System Design - Cache | Caching | Cache Invalidation | Cache Eviction

Caching:
- Caching works on locality of reference principle: recently requested data is likely to be requested again.
- It's like short-term memory which has limited space but is faster & contains most recently accessed items.
- Cache can be used in almost every layer: hardware, OS, Web browsers, web application, but are often found nearest to the front end.
- Types of cache:
- Application server cache:
- Placing a cache on request layer node enables the local storage of response data. When a request is made, node will quickly return the cached data, if exists. If not it'll query from disk.
- But when you've many nodes with load balancer, it randomely distribute across the nodes, the same request will go to different noodes, thus increasing cache misses
- Two choices are to overcome this: global cache & distribute cache.
- Distribute Cache:
- In it, each of its nodes own part of cached data.
- The cache is divided up using a consitent hashing function, such that if a request node is looking for a certain piece of data, it can quickly know where to look within distributed cache to check if data is available.
- Easily we can increase the cache space just by adding nodes to the request pool
- Global Cache:
- In this, all nodes use the same single cache space. Each of the request nodes queries the cache in the same way it would a local one.
- There can two type of global cache:
- First, when a cached response not found in cache, cache itself becomes responsible for retrieving the missing peice of data.
- Second, it's the responsibility of request nodes to retrieve any data that is not found. It can be used when low cache hit % would cause the cache buffer with cache misses. In this situation, it helps to have a large % of data set in cache.
- CDN
- It's Content Distribution Network for serving large amount of static media which is common to all.
- First request ask the CDN for data, if not cdn will query the back-end servers & then cache it locally
- If your system is not that big for CDN, you can serve static media from a seperate subdomain using a lightweight HTTP server like Nginx
- Cache Invalidation
- When data is modified in DB, it should be invalidated in the cache.
- write-through cache:
- Data is written into the cache & the DB at the same time.
- This allow cached to be fast
- Data consitency also there between cache & DB, which make sure nothing get lost in case of power failure
- This minimizes the risk of data loss, but has disadvantage of higher latency for write operations.
- write-around cache:
- Data is written directly to storage, bypassing the cache.
- This reduces flooded write operations but has disadvantage that a read request for recently written data will create a cache miss & must be read from slower back-end.
- write-back cache:
- Data is written to cache alone & completion is immedialtely confirm to client & write to permanent storage is done after specified intervals.
- This results in low latency & high throughput, however this spped comes with the risk of data loss in case of crash.
- Cache eviction policy
- FIFO
- LIFO
- LRU (Least Recently Used): Implement using Doubly Linked list & a hash function containing the reference of node in list
- Most Recently Used
- Least frequently Used
- Random Replacement

In this video, we're going to reveal Cache used in System Design:
- What is Cache/Caching
- Where it can be added
- Types of Cache
- Cache Invalidation
- Cache Eviction Policies


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