---
title: Databricks - Load data - Apache Airflow Load Control - 1.8
description: Databricks - Load data - Apache Airflow Load Control - 1.8
---

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3. [Load data with Apache Airflow](https://knowledge.bigenius-x.com/generators?hsLang=en#load-data-with-apache-airflow)

# Databricks - Load data - Apache Airflow Load Control - 1.8

Before loading the data from your Source(s) System(s) to your Databricks Target System, please: 

- <https://knowledge.bigenius-x.com/microsoft-sql-server-deployment-1.3.0?hsLang=en>[Deploy the generated Artifacts](https://knowledge.bigenius-x.com/generators?hsLang=en#deployment)
- Configure the [Load control environment for Apache Airflow](https://knowledge.bigenius-x.com/apache-airflow-load-control-environment?hsLang=en)

You are now ready to load the data with Apache Airflow.

### Create the Databricks Jobs

Airflow will use Databricks Jobs to load the data.

biGENIUS-X artifacts contain configuration files to create these Jobs.

Download the following helper: [deploy\_jobs.ps1](https://f926da42ec3845beb4acf72f.blob.core.windows.net/hubspotknowledgebase/deploy_jobs.ps1).

Copy it near the LoadControl folder of your generated artifacts:

![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-26-36-2931-PM.png?width=239&height=223&name=image-png-Aug-08-2024-01-26-36-2931-PM.png)

Then:

- Open **Powershell**
- Navigate to your generated artifacts folder:

```
--Examplecd C:\XXXXXXXXX\20240219144515
```

- Execute the Powershell script helper with the following parameters: 
    - Check [Apache Airflow - Load Control environment](https://knowledge.bigenius-x.com/apache-airflow-load-control-environment?hsLang=en#databricks-target-solution) to find the host and the token

```
-- Replace <yourhost> by the Databricks host-- Replace <yourtoken> by your PAT.\deploy_jobs.ps1 -databricksAccountName <yourhost> -jobsFolderName LoadControl -databricksToken <yourtoken>
```

You should have the following result for each Job creation:

![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-33-39-0888-PM.png?width=688&height=58&name=image-png-Aug-08-2024-01-33-39-0888-PM.png)

### Load the data with Apache Airflow

To load the data with Apache Airflow:

- Navigate to the Airflow homepage [http://localhost:8080](http://localhost:8080)  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-05-2024-02-55-31-1399-PM.png?width=688&height=230&name=image-png-Jun-05-2024-02-55-31-1399-PM.png)
- Enter your credentials
- You should have the following result:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-05-2024-02-56-15-1446-PM.png?width=688&height=216&name=image-png-Jun-05-2024-02-56-15-1446-PM.png)
- Configure a connection to your target solution environment by following the steps: 
    - Open the menu Admin \> Connections  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-36-12-8250-AM.png?width=507&height=168&name=image-png-Jun-06-2024-06-36-12-8250-AM.png)
    - Click on the plus icon  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-37-07-9860-AM.png?width=503&height=139&name=image-png-Jun-06-2024-06-37-07-9860-AM.png)
    - Enter the connection details:  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-13-41-9567-PM.png?width=688&height=561&name=image-png-Aug-08-2024-01-13-41-9567-PM.png)  
          - **Connection id**: Must be *databricks\_default*
          - **Connection Type**: select Databricks
          - **Host**: check [Apache Airflow - Load Control environment](https://knowledge.bigenius-x.com/apache-airflow-load-control-environment?hsLang=en#databricks-target-solution) to find it

- - - **Login**: Must be *token* (as we are using a PAT)
          - **Password**: Must be the PAT value (check [Apache Airflow - Load Control environment](https://knowledge.bigenius-x.com/apache-airflow-load-control-environment?hsLang=en#databricks-target-solution) to find it)
    - Check the connection by clicking on the Test button:  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-52-25-8266-AM.png?width=158&height=49&name=image-png-Jun-06-2024-06-52-25-8266-AM.png)
    - You should have the following message:  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-52-00-3336-AM.png?width=688&height=58&name=image-png-Jun-06-2024-06-52-00-3336-AM.png)
    - Save the connection by clicking on the Save button:  
      ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-52-54-6833-AM.png?width=158&height=49&name=image-png-Jun-06-2024-06-52-54-6833-AM.png)
- Go back to the DAGs list by clicking on the DAGs menu:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-54-19-7985-AM.png?width=541&height=42&name=image-png-Jun-06-2024-06-54-19-7985-AM.png)
- To launch a data load, click on the Trigger DAG button for the relevant DAG:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Jun-06-2024-06-55-31-9128-AM.png?width=129&height=87&name=image-png-Jun-06-2024-06-55-31-9128-AM.png)
- The data load started:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-20-45-2150-PM.png?width=688&height=121&name=image-png-Aug-08-2024-01-20-45-2150-PM.png)
- You can follow the data load by clicking on the DAG, then on the current execution (green bar), and finally on the Graph tab:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-21-18-8508-PM.png?width=688&height=299&name=image-png-Aug-08-2024-01-21-18-8508-PM.png)
- If you want to check the logs of the execution, click on the Audit Log tab:  
  ![](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Aug-08-2024-01-22-08-3096-PM.png?width=688&height=309&name=image-png-Aug-08-2024-01-22-08-3096-PM.png)
- You can now check that your data were correctly loaded by creating a Notebook in Databricks and executing with the following code:

```
-- Adapt the database and table names-- Add as many union as target tablesdf = spark.sql("""    select '`rawvault`.`rdv_sat_creditcard_delta_satellite_result`' as table_name    , count(*) as row_count    , max(bg_loadtimestamp) as max_bg_loadtimestamp    from `rawvault`.`rdv_sat_creditcard_delta_satellite_result`    union    select '`rawvault`.`rdv_hub_salesorderheader_hub_result`' as table_name    , count(*) as row_count    , max(bg_loadtimestamp) as max_bg_loadtimestamp    from `rawvault`.`rdv_hub_salesorderheader_hub_result`""")df.show(n=1000, truncate=False)
```

 

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