Microsoft Fabric - Placeholder values - 1.9

Please consult the article Replace the placeholders in the Artifacts to learn how to replace the placeholders with the values explained below.

Placeholder values

Depending on the Generator Configuration you are using for a Microsoft Fabric Target Technology, you can replace the placeholder values with the following:

database_name

Each database_name is filled by default with the layer name (example: rawvault).

It should contain the database name of the target lakehouse.

Example: docu_bglakehouse.

If you are using a Linked Project (from a Stage JDBC or a Stage File Project), it should contain the database name of the target lakehouse containing the source table created before with the Linked Project.

schema_name

Each database_directory must be empty, it is not needed for Microsoft Fabric.

file_path

Each file_path placeholder should contain the path where the Source Parquet files are available.

If you are using our Microsoft Fabric environment example, you can copy the path by:

• Opening the Lake House (docu_bglakehouse in our example) in the left menu:
  
• Opening the Context menu of the Files folder and choosing the Properties option:
  
• Copying the ABFS path:
  
• Add at the end your folder structure for each source as for the Creditcard source data:
  • They are stored inside the Files folder on the path Parquet
    
  • The ABFS path of the Files folder is abfss://bgfabricstagefiles@onelake.dfs.fabric.microsoft.com/docu_bglakehouse.Lakehouse/Files
  • The file_path to fill in the replacement_config.json file for the credit card source is: abfss://bgfabricstagefiles@onelake.dfs.fabric.microsoft.com/docu_bglakehouse.Lakehouse/Files/Parquet/

 

jdbc_url

For a SQL Server JDBC source, for example: jdbc:sqlserver://{ServerName}.database.windows.net:1433;encrypt=true;databaseName={DatabaseName};trustServerCertificate=true;

Replace:

• {ServerName} with your Azure SQL Server name
• {DatabaseName} with your SQL Server database name.

jdbc_driver

For a SQL Server JDBC source, for example:

com.microsoft.sqlserver.jdbc.SQLServerDriver

jdbc_user

For a SQL Server JDBC source, for example:

'{DatabaseUser}'

Replace {DatabaseUser} with your SQL Server user

Or you can use KeyVault to store a secret.

In this case, the syntax should be:
dbutils.secrets.get(scope='jdbc', key='<name of the secret>') 

jdbc_password

For a SQL Server JDBC source, for example:

'{DatabasePassword}'

Replace {DatabasePassword} with your SQL Server password

log_table_name

For logging, you can choose the table name that will contain the logs.

It is execution_log by default.

application_name

For logging, you can fill application_name to easily identify the logs concerning your Project in Databricks.

application_environment_name

For logging, you can fill application_environment_name to easily identify the logs concerning your Project in Databricks, depending on the target environment (development, integration, production...).

It is DEV by default.