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Yandex Query
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      • YQL to JSON type mapping
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In this article:

  • Request
  • Response
  • Example
  1. Reference
  2. HTTP API
  3. Methods
  4. get-query-results

get-query-results

Written by
Yandex Cloud
Updated at July 1, 2026
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  • Request
  • Response
  • Example

This method returns query results. A query containing multiple SELECT statements returns multiple query results. If this is the case, you can access results by their index.

When using the HTTP API, you must authenticate by providing the required headers. You can also specify optional headers to control how requests are executed. The HTTP API may return errors.

RequestRequest

GET request to /queries/{query_id}/results/{<query_result_number_starting_from_0>}?project={folder_id}, where {folder_id} is the folder ID and {query_id} is the query ID.

SQL query arguments are provided in the URL as query string variables.

Argument Description Default value Limitations
offset The number of rows to skip before starting to return rows from the query result set 0 Cannot be negative
limit Number of result rows 100 This value must be between 1 and 1,000

ResponseResponse

If successful, the response returns an HTTP 200 status code and query results.

{
  "columns": [
    {
      "name": "column0",
      "type": "Int32"
    },
    {
      "name": "column1",
      "type": "Int32"
    }    
  ],
  "rows": [
    [
      "1",
      "2"
    ],
    [
      "3",
      "4"
    ]    
  ]
}
Field Description
columns Result column array
columns[].name Column name
columns[].type Column data type
rows Result row array Each row array’s element count matches the number of columns in the columns field

Conversion rules from YQL data types to JSON-compatible data types are described in the YQL to JSON type mapping section.

ExampleExample

Request:

curl \
  --request 'GET' \
  'https://api.yandex-query.cloud.yandex.net/api/fq/v1/queries/cseugn35bc3r********/results/0?project=b1gaue5b382m********&offset=0&limit=100' \
  --header 'accept: application/json'

Response:

{
  "columns": [
    {
      "name": "column0",
      "type": "Int32"
    },
    {
      "name": "column1",
      "type": "Int32"
    }    
  ],
  "rows": [
    [
      "1",
      "2"
    ],
    [
      "3",
      "4"
    ]
  ]
}

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