How HashMap Works Internally in Java — Every Operation Explained

You use HashMap a hundred times a day. But can you explain — in detail — what happens on a single map.put? In this episode we crack open java.util.HashMap and trace every operation: → The internal structure — an array of Node buckets → How put(key, value) computes the index with (n − 1) & hash → Why bit-AND is faster than hash % n (and how Java enables the trick) → Collisions and chaining — when two keys land in the same bucket → How get() walks the chain and matches via equals() → How remove() unlinks a Node from the linked list → Resizing — the moment HashMap doubles capacity and rehashes everything → Treeify — the Java 8 optimization that drops worst-case from O(n) to O(log n) → Three production traps that bite engineers: mutable keys, the hashCode/equals contract, and thread-safety ⏱ Chapters 00:06 The question most engineers can't answer 00:24 What HashMap actually is 00:38 The library-shelves analogy 00:58 Internal structure — array of buckets 01:15 The Node — hash, key, value, next 01:32 put() in 4 steps 01:57 Worked example — six inserts at capacity 16 02:21 Collisions = chaining 02:39 Why (n − 1) & hash, not hash % n 03:02 get() — the 4-move lookup 03:20 Trace: looking up "C" 03:39 remove() — unlinking from the chain 03:53 Resize trigger (loadFactor 0.75) 04:13 Capacity 4 → 8 rehash trace 04:36 The amortized O(1) story 04:54 The complexity headline 05:14 Java 8 treeify — chain to red-black tree 05:37 Three production traps 06:05 Three interview questions you can now answer 06:26 Recap 06:47 What should we crack open next? 📚 Playlist: Java Internals — Cracking Open the JDK 🔗 codebrainery.com — the tech blog Subscribe @codebrainery for more Java internals — line by line, no hand-waving. #Java #HashMap #JVM #DataStructures #SoftwareEngineering #Codebrainery