使用 SQLExecuteQueryOperator 連線至 MSSQL

本指南旨在定義使用 SQLExecuteQueryOperator 與 MSSQL 資料庫互動的任務。

使用 SQLExecuteQueryOperator 在 MSSQL 資料庫中執行 SQL 命令。

注意

先前,MsSqlOperator 用於執行此類操作。請改用 SQLExecuteQueryOperator

使用 SQLExecuteQueryOperator 的常見資料庫操作

若要使用 SQLExecuteQueryOperator 對 MSSQL 資料庫執行 SQL 查詢,需要兩個參數:sqlconn_id。這兩個參數最終會傳遞給直接與 MSSQL 資料庫互動的 MSSQL hook 物件。

建立 MSSQL 資料庫表格

以下程式碼片段基於 Airflow-2.2

以下是使用 SQLExecuteQueryOperator 連線至 MSSQL 的範例用法

tests/system/microsoft/mssql/example_mssql.py[原始碼]


    # Example of creating a task to create a table in MsSql

    create_table_mssql_task = SQLExecuteQueryOperator(
        task_id="create_country_table",
        conn_id="airflow_mssql",
        sql=r"""
        CREATE TABLE Country (
            country_id INT NOT NULL IDENTITY(1,1) PRIMARY KEY,
            name TEXT,
            continent TEXT
        );
        """,
        dag=dag,
    )

您也可以使用外部檔案來執行 SQL 命令。腳本資料夾必須與 DAG.py 檔案位於同一層級。這樣一來,您可以輕鬆地將 SQL 查詢與程式碼分離維護。

tests/system/microsoft/mssql/example_mssql.py[原始碼]

    # Example of creating a task that calls an sql command from an external file.
    create_table_mssql_from_external_file = SQLExecuteQueryOperator(
        task_id="create_table_from_external_file",
        conn_id="airflow_mssql",
        sql="create_table.sql",
        dag=dag,
    )

您的 dags/create_table.sql 應該看起來像這樣

將資料插入 MSSQL 資料庫表格

然後,我們可以建立一個 SQLExecuteQueryOperator 任務來填充 Users 表格。

tests/system/microsoft/mssql/example_mssql.py[原始碼]

    populate_user_table = SQLExecuteQueryOperator(
        task_id="populate_user_table",
        conn_id="airflow_mssql",
        sql=r"""
                INSERT INTO Users (username, description)
                VALUES ( 'Danny', 'Musician');
                INSERT INTO Users (username, description)
                VALUES ( 'Simone', 'Chef');
                INSERT INTO Users (username, description)
                VALUES ( 'Lily', 'Florist');
                INSERT INTO Users (username, description)
                VALUES ( 'Tim', 'Pet shop owner');
                """,
    )

從您的 MSSQL 資料庫表格中提取記錄

從您的 MSSQL 資料庫表格中提取記錄可以很簡單,就像

tests/system/microsoft/mssql/example_mssql.py[原始碼]

    get_all_countries = SQLExecuteQueryOperator(
        task_id="get_all_countries",
        conn_id="airflow_mssql",
        sql=r"""SELECT * FROM Country;""",
    )

將參數傳遞到 SQLExecuteQueryOperator

SQLExecuteQueryOperator 提供 parameters 屬性,這使得在執行期間將值動態注入到您的 SQL 請求中成為可能。

要查找亞洲大陸的國家

tests/system/microsoft/mssql/example_mssql.py[原始碼]

    get_countries_from_continent = SQLExecuteQueryOperator(
        task_id="get_countries_from_continent",
        conn_id="airflow_mssql",
        sql=r"""SELECT * FROM Country where {{ params.column }}='{{ params.value }}';""",
        params={"column": "CONVERT(VARCHAR, continent)", "value": "Asia"},
    )

完整的 SQLExecuteQueryOperator DAG 以連線至 MSSQL

當我們將所有內容放在一起時,我們的 DAG 應該看起來像這樣

tests/system/microsoft/mssql/example_mssql.py[原始碼]

import os
from datetime import datetime

import pytest

from airflow import DAG

try:
    from airflow.providers.common.sql.operators.sql import SQLExecuteQueryOperator
    from airflow.providers.microsoft.mssql.hooks.mssql import MsSqlHook
except ImportError:
    pytest.skip("MSSQL provider not available", allow_module_level=True)

ENV_ID = os.environ.get("SYSTEM_TESTS_ENV_ID")
DAG_ID = "example_mssql"


with DAG(
    DAG_ID,
    schedule="@daily",
    start_date=datetime(2021, 10, 1),
    tags=["example"],
    catchup=False,
) as dag:

    # Example of creating a task to create a table in MsSql

    create_table_mssql_task = SQLExecuteQueryOperator(
        task_id="create_country_table",
        conn_id="airflow_mssql",
        sql=r"""
        CREATE TABLE Country (
            country_id INT NOT NULL IDENTITY(1,1) PRIMARY KEY,
            name TEXT,
            continent TEXT
        );
        """,
        dag=dag,
    )

    @dag.task(task_id="insert_mssql_task")
    def insert_mssql_hook():
        mssql_hook = MsSqlHook(mssql_conn_id="airflow_mssql", schema="airflow")

        rows = [
            ("India", "Asia"),
            ("Germany", "Europe"),
            ("Argentina", "South America"),
            ("Ghana", "Africa"),
            ("Japan", "Asia"),
            ("Namibia", "Africa"),
        ]
        target_fields = ["name", "continent"]
        mssql_hook.insert_rows(table="Country", rows=rows, target_fields=target_fields)
    # Example of creating a task that calls an sql command from an external file.
    create_table_mssql_from_external_file = SQLExecuteQueryOperator(
        task_id="create_table_from_external_file",
        conn_id="airflow_mssql",
        sql="create_table.sql",
        dag=dag,
    )
    populate_user_table = SQLExecuteQueryOperator(
        task_id="populate_user_table",
        conn_id="airflow_mssql",
        sql=r"""
                INSERT INTO Users (username, description)
                VALUES ( 'Danny', 'Musician');
                INSERT INTO Users (username, description)
                VALUES ( 'Simone', 'Chef');
                INSERT INTO Users (username, description)
                VALUES ( 'Lily', 'Florist');
                INSERT INTO Users (username, description)
                VALUES ( 'Tim', 'Pet shop owner');
                """,
    )
    get_all_countries = SQLExecuteQueryOperator(
        task_id="get_all_countries",
        conn_id="airflow_mssql",
        sql=r"""SELECT * FROM Country;""",
    )
    get_all_description = SQLExecuteQueryOperator(
        task_id="get_all_description",
        conn_id="airflow_mssql",
        sql=r"""SELECT description FROM Users;""",
    )
    get_countries_from_continent = SQLExecuteQueryOperator(
        task_id="get_countries_from_continent",
        conn_id="airflow_mssql",
        sql=r"""SELECT * FROM Country where {{ params.column }}='{{ params.value }}';""",
        params={"column": "CONVERT(VARCHAR, continent)", "value": "Asia"},
    )
    (
        create_table_mssql_task
        >> insert_mssql_hook()
        >> create_table_mssql_from_external_file
        >> populate_user_table
        >> get_all_countries
        >> get_all_description
        >> get_countries_from_continent
    )

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