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Documentation Index

Fetch the complete documentation index at: https://www.meilisearch.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

Facet search is a dedicated endpoint for searching through the values of a single facet. It is typically used to power auto-complete and type-ahead interfaces on top of filter menus, especially when a facet has too many distinct values to display at once (for example, thousands of brands or authors). If you are new to facets, start with Search with facets and Build faceted navigation. This page focuses on the /facet-search endpoint itself and the edge cases you need to know about before relying on it.

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Prerequisites

Before you can search a facet’s values, the attribute must be declared in filterableAttributes. Facet search is enabled by default on every index; you can disable it per index with the facetSearch setting if you do not need it and want to speed up indexing.

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Search a facet

Send a POST request to /indexes/{index_uid}/facet-search with the name of the facet you want to search and the partial string typed by the user: 
curl \
  -X POST 'MEILISEARCH_URL/indexes/books/facet-search' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "facetQuery": "c",
    "facetName": "genres"
}'
The response contains a facetHits array with the matching values and the number of documents that carry each one: 
{
  "facetHits": [
    { "value": "Children's Literature", "count": 1 },
    { "value": "Classics", "count": 6 },
    { "value": "Comedy", "count": 2 },
    { "value": "Coming-of-Age", "count": 1 }
  ],
  "facetQuery": "c"
}
You can further scope the results by combining facetQuery with q, filter, and matchingStrategy. See the facet search API reference for the full list of parameters.

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Facet search only works on string fields

Meilisearch does not support facet search on numeric fields. If you need to type-ahead through a numeric facet, convert the values to strings before indexing them (for example, store "rating": "4.5" rather than "rating": 4.5).
Internally, Meilisearch stores numbers as float64. Floating-point values lack exact decimal precision and can be represented in more than one way, which makes prefix matching on their textual form unreliable. Only string facet values are indexed for facet search.

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Facet search only matches the first term of facetQuery

Meilisearch’s facet search is single-term: only the first word in facetQuery is used to match facet values. Subsequent words are ignored.
For example, given a author facet that contains "Jane Austen":
  • facetQuery: "Jane" returns Jane Austen
  • facetQuery: "Austen" does not return Jane Austen, because the word Austen is not the start of the stored value
  • facetQuery: "Jane Aus" effectively behaves like facetQuery: "Jane" (the second word is dropped)
This is a deliberate trade-off that keeps the facet-search index compact and fast. If you need multi-word matching across facet values, perform a regular search with the q parameter instead and inspect the facetDistribution of the response.

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Get exact facet counts

By default, the counts returned by facet search are estimates, which is faster on large indexes. To force exact counts, set exhaustiveFacetCount to true: 
curl \
  -X POST 'MEILISEARCH_URL/indexes/books/facet-search' \
  -H 'Content-Type: application/json' \
  --data-binary '{
    "facetName": "genres",
    "facetQuery": "c",
    "exhaustiveFacetCount": true
  }'
Exact counts are slower to compute. Prefer them when accuracy matters (for example, a storefront’s category counts) and the defaults when latency matters most.

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Next steps

Search with facets

Configure facets and filter search results

Build faceted navigation

Patterns for category and filter menus

Handle large facet cardinality

Strategies for facets with thousands of values

Facet search API reference

Full list of parameters accepted by /facet-search