Optimizing Report Generation for an Agriculture Intelligence Website
Optimized an agriculture intelligence platform built in Laravel with PostgreSQL. By introducing secondary data tables and automating their population with CRON jobs, the report generation time was reduced by more than threefold, enhancing performance and user experience.
- Agricultural Data Analysis and Intelligence
- Laravel, PostgreSQL, Cron Jobs, SQL Optimization
- South Africa
The Client
The client is an agriculture intelligence website that provides various reports to its users. The website is built using Laravel and PostgreSQL, catering to agricultural data analysis and intelligence.
The Challenge
The client faced significant performance issues with report generation due to the complexity of the SQL queries involved:
- Most reports required joining 20 to 35 database tables.
- SQL queries ranged from 200 to 500 lines.
- Report generation was taking approximately 10 seconds even on a high-configuration server, leading to a slow user experience and inefficiency.
The Solution
To address these challenges, a comprehensive analysis and optimization strategy was implemented:
- Secondary Data Tables: Introduced secondary data tables for each report category to simplify data retrieval.
- Cron Job Automation: Developed cron jobs to populate these secondary tables periodically, ensuring they are up-to-date with the latest data.
- Simplified Queries: Modified the report generation process to fetch data from the pre-populated secondary tables, significantly reducing the complexity and length of the SQL queries.
Tools and Technology
Laravel
PostgreSQL
Cron Jobs
SQL
The Result
The optimization resulted in significant performance improvements:
- Faster Report Generation: Reduced report generation times by more than threefold, providing a much faster and smoother user experience.
- Efficient Data Retrieval: Simplified data retrieval process by eliminating complex joins and lengthy queries.
- Improved Server Performance: Reduced load on the server by optimizing database operations, allowing better handling of concurrent users.
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