get(String key) { 
Supplier<Object> valueSupplier = data.get(key); 
if (valueSupplier == null) { 
  return null; 
} 
return valueSupplier.get(); 
  } 
} 

To implement a HashMap with cache eviction in Java, I will use the java.util.LinkedHashMap class.

The LinkedHashMap class is a subclass of HashMap that maintains a doubly-linked list running through all of its entries. This allows me to iterate over the entries in the map in the order in which they were last accessed, from least-recently accessed to most-recently accessed.

I can use this property of LinkedHashMap to implement a cache with eviction by setting the maximum size of the cache and overriding the removeEldestEntry() method to remove the least-recently accessed entry when the size of the cache exceeds the maximum.

For example, the input array {1, 2, 3, 1, 2, 3, 3} should produce the following output: 3 

import java.util.HashMap; 
public class Main { 
  public static int mostFrequent(int[] nums) { 
HashMap<Integer, Integer> count = new HashMap<>(); 
for (int num : nums) { 
  count.put(num, count.getOrDefault(num, 0) + 1); 
} 
int maxCount = 0; 
int mostFrequent = 0; 
for (int num : count.keySet()) { 
  if (count.get(num) > maxCount) { 
    maxCount = count.get(num); 
    mostFrequent = num; 
  } 
} 
return mostFrequent; 
  } 
} 

The time complexity of this method is O(n), where n is the size of the input array. 

This question is a regular feature in interview questions on Hashmap, be ready to tackle it.  

For example, the input string "abcdabcd" should produce the following output: "abcd" 

HashSet is used when you only need to store unique elements and don't need to associate any values with them, while HashMap is used when you need to store key-value pairs and retrieve values based on their corresponding keys. However, both HashMap and HashSet use the concept of hashtables internally to implement their functionality. 

import java.util.HashSet; 
public class Main { 
  public static String uniqueCharacters(String s) { 
HashSet<Character> seen = new HashSet<>(); 
StringBuilder sb = new StringBuilder(); 
for (char c : s.toCharArray()) { 
  if (!seen.contains(c)) { 
    sb.append(c); 
    seen.add(c); 
  } 
} 
return sb.toString(); 
  } 
} 

This function uses a HashSet to store the characters that have already been seen and a StringBuilder to build up the result string. It iterates through the characters in the input string, adding each character to the result string if it has not been seen before and adding it to the HashSet so that it will not be added again. 

For example, the input array {1, 2, 3, 4, 5} and target 5 should produce the following output: 2 

import java.util.HashMap; 
public class Main { 
  public static int countPairs(int[] nums, int target) { 
HashMap<Integer, Integer> count = new HashMap<>(); 
for (int num : nums) { 
  count.put(num, count.getOrDefault(num, 0) + 1); 
} 
int pairs = 0; 
for (int num : count.keySet()) { 
  if (count.containsKey(target - num)) { 
    pairs += count.get(num) * count.get(target - num); 
  } 
} 
return pairs; 
  } 
} 

This function uses a HashMap to count the frequency of each number in the input array, and then iterates through the keys in the map to find pairs of numbers that add up to the target. It increments the pairs counter by the product of the frequencies of each pair of numbers, and returns the pairs count as the result. 

For example, when called with the input array {1, 2, 3, 4, 5} and target 5, the function will create a HashMap with the following entries: 

{ 
  1: 1, 
  2: 1, 
  3: 1, 
  4: 1, 
  5: 1 
}  

It will then iterate through the keys in the map and find that the pairs (1, 4) and (2, 3) add up to the target 5, so it will increment the pairs counter by 1 * 1 + 1 * 1 = 2 and return 2 as the result.

This is a frequently asked question in Hashmap interview questions.  

For example, the input list ["race", "car", "level", "hello", "world", "madam"] should produce the following output:

import java.util.ArrayList; 
import java.util.HashMap; 
import java.util.List; 
public class Main { 
  public static List<List<String>> palindromePairs(List<String> words) { 
HashMap<String, String> reversed = new HashMap<>(); 
for (String word : words) { 
  StringBuilder sb = new StringBuilder(word); 
  reversed.put(sb.reverse().toString(), word); 
} 
List<List<String>> pairs = new ArrayList<>(); 
for (String word : words) { 
  if (reversed.containsKey(word) && !word.equals(reversed.get(word))) { 
    List<String> pair = new ArrayList<>(); 
    pair.add(word); 
    pair.add(reversed.get(word)); 
    pairs.add(pair); 
  } 
} 
return pairs; 
  } 
} 

The time complexity of this method is O(n*k), where n is the size of the input list of words and k is the average length of the words in the input list.

The space complexity of this method is O(n*k) as well, where n is the size of the input list of words, and k is the average length of the words in the input list. The main source of space consumption is the HashMap which is used to store the reversed version of each word as the key and the original word as the value. The size of this map will be O(nk) because in the worst case where each word is unique and different with each other, all the words are stored in the map. Additionally, a list pairs is used to store all the palindrome pairs, which will also take O(n) space.

This code iterates through the list of words and uses the put() and getOrDefault() methods of the HashMap object to count the frequency of each word. The put() method adds the word to the map or updates its count if it already exists. 

To implement a HashMap with a custom entry class in Java, we can define a class that represents an entry in the map, and then use this class as the type of the key-value pairs in the HashMap. 

Here is an example of how I will implement a HashMap with a custom entry class in Java: 

To implement a HashMap with a custom key and value generator in Java, I can define a class that generates the keys and values for the map, and use this class to create the HashMap object and populate it with elements. 

Here is an example of how I will implement a HashMap with a custom key and value generator in Java: 

import java.util.HashMap; 
import java.util.Random; 
public class Main { 
  static class KeyGenerator { 
private Random random = new Random(); 
public int generateKey() { 
  return random.nextInt(); 
} 
  } 
  static class ValueGenerator { 
private Random random = new Random(); 
public String generateValue() { 
  return Long.toHexString(random.nextLong()); 
} 
  } 
  public static void main(String[] args) { 
KeyGenerator keyGenerator = new KeyGenerator(); 
ValueGenerator valueGenerator = new ValueGenerator(); 
HashMap<Integer, String> map = new HashMap<>(); 
for (int i = 0; i < 10; i++) { 
  int key = keyGenerator.generateKey(); 
  String value = valueGenerator.generateValue(); 
  map.put(key, value); 
} 
System.out.println(map); 
  } 
} 

Expect to come across this popular question in Hashmap interview questions for experienced.  

To implement a HashMap with a custom key and value serializer in Java, I can define a class that knows how to serialize and deserialize the keys and values for the map and use this class to create the HashMap object and populate it with elements. 

Here is an example of how I may implement a HashMap with a custom key and value serializer in Java: 

import java.io.ByteArrayInputStream; 
import java.io.ByteArrayOutputStream; 
import java.io.IOException; 
import java.io.ObjectInputStream; 
import java.io.ObjectOutputStream; 
import java.util.HashMap; 
public class Main { 
  static class KeySerializer { 
public byte[] serialize(int key) throws IOException { 
  try (ByteArrayOutputStream baos = new ByteArrayOutputStream(); 
       ObjectOutputStream oos = new ObjectOutputStream(baos)) { 
    oos.writeInt(key); 
    return baos.toByteArray(); 
  } 
}
public int deserialize(byte[] data) throws IOException, ClassNotFoundException { 
  try (ByteArrayInputStream bais = new ByteArrayInputStream(data); 
       ObjectInputStream ois = new ObjectInputStream(bais)) { 
    return ois.readInt(); 
  } 
} 
  } 
  static class ValueSerializer { 
public byte[] serialize(String value) throws IOException { 
  try (ByteArrayOutputStream baos = new ByteArrayOutputStream(); 
       ObjectOutputStream oos = new ObjectOutputStream(baos)) { 
    oos.writeUTF(value); 
    return baos.toByteArray(); 
  } 
} 
  } 
  public static void main(String[] args) throws IOException, ClassNotFoundException { 
KeySerializer keySerializer = new KeySerializer(); 
ValueSerializer valueSerializer = new ValueSerializer(); 
HashMap<byte[], byte[]> map = new HashMap<>(); 
map.put(keySerializer.serialize(1), valueSerializer.serialize("a")); 
map.put(keySerializer.serialize(2), valueSerializer.serialize("b")); 
map.put(keySerializer.serialize(3), valueSerializer.serialize("c")); 
} 
} 

public String deserialize(byte[] data) throws IOException, ClassNotFoundException { 
  try (ByteArrayInputStream bais = new ByteArrayInputStream(data); 
       ObjectInputStream ois = new ObjectInputStream(bais)) { 
    return ois.readUTF(); 
  } 
} 
public static void main(String[] args) throws IOException, ClassNotFoundException { 
KeySerializer keySerializer = new KeySerializer(); 
ValueSerializer valueSerializer = new ValueSerializer(); 
HashMap<byte[], byte[]> map = new HashMap<>(); 
map.put(keySerializer.serialize(1), valueSerializer.serialize("a")); 
map.put(keySerializer.serialize(2), valueSerializer.serialize("b")); 
map.put(keySerializer.serialize(3), valueSerializer.serialize("c")); 
System.out.println(keySerializer.deserialize(map.get(keySerializer.serialize(1))));  // prints "a" 
System.out.println(keySerializer.deserialize(map.get(keySerializer.serialize(2))));  // prints "b" 
} 

To implement a HashMap with a custom key and value factory in Java, I can define a class that knows how to create the keys and values for the map, and use this class to create the HashMap object and populate it with elements. 

Here is an example of how you might implement a HashMap with a custom key and value factory in Java: 

import java.util.HashMap; 
import java.util.function.Function; 
public class Main { 
  static class KeyFactory implements Function<Integer, String> { 
@Override 
public String apply(Integer key) { 
  return Integer.toHexString(key); 
} 
  } 
  static class ValueFactory implements Function<String, Integer> { 
@Override 
public Integer apply(String value) { 
  return value.length(); 
} 
  } 
  public static void main(String[] args) { 
KeyFactory keyFactory = new KeyFactory(); 
ValueFactory valueFactory = new ValueFactory(); 
HashMap<String, Integer> map = new HashMap<>(); 
map.computeIfAbsent(keyFactory.apply(1), valueFactory); 
map.computeIfAbsent(keyFactory.apply(2), valueFactory); 
map.computeIfAbsent(keyFactory.apply(3), valueFactory); 
System.out.println(map.get(keyFactory.apply(1)));  // prints 1 
System.out.println(map.get(keyFactory.apply(2)));  // prints 1 
System.out.println(map.get(keyFactory.apply(3)));  // prints 1 
  } 
} 

To implement a HashMap with a custom key and value transformer in Java, you can define a class that knows how to transform the keys and values for the map and use this class to create the HashMap object and populate it with elements. 

Here is an example of how I will implement a HashMap with a custom key and value transformer in Java: 

import java.util.HashMap; 
import java.util.function.Function; 
 public class Main { 
  static class KeyTransformer implements Function<Integer, String> { 
@Override 
public String apply(Integer key) { 
  return Integer.toHexString(key); 
} 
  } 
  static class ValueTransformer implements Function<String, Integer> { 
@Override 
public Integer apply(String value) { 
  return value.length(); 
} 
  }  
  public static void main(String[] args) { 
KeyTransformer keyTransformer = new KeyTransformer(); 
ValueTransformer valueTransformer = new ValueTransformer(); 
HashMap<Integer, String> map = new HashMap<>(); 
map.put(1, "a"); 
map.put(2, "b"); 
map.put(3, "c"); 
map.replaceAll((key, value) -> keyTransformer.apply(key), valueTransformer); 
System.out.println(map.get(1));  // prints 1 
System.out.println(map.get(2));  // prints 1 
System.out.println(map.get(3));  // prints 1 
  } 
} 

In this example, the KeyTransformer class implements a Function that takes an Integer key and returns a String key, and the ValueTransformer class implements a Function that takes a String value and returns an Integer value. 

The main() method creates instances of the KeyTransformer and ValueTransformer classes and uses them to transform the keys and values of the HashMap using the replaceAll() method. The final state of the HashMap is then printed to the console. 

A must-know for anyone heading into a Hashmap interview, this question is frequently asked in Java Hashmap interview questions.  

To implement a HashMap with a custom key and value filter in Java, I will define a class that knows how to filter the keys and values for the map and use this class to create the HashMap object and populate it with elements. 

Here is an example of how I will implement a HashMap with a custom key and value filter in Java: 

import java.util.HashMap; 
import java.util.function.Predicate; 
public class Main { 
  static class KeyFilter implements Predicate<Integer> { 
@Override 
public boolean test(Integer key) { 
  return key % 2 == 0; 
} 
  } 
  static class ValueFilter implements Predicate<String> { 
@Override 
public boolean test(String value) { 
  return value.length() % 2 == 0; 
} 
  } 
  public static void main(String[] args) { 
KeyFilter keyFilter = new KeyFilter(); 
ValueFilter valueFilter = new ValueFilter(); 
HashMap<Integer, String> map = new HashMap<>(); 
map.put(1, "a"); 
map.put(2, "bb"); 
map.put(3, "ccc"); 
map.entrySet().removeIf(entry -> !keyFilter.test(entry.getKey()) || !valueFilter.test(entry.getValue())); 
System.out.println(map);  // prints {2=bb} 
  } 
} 

There are several ways to handle concurrency issues in a HashMap in a high-concurrency environment in Java: 

• Use the ConcurrentHashMap class instead of the HashMap class. ConcurrentHashMap is a thread-safe implementation of Map that provides better performance in high-concurrency environments compared to HashMap. 
• Use a synchronized block or method to synchronize access to the HashMap. This will prevent multiple threads from modifying the map at the same time, but can lead to reduced performance due to the overhead of synchronization. 
• Use the Collections.synchronizedMap() method to create a synchronized wrapper around a HashMap. This will also prevent multiple threads from modifying the map at the same time, but can also lead to reduced performance due to the overhead of synchronization. 

To compare the performance of different map implementations (e.g. HashMap, TreeMap, LinkedHashMap) in Java, I will use a microbenchmarking library such as JMH (Java Microbenchmark Harness) to measure the time it takes for each map implementation to perform a set of operations.

To design a scalable and maintainable HashMap implementation in Java, I will consider the following best practices: 

• A good hash function to distribute the keys evenly across the map and reduce the likelihood of hash collisions. A good hash function should be fast, uniform, and produce different outputs for different inputs. 
• A dynamic resizing mechanism to adjust the size of the map as the number of elements in the map grows or shrinks. This can help to improve the performance of the map by keeping the number of elements per bucket within a reasonable range. 
• Linked list or tree structure to store the elements in each bucket, rather than using an array. This will allow the map to handle a larger number of elements without incurring a significant performance penalty.