Apache Airflow™

Written by

Updated at July 7, 2026

To operate under the Apache Airflow™ management, Yandex Query provides the apache-airflow-providers-yandex package. Apache Airflow™ jobs are Python applications consisting of Apache Airflow™ operators and their dependencies, which decide the order of execution. To make queries to Yandex Query, the package contains the YQExecuteQueryOperator Apache Airflow™ operator.

To run queries against Yandex Query, you need to initialize YQExecuteQueryOperator using the arguments listed below.

Required arguments:

Optional arguments:

folder_id: Target folder for the query. If not specified, it defaults to the Managed Service for Apache Airflow™ folder.
yandex_conn_id: Connection ID of type yandexcloud, containing the parameters for connecting to Yandex Cloud. If not specified, defaults to the yandexcloud_default connection. The yandexcloud_default connection comes preconfigured with Managed Service for Apache Airflow™, so you do not need to create it manually.

Here is an example:

yq_operator = YQExecuteQueryOperator(task_id="yq_operator", sql="SELECT 'Hello, world!'")

This example creates an Apache Airflow™ task with ID yq_operator that runs SELECT 'Hello, world!'. For a complete example of running a query in Yandex Query from Managed Service for Apache Airflow™, refer to Automating Yandex Query tasks with Yandex Managed Service for Apache Airflow™.

Return values

A successful YQExecuteQueryOperator returns data as a dict that contains an array of column descriptions and an array of result rows.

Query:

yq_operator = YQExecuteQueryOperator(task_id="yq_operator", sql="SELECT 'Hello, World!'")

Result:

{
  'rows': [['Hello, world!']],
  'columns': [{'name': 'column0', 'type': 'String'}]
}

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

The following rules apply when converting YQL types to Python types.

YQL type	Python type	Python example
`Int8`, `Int16`, `Int32`, `Uint8`, `Uint16`, `Uint32`, `Int64`, `Uint64`	`int`	`647713`
`Bool`	`bool`	True
`Float`, `Double`	`double` NaN and Inf become `None`	`7.88731023` `None`
`Decimal`	`Decimal`	`45.23410083`
`Utf8`	`str`	`String text`
`String`	`str` `bytes`	`String text`

YQL type	Python type	Python example
`Json`, `JsonDocument`	`str` (whole node serialized to a string)	`{"a":[1,2,3]}`
`Date`, `Datetime`, `Timestamp`	`datetime`	`2022-02-09`

YQL type	Python type	Python example
`Optional`	Original type or None	`1`

YQL type	Python type	Python example
`List<Type>`	`list`	`[1,2,3,4]`
`Dict<KeyType, ValueType>`	`dict`	`{key1: value1, key2: value2}`
`Set<KeyType>`	`set`	`set(key_value1, key_value2)`
`Tuple<Type1, Type2>`	`tuple`	`(element1, element2, ..)`
`Struct<Name:Utf8,Age:Int32>`	`dict`	`{ "Name": "John", "Age": 128 }`
`Variant<Type1, Type2>` with a tuple	`list`	`list[64563, 1]`
`Variant<value:Int32,error:String>` structured string	`dict`	`{key1: value1, key2: value2}`