Tell me more about the story of optimizing report speed: what did you do, what did you face, what difficulties did you have, how did you solve them?

In one of my Go projects, I worked on optimizing the report generation speed, which initially took too long — sometimes several minutes. The main issues were related to inefficient database operations and unnecessary computations.

What I did:

• Analyzed CPU and memory profiling using pprof to identify bottlenecks.
• Optimized SQL queries, removed redundant JOINs, and selected only necessary fields.
• Implemented caching of intermediate results to avoid recalculating the same data.
• Parallelized data processing using goroutines, considering resource constraints.

Challenges:

• Parallelism led to data races, so I used mutexes and channels for synchronization.
• Memory limitations prevented caching too much data.
• Incorrect indexes in the database slowed down queries, requiring close collaboration with the DBA.

How I solved it:

• Used a profiler to precisely identify bottlenecks.
• Rewrote parts of the logic with more efficient algorithms.
• Introduced batch processing to reduce load.
• Set up monitoring and logging to track performance in real-time.

As a result, the report generation time was reduced from several minutes to a few seconds, significantly improving the system's usability.