A HashMap (or Object/Map in JavaScript) is a data structure that stores data in key-value pairs. It uses a hash function to compute an index into an array of buckets, from which the desired value can be found.

Think of a HashMap as a massive array of numbered cubbies, but instead of using a number to find your cubby, you use a Name:

1. You want to store your "Blue Shirt" in a cubby named "Outfit".
2. The "Magic Blender" (Hash Function) takes the word "Outfit" and turns it into a number, say 42.
3. You put the "Blue Shirt" in cubby 42.
4. Next time you want your "Outfit", you give the Blender the name "Outfit", it gives you 42 again, and you go straight to the shirt!

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Core Properties

• Key-Value Storage: Every item has a unique identifier (key).
• Complexity: $O(1)$ average time for Put, Get, and Remove.
• Hashing: The process of converting a key into an integer index.
• Collisions: When two different keys produce the same index. Handled via Chaining (linked lists in buckets) or Open Addressing.

Use Cases

• Caching: Storing results of expensive operations.
• Counting: Tracking occurrences of items.
• Indexing: Mapping IDs to full objects for fast access.
• Two Sum: Reducing $O(n^2)$ search to $O(n)$.

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javascript Standard
/**
 * Using the native JavaScript Map object
 */
const userMap = new Map();

// 1. Setting Values
userMap.set('id_101', { name: 'Alice', role: 'Engineer' });
userMap.set('id_102', { name: 'Bob', role: 'Designer' });

// 2. Getting Values (O(1))
const user = userMap.get('id_101');
console.log(user.name); // Alice

// 3. Checking Existence
if (userMap.has('id_101')) {
  console.log("User exists!");
}

// 4. Deleting
userMap.delete('id_102');

// 5. Size
console.log(userMap.size); // 1

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Map vs. Object in JS

• Map: Better for frequent additions/removals, supports any data type as key, maintains insertion order.
• Object: Better for simple records, only supports strings/symbols as keys, slightly more overhead for dynamic hashing.

Common Interview Questions

• Two Sum: Use a map to store target - current and find matches in one pass.
• LRU Cache: A classic high-level design problem using a Map and a Doubly Linked List.
• Isomorphic Strings: Using two maps to check mapping consistency.