> ## 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.
# Federated search
> In this tutorial you will see how to perform a query searching multiple indexes at the same time to obtain a single list of results.
Meilisearch allows you to make multiple search requests at the same time with the `/multi-search` endpoint. A federated search is a multi-search that returns results from multiple queries in a single list.
In this tutorial you will see how to create separate indexes containing different types of data from a CRM application. You will then perform a query searching all these indexes at the same time to obtain a single list of results.
## Create three indexes
Download the following datasets: `crm-chats.json`, `crm-profiles.json`, and `crm-tickets.json` containing data from a fictional CRM application.
Add the datasets to Meilisearch and create three separate indexes, `profiles`, `chats`, and `tickets`:
```sh theme={null}
curl -X POST 'MEILISEARCH_URL/indexes/profiles' -H 'Content-Type: application/json' -H 'Authorization: Bearer MEILISEARCH_KEY' --data-binary @crm-profiles.json &&
curl -X POST 'MEILISEARCH_URL/indexes/chats' -H 'Content-Type: application/json' -H 'Authorization: Bearer MEILISEARCH_KEY' --data-binary @crm-chats.json &&
curl -X POST 'MEILISEARCH_URL/indexes/tickets' -H 'Content-Type: application/json' -H 'Authorization: Bearer MEILISEARCH_KEY' --data-binary @crm-tickets.json
```
[Use the tasks endpoint](/capabilities/indexing/tasks_and_batches/monitor_tasks) to check the indexing status. Once Meilisearch successfully indexed all three datasets, you are ready to perform a federated search.
## Perform a federated search
When you are looking for Natasha Nguyen's email address in your CRM application, you may not know whether you will find it in a chat log, among the existing customer profiles, or in a recent support ticket. In this situation, you can use federated search to search across all possible sources and receive a single list of results.
Use the `/multi-search` endpoint with the `federation` parameter to query the three indexes simultaneously:
```bash cURL theme={null}
curl \
-X POST 'MEILISEARCH_URL/multi-search' \
-H 'Content-Type: application/json' \
--data-binary '{
"federation": {},
"queries": [
{
"indexUid": "chats",
"q": "natasha"
},
{
"indexUid": "profiles",
"q": "natasha"
},
{
"indexUid": "tickets",
"q": "natasha"
}
]
}'
```
Meilisearch should respond with a single list of search results:
```json theme={null}
{
"hits": [
{
"id": 0,
"client_name": "Natasha Nguyen",
"message": "My email is natasha.nguyen@example.com",
"time": 1727349362,
"_federation": {
"indexUid": "chats",
"queriesPosition": 0
}
},
…
],
"processingTimeMs": 0,
"limit": 20,
"offset": 0,
"estimatedTotalHits": 3,
"semanticHitCount": 0
}
```
## Promote results from a specific index
Since this is a CRM application, users have profiles with their preferred contact information. If you want to search for Riccardo Rotondo's preferred email, you can boost documents in the `profiles` index.
Use the `weight` property of the `federation` parameter to boost results coming from a specific query:
```bash cURL theme={null}
curl \
-X POST 'MEILISEARCH_URL/multi-search' \
-H 'Content-Type: application/json' \
--data-binary '{
"federation": {},
"queries": [
{
"indexUid": "chats",
"q": "rotondo"
},
{
"indexUid": "profiles",
"q": "rotondo",
"federationOptions": { "weight": 1.2 }
},
{
"indexUid": "tickets",
"q": "rotondo"
}
]
}'
```
This request will lead to results from the query targeting `profile` ranking higher than documents from other queries:
```json theme={null}
{
"hits": [
{
"id": 1,
"name": "Riccardo Rotondo",
"email": "riccardo.rotondo@example.com",
"_federation": {
"indexUid": "profiles",
"queriesPosition": 1
}
},
…
],
"processingTimeMs": 0,
"limit": 20,
"offset": 0,
"estimatedTotalHits": 3,
"semanticHitCount": 0
}
```
## Paginate federated results
By default, federated search returns a limited number of results using `offset` and `limit`. If you need exhaustive pagination, use the `federation.page` and `federation.hitsPerPage` parameters instead. These work like traditional page-based pagination across the merged result set.
Send a federated search request with pagination:
```bash theme={null}
curl \
-X POST 'MEILISEARCH_URL/multi-search' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer MEILISEARCH_KEY' \
--data-binary '{
"federation": {
"page": 2,
"hitsPerPage": 10
},
"queries": [
{ "indexUid": "profiles", "q": "Nguyen" },
{ "indexUid": "chats", "q": "Nguyen" },
{ "indexUid": "tickets", "q": "Nguyen" }
]
}'
```
The response includes `page`, `hitsPerPage`, and `totalPages` instead of `offset`, `limit`, and `estimatedTotalHits`:
```json theme={null}
{
"hits": [ … ],
"processingTimeMs": 1,
"page": 2,
"hitsPerPage": 10,
"totalHits": 25,
"totalPages": 3
}
```
This makes it straightforward to build paginated UIs that display merged results from multiple indexes.
## Conclusion
You have created three indexes, then performed a federated multi-index search to receive all results in a single list. You then used `weight` to boost results from the index most likely to contain the information you wanted, and paginated through merged results using `federation.page` and `federation.hitsPerPage`.
## Next steps
Fine-tune result ranking when combining results from multiple indexes.
Create a single search interface that queries multiple indexes at once.
Learn about multi-search capabilities and when to use them.