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- Published on
모든 언어와 시스템에 들어있는 기본 자료구조지만 현대 구현의 내부는 잘 알려지지 않은 해시맵. 이 글은 해시맵을 처음부터 해부합니다. 체이닝 vs 개방 주소법, Linear/Quadratic/Double probing, Robin Hood의 분산 감소 전략, Hopscotch와 Cuckoo, Google Swiss Table이 SIMD로 16개 슬롯을 한 번에 비교하는 방법, Facebook F14, Rust hashbrown, Python dict의 perturbation, Java HashMap의 tree 전환, 해시 함수 선택(SipHash vs xxHash vs FNV), hash flooding DDoS, 그리고 벤치마크와 실무 튜닝까지 — 현대 해시맵의 성능 비결을 제대로 이해하고 싶은 엔지니어를 위한 종합 가이드입니다.- Published on
파이썬 `dict`, 자바 `HashMap`, 러스트 `HashMap`, C++ `unordered_map`, Go `map` — 매일 쓰는 이 자료구조들이 왜 전혀 다르게 구현됐는가. 80년대 체이닝부터 2017년 Google Swiss Table까지, 해시 테이블이 30배 빨라진 진화 과정. Java가 8.0에서 Red-Black Tree로 떨어지는 이유, Rust가 왜 느린 SipHash를 기본으로 쓰는지, Robin Hood hashing의 공평함, SIMD로 16개 버킷을 병렬 비교하는 Swiss Table의 마법까지. 매일 쓰는 Map 뒤의 수십 년 엔지니어링.- Published on
면접에 나오는 모든 자료구조를 시각화와 코드로! Array, LinkedList, Stack/Queue, HashMap, BST, AVL, Red-Black Tree, Heap, Trie, Graph, Union-Find, B-Tree/B+Tree, Skip List, Bloom Filter — 시간복잡도 비교표와 실전 활용까지.- Published on
Redis의 모든 것! 5가지 데이터 구조 활용법, 캐싱 패턴(Cache-Aside/Write-Through/Write-Behind), Pub/Sub, Redis Streams, Redis Stack(JSON/Search/TimeSeries), Lua 스크립트, Cluster, 면접 질문까지.