Azure Data Factory: Global Parameters Don't Behave as Expected with New Deployment Method
Problem: Developers using Azure Data Factory (ADF) have reported issues with global parameters when deploying pipelines using the new deployment method. This method, introduced in recent Azure Data Factory updates, aims to simplify the pipeline deployment process. However, many users are facing challenges where global parameters defined in the ADF's main pipeline configuration don't propagate correctly to child pipelines.
Rephrasing: Imagine you're building a complex data pipeline in Azure Data Factory. You use global parameters to manage common configurations like database connection strings or file paths. When you deploy this pipeline using the new method, the global parameters don't appear to work as expected in your child pipelines.
Original Code (Example):
// Main Pipeline (adf_pipeline.json)
{
"name": "MyMainPipeline",
"properties": {
"parameters": {
"myConnectionString": {
"type": "string",
"defaultValue": "my_default_connection_string"
}
}
}
}
// Child Pipeline (child_pipeline.json)
{
"name": "MyChildPipeline",
"properties": {
"activities": [
{
"type": "SqlServerSource",
"name": "SourceActivity",
"linkedServiceName": {
"referenceName": "MySqlServer",
"type": "LinkedServiceReference"
},
"sqlReaderQuery": "SELECT * FROM MyTable",
"connectionString": "@{pipeline().parameters.myConnectionString}"
}
]
}
}
Analysis and Clarification:
The new ADF deployment method focuses on deploying pipelines as ARM templates, using the az datafactory command. While this approach simplifies deployment, it changes how global parameters are handled. In the old method, global parameters were directly defined within the ADF workspace and propagated to child pipelines. However, in the new method, global parameters are defined as resources in the ARM template itself, which requires explicit inclusion within each child pipeline that utilizes them.
Key Insights:
- Parameter Scope Change: Global parameters in the new deployment method are scoped to the ARM template, not the ADF workspace.
- Explicit Definition Required: Child pipelines must explicitly declare the global parameters they need within their definition, using the
parametersproperty. - Deployment Strategy Impact: Deploying pipelines using the new method necessitates careful consideration of global parameter handling and their inclusion in child pipeline definitions.
Solution:
To resolve this issue, you need to adjust your child pipeline definition by explicitly referencing the global parameter within the parameters section:
// Child Pipeline (child_pipeline.json)
{
"name": "MyChildPipeline",
"properties": {
"parameters": {
"myConnectionString": {
"type": "string",
"defaultValue": "my_default_connection_string"
}
},
"activities": [
{
"type": "SqlServerSource",
"name": "SourceActivity",
"linkedServiceName": {
"referenceName": "MySqlServer",
"type": "LinkedServiceReference"
},
"sqlReaderQuery": "SELECT * FROM MyTable",
"connectionString": "@{pipeline().parameters.myConnectionString}"
}
]
}
}
Additional Value:
- Transition Guide: Consider the transition guide provided by Microsoft for migrating existing ADF pipelines to the new deployment method. This guide outlines best practices and potential challenges.
- Code Snippet: Providing working code snippets showcasing global parameter usage within both main and child pipelines will be immensely helpful.
- Community Forums: Encourage users to consult with the Azure Data Factory community forums for further assistance and to share their experiences with the new deployment method.
References:
- Azure Data Factory Deployment Methods
- Azure Data Factory - Migrate your existing pipelines to the new deployment method
Conclusion:
While the new deployment method brings advantages, it also introduces subtle changes in how global parameters are managed. Understanding these changes and adapting your code accordingly is crucial for ensuring successful pipeline deployments. By following the steps outlined above, you can effectively utilize global parameters within the new deployment method and maintain the flexibility and control you need to build robust and efficient data pipelines.
