Kotlin High-Performance Programming
summary
Kotlin performance hinges on memory access: avoid unnecessary object copies and short-lived instances. The talk compares patterns (returning Pair vs out-arg), shows collection chains allocate per step (use Sequence for large streams or inline loops for small ones), warns that varargs cause array copies, and recommends using Android Profiler and microbenchmarks to measure before optimizing while encapsulating changes to keep code maintainable.
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chapters (15)
- 0:00Introduction
- 2:50Is Kotlin slow?
- 7:46Bulk data processing prereqs
- 9:53Memory latency impact
- 13:08Disposable instances cost
- 15:53Data classes vs tuples internals
- 19:54Optimizing collection ops
- 23:48Varargs spread operator costs
- 26:49Hidden costs summary
- 27:53Algorithm selection pitfalls
- 31:52Precision vs computation cost
- 33:17Eliminating waste vs readability
- 34:43Readability and maintainability
- 36:08Measure improve repeat
- 36:52Summary
