> ## Documentation Index
> Fetch the complete documentation index at: https://docs.blnkfinance.com/llms.txt
> Use this file to discover all available pages before exploring further.
# JOINs
> Learn how to retrieve related data across collections in a single search query
Available in version 0.11.3 and later.
## Overview
JOINs let you pull related data from other collections into the collection you are querying.
Let's say you want to fetch a list of balances, but also want to see the identity info linked to the balances; with JOIN, you can do that in one request.
Blnk links collections through `_id` fields. For example, a balance uses `identity_id` to point to the matching `identity_id` in the identities collection.
***
## Retrieving related data
Use `include_fields` to tell the Search API which related collection to return as part of your results. The format is:
* `$collection_name(*)` to include all fields
* `$collection_name(field1,field2,field3)` to include specific fields.
For example, when you search for balances, you can fetch the identity linked to each balance:
```json Show all fields theme={"system"}
{
"q": "*",
"include_fields": "$identities(*)"
}'
```
```json Show specific fields theme={"system"}
{
"q": "*",
"include_fields": "$identities(first_name,last_name,email)"
}'
```
The response will include an `identities` object populated with the identity details of the balance.
```json Response (all fields) {15-36} expandable theme={"system"}
{
"facet_counts": [],
"found": 144,
"hits": [
{
"document": {
"balance": "9848100",
"balance_id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"created_at": 1763661598,
"credit_balance": "9848100",
"currency": "GBP",
"currency_multiplier": 0,
"debit_balance": "0",
"id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"identities": {
"category": "",
"city": "",
"country": "Mexico",
"created_at": 1763661592,
"dob": 1763661592,
"email_address": "graciela.rosas@example.com",
"first_name": "Graciela",
"gender": "",
"id": "idt_8cc22560-5ace-4989-8953-fcbad7947d48",
"identity_id": "idt_8cc22560-5ace-4989-8953-fcbad7947d48",
"identity_type": "",
"last_name": "Rosas",
"meta_data": {},
"nationality": "",
"organization_name": "",
"other_names": "",
"phone_number": "",
"post_code": "",
"state": "Guanajuato",
"street": "3936 Prolongación Norte Coronado"
},
"identity_id": "idt_8cc22560-5ace-4989-8953-fcbad7947d48",
"indicator": "",
"inflight_balance": "0",
"inflight_credit_balance": "0",
"inflight_debit_balance": "0",
"inflight_expires_at": 1763661598,
"ledger_id": "ldg_ad728e47-b730-4356-b1a7-703f42d33f87",
"meta_data": { },
"precision": 0,
"version": 2
},
"highlight": {},
"highlights": []
}
]
}
```
```json Response (specific fields) {15-19} expandable theme={"system"}
{
"facet_counts": [],
"found": 144,
"hits": [
{
"document": {
"balance": "9848100",
"balance_id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"created_at": 1763661598,
"credit_balance": "9848100",
"currency": "GBP",
"currency_multiplier": 0,
"debit_balance": "0",
"id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"identities": {
"email_address": "graciela.rosas@example.com",
"first_name": "Graciela",
"last_name": "Rosas"
},
"identity_id": "idt_8cc22560-5ace-4989-8953-fcbad7947d48",
"indicator": "",
"inflight_balance": "0",
"inflight_credit_balance": "0",
"inflight_debit_balance": "0",
"inflight_expires_at": 1763661598,
"ledger_id": "ldg_ad728e47-b730-4356-b1a7-703f42d33f87",
"meta_data": { },
"precision": 0,
"version": 2
},
"highlight": {},
"highlights": []
}
]
}
```
You can include multiple related collections in your results, e.g., `$ledgers(*), $identities(first_name,last_name,email)`.
***
## Filter by related data
You can filter a collection using related data from another collection. For example, let's say you want to only view identities that have a USD balance:
* First, you'll search for all identities – `/search/identities`.
* Then add a "balance" filter to only include identities linked to a USD balance.
* Finally, you can specify what balance fields you want to include in the results.
```json Request theme={"system"}
{
"q": "*",
"filter_by": "$balances(currency:=USD)",
"include_fields": "$balances(balance_id,currency,balance,credit_balance,debit_balance)"
}
```
```json Response {7-13, 40-46} expandable theme={"system"}
{
"facet_counts": [],
"found": 48,
"hits": [
{
"document": {
"balances": {
"balance": "16712100",
"balance_id": "bln_f933c83c-dc40-4a48-b063-45039173c218",
"credit_balance": "61033900",
"currency": "USD",
"debit_balance": "44321800"
},
"category": "",
"city": "",
"country": "United Kingdom",
"created_at": 1763661596,
"dob": 1763661596,
"email_address": "debra.barrett@example.com",
"first_name": "Debra",
"gender": "",
"id": "idt_651d448d-772d-4ae3-a878-836d39600e4a",
"identity_id": "idt_651d448d-772d-4ae3-a878-836d39600e4a",
"identity_type": "",
"last_name": "Barrett",
"meta_data": {},
"nationality": "",
"organization_name": "",
"other_names": "",
"phone_number": "",
"post_code": "",
"state": "West Midlands",
"street": "7028 Victoria Road"
},
"highlight": {},
"highlights": []
},
{
"document": {
"balances": {
"balance": "984000",
"balance_id": "bln_c7d7c125-2d9b-438f-b99a-1ee7a7ff4000",
"credit_balance": "44825600",
"currency": "USD",
"debit_balance": "43841600"
},
"category": "",
"city": "",
"country": "Ireland",
"created_at": 1763661596,
"dob": 1763661596,
"email_address": "darrell.payne@example.com",
"first_name": "Darrell",
"gender": "",
"id": "idt_8752147a-f97b-4d32-842e-92d360774fcf",
"identity_id": "idt_8752147a-f97b-4d32-842e-92d360774fcf",
"identity_type": "",
"last_name": "Payne",
"meta_data": {},
"nationality": "",
"organization_name": "",
"other_names": "",
"phone_number": "",
"post_code": "",
"state": "Mayo",
"street": "2441 George Street"
},
"highlight": {},
"highlights": []
}
],
"out_of": 48,
"page": 1,
"request_params": {
"collection_name": "identities",
"per_page": 2,
"q": "*"
},
"search_cutoff": false,
"search_time_ms": 14
}
```
The fields you include when filtering must be from the collection you are filtering by. In this example, we are filtering by balances, so we can only include fields from the balances collection.
Another example: you want to view all balances that has sent money at least once to a particular balance:
* First, you'll search for all balances – `/search/balances`.
* Next, add a "transactions" filter so you only return balances that were involved in a transaction where the destination matches the target balance.
* Finally, you can specify what transaction fields you want to include in the results.
```json Request wrap theme={"system"}
{
"q": "*",
"filter_by": "$transactions(destination:=bln_1234567890)",
"include_fields": "$transactions(transaction_id, amount, currency, status, created_at)"
}
```
***
## Merging / nesting joined fields
When the joined collection returns one result per document, the collection's fields are returned as nested objects. For example, see our first example response:
```json theme={"system"}
{
"facet_counts": [],
"found": 144,
"hits": [
{
"document": {
"balance": "9848100",
"balance_id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"identities": {
"email_address": "graciela.rosas@example.com",
"first_name": "Graciela",
"last_name": "Rosas"
}
}
}
]
}
```
You can merge the joined fields to the main document by specifying `strategy:merge` in your request.
```json Request theme={"system"}
{
"q": "*",
"include_fields": "$identities(*, strategy:merge)"
}
```
```json Merged response theme={"system"}
{
"facet_counts": [],
"found": 144,
"hits": [
{
"document": {
"balance": "9848100",
"balance_id": "bln_d9eb274a-d8bb-4ada-bc62-541d5e0073ac",
"email_address": "graciela.rosas@example.com",
"first_name": "Graciela",
"last_name": "Rosas"
}
}
]
}
```
### Handling nested arrays
When a join returns more than one match, the Search API gives you an array. When there is only one match, it becomes an object. This can make the shape inconsistent.
To keep it consistent, add `strategy:nest_array` so the joined data is always returned as an array. Example:
```json Request theme={"system"}
{
"q": "*",
"include_fields": "$balances(*, strategy:nest_array)"
}
```
This ensures the joined `balances` data is always an array, no matter how many results it contains.
***
## Nested JOINs
You can stack JOINs to go deeper. For example, you can join a balance to its identity, then also join that same balance to its ledger in the same query.
```json Request wrap theme={"system"}
{
"q": "*",
"include_fields": "$balances(balance, currency, $ledgers(*), strategy:nest_array)"
}
```
```json Response expandable theme={"system"}
{
"facet_counts": [],
"found": 48,
"hits": [
{
"document": {
"balances": [
{
"balance": "16712100",
"currency": "USD",
"ledgers": {
"created_at": 1763661567,
"ledger_id": "ldg_ad728e47-b730-4356-b1a7-703f42d33f87",
"meta_data": {},
"name": "Customers Ledger"
}
}
],
"email_address": "debra.barrett@example.com",
"first_name": "Debra",
"identity_id": "idt_651d448d-772d-4ae3-a878-836d39600e4a",
"last_name": "Barrett"
}
}
]
}
```
***
## Need help?
We are very happy to help you make the most of Blnk, regardless of whether it is your first time or you are switching from another tool.
To ask questions or discuss issues, please [contact us](mailto:support@blnkfinance.com) or [join our Discord community](https://discord.gg/7WNv94zPpx).
***
**Tip:** Connect to Blnk Cloud to see your Core data.
You can view your transactions, manage identities, create custom reports, invite other team members to collaborate, and perform operations on your Core — all in one dashboard.
[Check out Blnk Cloud →](https://www.blnkfinance.com/products/cloud)