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One of my projects was using Memcached, a high-performance, distributed memory object caching system to reduce the time accessing db.

Memcached is an in-memory key-value store for small chunks of arbitrary data(strings, objects) from results of database calls, API calls, or page rendering.

Quick Example,

function get_foo(foo_id)
    // try to fetch data from memory first.
    foo = memcached_get("foo:" . foo_id)
    return foo if defined foo
    // fetch from db is not existed in cache
    foo = fetch_foo_from_database(foo_id)
    memcached_set("foo:" . foo_id, foo)
    return foo
Why use a memory Cache?
One use of a memory cache is to speed up common data store queries. If many requests make the same query with the same parameters, and changes to the results do not need to appear on the web site right away, the app can cache the results in the memcached. 

What is it made up of?
1. Client software, which is given a list of available memcached servers.
2. A client-based hashing algorithm, which chooses a server based on the 'key' input.
3. Server software, which stores your values with their keys into an internal hash table.
4. Server algorithms, which determine when to throw out old data(if out of memory), or reuse memory;
What  are the design philosophies? 
1. Simple Key/Value Store. The server does not care what your data looks lie. Items are made up  of a key, an expiration time,optional flags, and raw data. It does not understand data structures; you must upload data that is pre-serialized. Most of time, people store SQL as the key.
2. Smarts half in client, half in the server
A "memcached implementation" is implemented partially in client, and partially in a server. Clients understand how to send items to particular servers, what to do when it cannot contact a server, and how to fetch keys from the servers.
The server understand how to receive items, and how to expire them;
3. Servers are disconnected from each other
4. O(1) everything. 


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