# Search Preview: Multi-source Jobs API

{% columns %}
{% column width="16.666666666666664%" %}
Data type:

Query type:

URL:
{% endcolumn %}

{% column width="83.33333333333334%" %}
Multi-source Jobs

Elasticsearch DSL

<https://api.coresignal.com/cdapi/v2/job\\_multi\\_source/search/es\\_dsl/preview>
{% endcolumn %}
{% endcolumns %}

***

## Overview

Retrieve a limited set of fields from top-matching records in real time, and search suggestion features. Here, Multi-source Jobs API search `/v2/job_multi_source/search/es_dsl/preview` endpoint's usage is reviewed.

<table data-view="cards"><thead><tr><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td>General information about search preview</td><td><a href="../../api-introduction/requests/search-preview">search-preview</a></td></tr></tbody></table>

## Request queries

See the request example of `preview` endpoint. Search Preview endpoints accept the same query structure as their corresponding Search endpoints.&#x20;

{% code title="Elasticsearch DSL request" %}

```json
curl -X 'POST' \
'https://api.coresignal.com/cdapi/v2/job_multi_source/search/es_dsl/preview' \
  -H 'accept: application/json' \
  -H 'apikey: {API Key}' \
  -H 'Content-Type: application/json' \
  -d '{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "title": "manager"
          }
        },
        {
          "match": {
            "location": "Los Angeles"
          }
        }
      ]
    }
  }
}'
```

{% endcode %}

## Response structure

Here is an overview of the fields that are retrieved using the Multi-source Jobs API search preview endpoints.

| Data field     | Description                                     | Data type |
| -------------- | ----------------------------------------------- | --------- |
| `id`           | Unified job identifier across all sources       | Long      |
| `created_at`   | Timestamp when the job record was first created | Timestamp |
| `title`        | Standardized job title                          | String    |
| `location`     | Job location                                    | String    |
| `company_name` | Company name                                    | String    |
| `_score`       | Elasticsearch score                             | Float     |

**Refer to the data example here:**

{% hint style="info" %}
All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes.
{% endhint %}

{% code title="Elasticsearch DSL response" %}

```json
  {
    "id": 1234,
    "created_at": "2025-07-01 00:00:00",
    "title": "Event Manager",
    "location": "Los Angeles, CA",
    "company_name": "Example Company",
    "_score": 12.34567
  }
```

{% endcode %}

## Pagination

Example of the request using pagination query parameter `page`.

{% code title="Elasticsearch DSL request" %}

```json
curl -X 'POST' \
'https://api.coresignal.com/cdapi/v2/job_multi_source/search/es_dsl/preview?page=2' \
  -H 'accept: application/json' \
  -H 'apikey: {API Key}' \
  -H 'Content-Type: application/json' \
  -d '{
  "query": {
    "bool": {
      "must": [
        {
          "match": {
            "title": "manager"
          }
        },
        {
          "match": {
            "location": "CA"
          }
        }
      ]
    }
  }
}'
```

{% endcode %}

### Sorting options

Multi-source Jobs API `/v2/job_multi_source/search/es_dsl/preview` endpoint supports sorting capabilities, which are the same as found in Multi-source Jobs API's [Elasticsearch DSL](https://docs.coresignal.com/jobs-api/elasticsearch-dsl#sorting-options) topic.&#x20;


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.coresignal.com/jobs-api/multi-source-jobs-api/search-preview.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.