📘 Overview

SQLByColumnGenerator is an operator designed to synthesize SQL queries based on database information. It iterates through connected databases, analyzes their schemas, and leverages a Large Language Model (LLM) to generate a variety of SQL queries. This process helps create diverse and relevant datasets for tasks like Text-to-SQL model training and evaluation, covering different complexities, functions, and styles.

__init__ function

def __init__(self, 
             llm_serving: LLMServingABC, 
             database_manager: DatabaseManager,
             generate_num: int = 5,
             prompt_template = None
    ):

Parameter	Type	Default	Description
llm_serving	LLMServingABC	Required	An instance of a Large Language Model serving class, used for generating SQL queries.
database_manager	DatabaseManager	Required	A manager instance that handles database connections and retrieves schema information.
generate_num	int	5	The number of SQL queries to generate for each special column within a database schema.
prompt_template	PromptABC	SelectSQLGeneratorPrompt	The prompt template object used to construct inputs for the LLM. Defaults to SelectSQLGeneratorPrompt.

Prompt Template Descriptions

Prompt Template Name	Primary Purpose	Applicable Scenarios	Feature Description

run function

def run(self, storage: DataFlowStorage,
        output_sql_key: str = "sql",
        output_db_id_key: str = "db_id"
    ):

Parameter	Type	Default	Description
storage	DataFlowStorage	Required	The DataFlow storage instance used for writing the generated data.
output_sql_key	str	"sql"	The column name for the generated SQL queries in the output.
output_db_id_key	str	"db_id"	The column name for the corresponding database ID in the output.

🧠 Example Usage

# Blank

🧾 Default Output Format

Field	Type	Description
db_id	str	The identifier of the database for which the SQL was generated.
sql	str	The generated SQL query string.

Example Input:

This operator does not require a specific input file, as it generates data based on the database schemas accessible via the database_manager.

Example Output:

{
  "db_id": "chinook_1",
  "sql": "SELECT T1.Title, T2.Name FROM Album AS T1 JOIN Artist AS T2 ON T1.ArtistId = T2.ArtistId ORDER BY T2.Name DESC LIMIT 3;"
}