GATE CSEIT/Database/Hashing example ( Which clear your all doubt).

GATE CSEIT/Database/Hashing example ( Which clear your all doubt).

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Hashing in Databases – GATE CSE/IT Example with Explanation

What is Hashing in Databases?

Hashing is a technique used in databases to quickly access records using a hash function that maps keys to locations in a hash table. It helps in:
Efficient retrieval of data in O(1) average time complexity.
Reducing search time compared to sequential or binary search.
Handling large datasets effectively.

Example 1: Simple Hashing in Database

Problem Statement:

A database contains student records with unique roll numbers (keys). We use a hash function to store and retrieve records efficiently.

Given Data:

Hash Function:

Let’s use Modulo Hashing where the hash function is:

$$h(Key)=Key\mathrm{mod}10$$

This means the roll number will be stored at an index based on its last digit.

Hash Table After Insertion:

Example Query: Searching for roll number 1099
Step 1: Compute h(1099) = 1099 % 10 = 9
Step 2: Go to index 9 → Found! Charlie is stored here.

Example 2: Collision Handling with Chaining

Problem Statement:

Suppose two students have roll numbers 1023 and 1123. Since

$$1023\mathrm{mod}10=1123\mathrm{mod}10=3$$

both will be assigned to index 3 in the hash table. This causes a collision.

Solution:

Use Chaining (Linked List at each index).

Updated Hash Table (with Chaining for index 3):

 Now, when searching for 1123, we check index 3 and traverse the list to find it.

Key Takeaways for GATE Exam

Direct Addressing is inefficient for large keys, so hashing is used.
Modular Hashing (h(key) = key % table_size) is common in GATE problems.
Collisions are handled using:

• Chaining (Linked List at each index)
• Open Addressing (Linear Probing, Quadratic Probing, Double Hashing)
  Hashing is efficient (O(1) average case) but can degrade to O(n) in worst case (when all keys hash to the same location).

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GATE CSEIT/Database/Hashing example ( Which clear your all doubt).

INFORMATION TECHNOLOGY

Here’s a clear and detailed hashing example tailored for GATE CSE/IT – Database topic to help clear all your doubts about how hashing works, what collisions are, and how collision resolution is done.

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Hashing: Crystal Clear Example

Problem:

Insert the following keys into a hash table of size 10 using:

1. Division method: h(k) = k mod 10

2. Use Linear Probing to handle collisions.

Keys to insert:
23, 43, 13, 27, 33

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Step 1: Apply Hash Function

For each key:
h(k) = k mod 10

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Collision Detection

We see collisions at index 3 for:

• 43 (conflicts with 23)

• 13 (conflicts with 23 and 43)

• 33 (conflicts with 23, 43, 13)

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Collision Resolution Using Linear Probing

Linear Probing:
If slot h(k) is occupied, check h(k) + 1, then h(k) + 2, and so on (mod table size).

Insertion Order:

1. 23 → index 3 (free)

2. 43 → index 3 (occupied) → try 4

3. 13 → index 3 (occupied), 4 (occupied) → try 5

4. 27 → index 7 (free)

5. 33 → index 3 → 4 → 5 → try 6

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Final Hash Table

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Key Concepts You Learned:

• Hash Function: Converts a key to an index.

• Collision: Two keys get same index (e.g., 23, 43, 13, 33 → all map to 3).

• Linear Probing: Find next free slot (sequentially) when a collision occurs.

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Try Yourself

Use the same method for keys:
11, 22, 31, 4, 15, 28, 17
with table size = 10
and h(k) = k mod 10

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Would you like:

• The same example using chaining?

• A quiz to practice?

• A PDF/visual chart of this process?

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GATE CSEIT/Database/Hashing example ( Which clear your all doubt).

UNIT-2 HASHING STATIC HASHING Hash Tables …

DBMS Hashing