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.
Meilisearch uses bucket sort to rank search results. This algorithm distributes documents into buckets based on ranking rules, then recursively sorts within each bucket using subsequent rules.
How bucket sort works in Meilisearch
When you search, Meilisearch doesn’t score documents with a single number. Instead, it applies ranking rules sequentially, sorting documents into buckets at each step.
Example: Searching for “Badman dark knight returns”
Step 1: Apply the words rule
The first ranking rule (words) sorts documents by how many query words they contain:
| Bucket | Matches | Documents |
|---|
| 1 | All 4 words | ”Batman: The Dark Knight Returns” |
| 2 | 3 words | ”Batman: The Dark Knight” |
| 3 | 2 words | … |
| 4 | 1 word | ”Angel and the Badman” |
typo rule within buckets
If a bucket contains multiple documents, the next rule (typo) breaks ties. For example, in the 1-word bucket where “Badman” appears:
| Bucket | Typos | Documents |
|---|
| 4.1 | 0 typos | Documents containing “Badman” exactly |
| 4.2 | 1 typo | Documents corrected “Badman” → “Batman” |
Why bucket sort?
Bucket sort offers several advantages for search ranking:
- Flexibility: Different sorting algorithms can be applied within individual buckets
- Configurable priority: You control which criteria matter most by reordering rules
- Efficient tie-breaking: Only documents that tie on one rule need evaluation by the next
Best and worst cases
| Case | Condition | Complexity |
|---|
| Best | Documents spread evenly across buckets | O(n+k) where n=documents, k=buckets |
| Worst | All documents in one bucket | Depends on the sorting algorithm used |
Default ranking rules
Meilisearch applies these rules in order:
- words: Documents containing more query words rank higher
- typo: Documents with fewer typos rank higher
- proximity: Documents where query words appear closer together rank higher
- attributeRank: Documents matching in more important attributes rank higher
- sort: User-defined sort order (if specified)
- wordPosition: Documents with matches closer to the beginning of an attribute rank higher
- exactness: Documents with exact matches rank higher
Customizing ranking rules
You can reorder, add, or remove ranking rules:
curl -X PUT "${MEILISEARCH_URL}/indexes/movies/settings/ranking-rules" \
-H "Authorization: Bearer ${MEILISEARCH_KEY}" \
-H "Content-Type: application/json" \
--data-binary '[
"words",
"typo",
"proximity",
"attributeRank",
"sort",
"wordPosition",
"exactness",
"release_date:desc"
]'
release_date:desc as a custom rule means newer movies rank higher when all other factors are equal.
