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91 lines
3.5 KiB
ReStructuredText
91 lines
3.5 KiB
ReStructuredText
.. _limits:
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Limits
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------
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Redis
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.....
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By default, Redis will not evict persistent cache keys (those with a ``None``
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timeout) when the maximum memory has been reached. The cache keys created
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by django-cachalot are persistent, so if Redis runs out of memory,
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django-cachalot and all other ``cache.set`` will raise
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``ResponseError: OOM command not allowed when used memory > 'maxmemory'.``
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because Redis is not allowed to delete persistent keys.
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To avoid this, 2 solutions:
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- If you only store disposable data in Redis, you can change
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``maxmemory-policy`` to ``allkeys-lru`` in your Redis configuration.
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Be aware that this setting is global; all your Redis databases will use it.
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**If you don’t know what you’re doing, use the next solution or use
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another cache backend.**
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- Increase ``maxmemory`` in your Redis configuration.
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You can start by setting it to a high value (for example half of your RAM)
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then decrease it by looking at the Redis database maximum size using
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``redis-cli info memory``.
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For more information, read
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`Using Redis as a LRU cache <http://redis.io/topics/lru-cache>`_.
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Memcached
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.........
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By default, memcached is configured for small servers.
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The maximum amount of memory used by memcached is 64 MB,
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and the maximum memory per cache key is 1 MB. This latter limit can lead to
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weird unhandled exceptions such as
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``Error: error 37 from memcached_set: SUCCESS``
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if you execute queries returning more than 1 MB of data.
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To increase these limits, set the ``-I`` and ``-m`` arguments when starting
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memcached. If you use Ubuntu and installed the package, you can modify
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`/etc/memcached.conf`, add ``-I 10`` on a newline to set the limit
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per cache key to 10 MB, and if you want increase the already existing ``-m 64``
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to something like ``-m 1000`` to set the maximum cache size to 1 GB.
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Locmem
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......
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Locmem is a just a ``dict`` stored in a single Python process.
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It’s not shared between processes, so don’t use locmem with django-cachalot
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in a multi-processes project, if you use RQ or Celery for instance.
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MySQL
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.....
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This database software already provides by default something like
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django-cachalot:
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`MySQL query cache <http://dev.mysql.com/doc/refman/5.7/en/query-cache.html>`_.
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Django-cachalot will slow down your queries if that query cache is enabled.
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If it’s not enabled, django-cachalot will make queries much faster.
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But you should probably better enable the query cache instead.
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.. _Raw queries limits:
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Raw SQL queries
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...............
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.. note::
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Don’t worry if you don’t understand what follow. That probably means you
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don’t use raw queries, and therefore are not directly concerned by
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those potential issues.
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By default, django-cachalot tries to invalidate its cache after a raw query.
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It detects if the raw query contains ``UPDATE``, ``INSERT`` or ``DELETE``,
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and then invalidates the tables contained in that query by comparing
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with models registered by Django.
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This is quite robust, so if a query is not invalidated automatically
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by this system, please :ref:`send a bug report <reporting>`.
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In the meantime, you can use :ref:`the API <API>` to manually invalidate
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the tables where data has changed.
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However, this simple system can be too efficient in some cases and lead to
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unwanted extra invalidations.
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In such cases, you may want to partially disable this behaviour by
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:ref:`dynamically overriding settings <Dynamic overriding>` to set
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:ref:`CACHALOT_INVALIDATE_RAW` to ``False``.
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After that, use :ref:`the API <API>` to manually invalidate the tables
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you modified.
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