🗂️ Hash Tables Explained Like You're 5
Building AI systems and writing about how they actually work. Master of AI @ University of Technology Sydney. Previously B.Tech CS with focus on IoT. I believe the best way to learn is to explain. That's why I'm documenting tech concepts with simple analogies (@sreekarreddy.com). AWS Certified • Azure AI Certified • Neo4j Professional • Google Data Analytics When not coding: exploring Sydney, working on side projects, and teaching tech to anyone who'll listen.
A library card catalog
Day 37 of 149
👉 Full deep-dive with code examples
The Library Catalog
Old libraries had card catalogs:
Looking for "Harry Potter"?
- H → Drawer for H
- Find "Harry Potter" card
- Card says: Shelf 3, Row 2
Jump directly to the right drawer!
How It Works
A hash function turns keys into locations:
"apple" → hash → 42
"banana" → hash → 17
"cherry" → hash → 8
Now you know where to look.
Why So Fast?
Array: Look through EVERY item = O(n) Hash Table: Jump directly to location = O(1)
Array: Check 1? No. Check 2? No. Check 3? Yes!
Hash Table: Calculate location → Jump there → Found!
The Catch: Collisions
What if two keys hash to the same spot?
"apple" → 42 "pear" → 42 (uh oh!)
Solutions:
- Chain (link multiple items at same spot)
- Probe (look at next spot)
In One Sentence
Hash tables use a function to instantly calculate where data is stored, making lookups super fast.
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