transform_file operator

When to use the transform_file operator

The transform_file operator allows you to implement the T of an ELT system by running a SQL query from specified SQL file. Each step of the transform pipeline creates a new table from the SELECT statement and enables tasks to pass those tables as if they were native Python objects.

The transform_file functions return a Table object that can be passed to future tasks. This table will be either an auto-generated temporary table, or will overwrite a table given in the output_table parameter. The transform_file operator treats values in the double brackets as Airflow jinja templates. You can find more details on templating at Templating.

    table_from_query = aql.transform_file(
        parameters={"input_table": imdb_movies},
        op_kwargs={"output_table": target_table},


  • query_modifier - The query_modifier parameter allows you to define statements to run before and after the run_raw_sql main statement. To associate a Snowflake query tag, for instance, it is possible to use query_modifier=QueryModifier(pre_queries=["ALTER SESSION SET QUERY_TAG=<my-query-tag>]).