[[index-modules-cache]]
== Cache

There are different caching inner modules associated with an index. They
include `filter` and others.

[float]
[[filter]]
=== Filter Cache

The filter cache is responsible for caching the results of filters (used
in the query). The default implementation of a filter cache (and the one
recommended to use in almost all cases) is the `node` filter cache type.

[float]
[[node-filter]]
==== Node Filter Cache

The `node` filter cache may be configured to use either a percentage of
the total memory allocated to the process or an specific amount of
memory. All shards present on a node share a single node cache (thats
why its called `node``). The cache implements an LRU eviction policy:
when a cache becomes full, the least recently used data is evicted to
make way for new data.

The setting that allows one to control the memory size for the filter
cache is `indices.cache.filter.size`, which defaults to `20%`. *Note*,
this is *not* an index level setting but a node level setting (can be
configured in the node configuration).

`indices.cache.filter.size` can accept either a percentage value, like
`30%`, or an exact value, like `512mb`.

[float]
[[index-filter]]
==== Index Filter Cache

A filter cache that exists on the index level (on each node). Generally,
not recommended for use since its memory usage depends on which shards
are allocated on each node and its hard to predict it. The types are:
`resident`, `soft` and `weak`.

All types support the following settings:

[cols="<,<",options="header",]
|=======================================================================
|Setting |Description
|`index.cache.filter.max_size` |The max size (count, not byte size) of
the cache (per search segment in a shard). Defaults to not set (`-1`),
which is usually fine with `soft` cache and proper cacheable filters.

|`index.cache.filter.expire` |A time based setting that expires filters
after a certain time of inactivity. Defaults to `-1`. For example, can
be set to `5m` for a 5 minute expiry.
|=======================================================================

