created the datebase index optimisation

[KAMALDEEN333]

📌 Overview
As GasGuard analytics and dashboards grow, query performance can degrade, causing slow response times for merchants and developers. Proper indexing improves query efficiency, reduces latency, and ensures a responsive experience.

This task introduces Database Index Optimization to accelerate analytics queries and improve dashboard performance.

🎯 Objective
Build a system that:

Identifies slow queries and performance bottlenecks in analytics and reporting
Implements optimal database indexes on frequently queried tables and columns
Ensures faster response times for dashboards and API analytics endpoints
Maintains data integrity while optimizing performance
🛠 Scope of Work
1️⃣ Query Analysis
Profile database queries used for dashboards and reporting:

Implemented 🗃️ Database Index Optimization

Gas usage aggregation per merchant
Transaction success metrics
Chain reliability and gas volatility metrics
Identify:

Columns frequently used in WHERE, JOIN, and ORDER BY clauses
Tables with large datasets or high read frequency
Opportunities for composite or partial indexes
2️⃣ Index Implementation
Create optimized indexes in the database (PostgreSQL recommended):

Single-column indexes for high-selectivity queries
Composite indexes for multi-column filtering
Partial indexes for subset data (e.g., recent transactions)
Ensure minimal write performance impact

Example SQL:

CREATE INDEX idx_merchant_chain_date
ON transactions (merchant_id, chain_id, created_at);

close #73