Database Query Optimization for Billing Reports

[elizabetheonoja-art]

Problem Statement

Monthly billing report generation takes over 30 seconds for accounts with high usage. Query optimization and caching can reduce this to under 2 seconds.

Technical Bounds

• Analyze slow query logs for billing aggregations
• Implement materialized views for common report patterns
• Add Redis caching for frequently accessed data
• Support incremental report generation

Steps

1. Profile current billing report queries
2. Create materialized views for aggregation
3. Implement query result caching layer
4. Add incremental update mechanism
5. Benchmark before and after optimization

[NuruddeenA97234]

Hello Utility-Protocol team,

I would like to take on this performance optimization issue.

Why me:
I have experience optimizing slow SQL queries and implementing caching layers for reporting systems. I have worked with PostgreSQL materialized views, Redis caching, and incremental ETL jobs to reduce report generation time from minutes to seconds.

My approach to deliver this:

1. Profiling: Analyze slow query logs for the billing aggregation queries. Identify N+1 queries, missing indexes, and heavy GROUP BY operations.

2. Materialized Views: Create materialized views for the most common monthly billing report patterns. Add refresh strategy with CONCURRENTLY to avoid locking.

3. Caching Layer: Implement Redis caching for report results. Key will be accountId plus month plus year with TTL of 24 hours. Invalidate cache on new billing events.

4. Incremental Updates: Build an incremental update mechanism that only recalculates the delta since the last report instead of full aggregation every time.

5. Benchmarking: Measure before and after using the same high usage test account. Target is under 2 seconds. I will include the benchmark results in the PR.

Deliverable: Optimized queries, new materialized views, Redis cache implementation, and documented benchmark showing the 30s to under 2s improvement. ETA 3 days.

This will make the billing experience much faster for users with high usage.

Ready to start.

Thanks
Nuruddeen Abubakar