Operations on Hash Tables

Hash tables are incredibly useful data structures for storing and retrieving information quickly. You can think of them as a specialized phone book where you can instantly find someone’s phone number just by knowing their name. Just like you perform actions with a phone book (adding new contacts, looking up a number, removing an entry), you perform similar operations on hash tables. Let’s explore the three main operations: insertion, search, and deletion.

Insertion: Adding Data to the Table

Insertion is the process of adding a new piece of data, usually a key-value pair, into the hash table. Imagine you have a new contact’s phone number (value) you want to save using their name (key).

Here’s how it generally works:

  1. Get the Key: You start with the unique key associated with the data you want to store (e.g., the name ‘Alice’).
  2. Calculate the Hash: Use the hash function to convert the key (‘Alice’) into a numerical hash code. This function turns the name into a number.
  3. Find the Bucket: Convert the hash code into an index (or “bucket” address) that fits within the size of the hash table’s underlying array. This tells you where to store the data.
  4. Store the Data: Place the key-value pair (e.g., ‘Alice’ -> ‘555-1234’) into the bucket at the calculated index.

Note

What if two different keys (like ‘Alice’ and ‘Bob’) hash to the same index? This is called a collision. Hash tables have specific strategies to handle collisions, like storing multiple items in the same bucket (using a list) or finding the next available empty slot. We’ll explore these strategies in detail later.

Search: Finding Data in the Table

Search, or retrieval, is the process of looking up the value associated with a given key. Suppose you want to find the phone number for ‘Alice’.

The steps are very similar to insertion:

  1. Get the Key: You start with the key you’re looking for (e.g., ‘Alice’).
  2. Calculate the Hash: Use the same hash function as used during insertion to convert the key (‘Alice’) into its hash code.
  3. Find the Bucket: Convert the hash code into the corresponding bucket index.
  4. Look in the Bucket: Go to the calculated bucket index in the array.
  5. Find the Key: Check the items stored in that bucket. If you find an item with the matching key (‘Alice’), return its associated value (‘555-1234’). If the key isn’t found in that bucket (or the bucket is empty), the key doesn’t exist in the hash table.

Tip

The efficiency of the search operation is the main reason hash tables are so powerful. Ideally, calculating the hash and index takes you directly to the correct bucket, making the search very fast, often close to instantaneous on average (represented as O(1) time complexity).

Deletion: Removing Data from the Table

Deletion involves removing a key-value pair from the hash table. Let’s say ‘Alice’ moves away, and you want to remove her contact information.

The process starts like a search:

  1. Get the Key: Identify the key of the item you want to remove (e.g., ‘Alice’).
  2. Calculate the Hash: Use the hash function to get the hash code for the key.
  3. Find the Bucket: Determine the bucket index from the hash code.
  4. Locate the Item: Go to the specific bucket and search for the item with the matching key (‘Alice’).
  5. Remove the Item: If the item with the key is found, remove it from the bucket (e.g., remove the ‘Alice’ -> ‘555-1234’ pair). If it’s not found, you don’t need to do anything.

Warning

Deletion can sometimes be slightly tricky depending on how collisions are handled. For example, in some methods (like open addressing), simply removing an element might disrupt the search path for other elements that collided with the deleted one. Special techniques might be needed, like marking the slot as “deleted” instead of “empty”.

These three operations – Insert, Search, and Delete – form the core functionality of hash tables, enabling efficient data management.

What’s Next?

By now, you must have learnt about the fundamental operations on hash tables. To further deepen your understanding, consider exploring these related topics: