40% Performance Improvement on 1M+ Records

SQL Query Optimization Suite

Systematic SQL query optimization on large-scale datasets reducing execution time by approximately 40% through indexing, rewrites, and materialized views.

SQLClickHousePythonAWS

View Code

40%

Speed Boost

1M+

Records

2.1s

Final Time

Problem Statement

Critical analytical queries on 1M+ record datasets took 12+ seconds, blocking real-time dashboard performance and analyst productivity.

Architecture

Query profiling pipeline identifying bottlenecks, followed by staged optimization: indexes, query rewrites, and materialized view deployment.

Database

ClickHouse and MySQL with 1M+ analytical records.

Solution

Applied index optimization, query rewrites, and materialized views reducing average query execution from 12.5s to 2.1s.

Key Queries

Query execution plan analysis
Materialized view aggregation queries
Optimized JOIN and subquery rewrites

Dashboards Built

Query performance monitoring dashboard
Before/after execution time comparison
Database load impact tracking

Business Insights

Unlocked real-time dashboard feasibility

Reduced analyst wait time significantly

Lowered cloud compute costs

Challenges

Optimizing without changing business logic
Managing materialized view refresh schedules
Testing performance across query patterns

Future Scope

Automated query optimization suggestions
Query cache layer integration
Cost-based optimization analysis

Features

Query profiling and benchmarkingIndex recommendation engineMaterialized view managementPerformance regression monitoring