FIFO, LIFO, LRU, MRU, LFU - Cache Eviction Policies Explained Simply (System
Your cache is full. Something has to go. But which item do you remove - and does it even matter? The answer can make or break your app's performance.
Your cache is full. Something has to go. But which item do you remove - and does it even matter? The answer can make or break your app’s performance.
What’s in the video (7m 2s)
- 0:00 — Cache Eviction Policies Introduction
- 0:43 — Why we Need to Evict Cached Data?
- 1:29 — Simple Cache Eviction Policies - FIFO & LIFO
- 1:38 — How First In First Out (FIFO) Cache Eviction Policy Works?
- 2:08 — How Last In First Out (LIFO) Cache Eviction Policy Works?
- 2:26 — FIFO vs LIFO
- 2:46 — Recency Based Cache Eviction Policies
- 2:56 — How Least Recently Used (LRU) Cache Eviction Policy Works?
- 3:34 — How Most Recently Used (MRU) Cache Eviction Policy Works?
- 4:12 — Frequency Based Cache Eviction Policies
- 4:23 — How Least Frequently Used (LFU) Cache Eviction Policy Works?
- 4:41 — LRU vs LFU
- 5:07 — Random Replacement Cache Eviction Policy
- 5:36 — Usecases and Tradeoffs of Cache Eviction Policies
Resources
- Full System Design series: YouTube playlist
- Previous episode: https://youtu.be/jFfY9JarT1g
- Next episode: https://youtu.be/xqXiWmN5UX4
For more in this series, visit the #system-design tag page or jump to the channel uploads list for everything else.
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