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Cleaned up the Memcached cache backend doc 

Consistent casing, minor typo fixes, reduced rhetoric.
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Tom Dyson 2014-10-13 11:24:36 +01:00 committed by Baptiste Mispelon
parent 8d789449c7
commit 8701b59007
1 changed files with 19 additions and 18 deletions
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docs/topics/cache.txt
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@ -62,21 +62,21 @@ settings file. Here's an explanation of all available values for
Memcached Memcached
--------- ---------
By far the fastest, most efficient type of cache available to Django, The fastest, most efficient type of cache supported natively by Django,
Memcached__ is an entirely memory-based cache framework originally developed to Memcached__ is an entirely memory-based cache server, originally developed
handle high loads at LiveJournal.com and subsequently open-sourced by Danga to handle high loads at LiveJournal.com and subsequently open-sourced by
Interactive. It is used by sites such as Facebook and Wikipedia to reduce Danga Interactive. It is used by sites such as Facebook and Wikipedia to
database access and dramatically increase site performance. reduce database access and dramatically increase site performance.
__ http://memcached.org/ __ http://memcached.org/
Memcached runs as a daemon and is allotted a specified amount of RAM. All it does is Memcached runs as a daemon and is allotted a specified amount of RAM. All it
provide a fast interface for adding, retrieving and deleting arbitrary data in 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 the cache. All data is stored directly in memory, so there's no overhead of
database or filesystem usage. database or filesystem usage.
After installing Memcached itself, you'll need to install a memcached After installing Memcached itself, you'll need to install a Memcached
binding. There are several python memcached bindings available; the binding. There are several Python Memcached bindings available; the
two most common are `python-memcached`_ and `pylibmc`_. two most common are `python-memcached`_ and `pylibmc`_.
.. _`python-memcached`: ftp://ftp.tummy.com/pub/python-memcached/ .. _`python-memcached`: ftp://ftp.tummy.com/pub/python-memcached/
@ -114,12 +114,13 @@ In this example, Memcached is available through a local Unix socket file
} }
} }
One excellent feature of Memcached is its ability to share cache over multiple One excellent feature of Memcached is its ability to share a cache over
servers. This means you can run Memcached daemons on multiple machines, and the multiple servers. This means you can run Memcached daemons on multiple
program will treat the group of machines as a *single* cache, without the need machines, and the program will treat the group of machines as a *single*
to duplicate cache values on each machine. To take advantage of this feature, cache, without the need to duplicate cache values on each machine. To take
include all server addresses in :setting:`LOCATION <CACHES-LOCATION>`, either advantage of this feature, include all server addresses in
separated by semicolons or as a list. :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 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:: address 172.19.26.240 and 172.19.26.242, both on port 11211::
@ -149,8 +150,8 @@ on the IP addresses 172.19.26.240 (port 11211), 172.19.26.242 (port 11212), and
} }
} }
A final point about Memcached is that memory-based caching has one 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 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 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. 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 Without a doubt, *none* of the Django caching backends should be used for