Cleaned up the Memcached cache backend doc

Memcached

---------

By far the fastest, most efficient type of cache available to Django,

Memcached__ is an entirely memory-based cache framework originally developed to

handle high loads at LiveJournal.com and subsequently open-sourced by Danga

Interactive.  It is used by sites such as Facebook and Wikipedia to reduce

database access and dramatically increase site performance.

The fastest, most efficient type of cache supported natively by Django,

Memcached__ is an entirely memory-based cache server, originally developed

to handle high loads at LiveJournal.com and subsequently open-sourced by

Danga Interactive. It is used by sites such as Facebook and Wikipedia to

reduce database access and dramatically increase site performance.

__ http://memcached.org/

Memcached runs as a daemon and is allotted a specified amount of RAM. All it does is

provide a fast interface for adding, retrieving and deleting arbitrary data in

Memcached runs as a daemon and is allotted a specified amount of RAM. All it

does is provide a fast interface for adding, retrieving and deleting data in

the cache. All data is stored directly in memory, so there's no overhead of

database or filesystem usage.

After installing Memcached itself, you'll need to install a memcached

binding. There are several python memcached bindings available; the

After installing Memcached itself, you'll need to install a Memcached

binding. There are several Python Memcached bindings available; the

two most common are `python-memcached`_ and `pylibmc`_.

.. _`python-memcached`: ftp://ftp.tummy.com/pub/python-memcached/

        }

    }

One excellent feature of Memcached is its ability to share cache over multiple

servers. This means you can run Memcached daemons on multiple machines, and the

program will treat the group of machines as a *single* cache, without the need

to duplicate cache values on each machine. To take advantage of this feature,

include all server addresses in :setting:`LOCATION <CACHES-LOCATION>`, either

separated by semicolons or as a list.

One excellent feature of Memcached is its ability to share a cache over

multiple servers. This means you can run Memcached daemons on multiple

machines, and the program will treat the group of machines as a *single*

cache, without the need to duplicate cache values on each machine. To take

advantage of this feature, include all server addresses in

:setting:`LOCATION <CACHES-LOCATION>`, either separated by semicolons or as

a list.

In this example, the cache is shared over Memcached instances running on IP

address 172.19.26.240 and 172.19.26.242, both on port 11211::

        }

    }

A final point about Memcached is that memory-based caching has one

disadvantage: Because the cached data is stored in memory, the data will be

A final point about Memcached is that memory-based caching has a

disadvantage: because the cached data is stored in memory, the data will be

lost if your server crashes. Clearly, memory isn't intended for permanent data

storage, so don't rely on memory-based caching as your only data storage.

Without a doubt, *none* of the Django caching backends should be used for