I Love Big-O but It Misleads Me
summary
Explains why Big-O complexity (e.g., N log N for sorting) can be misleading for real performance work. Uses concrete examples where asymptotic analysis fails or leads astray, argues for paying attention to hidden constant factors, hardware effects (CPU instruction sets, SSD latency), and for measuring real latencies repeatedly instead of relying solely on algorithmic complexity.
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chapters (8)
- 0:00Introduction
- 1:50Big O limitations
- 8:31Hidden constants impact
- 16:35Memory access orders
- 24:43N+1 query problem
- 37:22Pragmatic solutions
- 40:12Performance measurement
- 42:25Conclusion
