Enable Schema Drift in Azure Data Factory
Question
Hugh is a Data Analyst of Woodgrove Inc.
He's working on data orchestration using Azure data factory for copying data from the Azure data lake storage Gen2 to Databricks & transformation.
In the pipeline, he's using ADF to build complex solutions with data flow's schema drift feature & applying reusable patterns based on flexible dataset schemas.
He needs to apply schema drift in source settings in Azure Data factory to define the source data flow as drifted.
The schema drift is defined as reading columns that aren't defined in the dataset schema.
He checked the option “Allow schema drift” & “infer drifted column types” in the source settings of the ADF pipeline.
Does the solution meet the requirements of enabling “schema drift” in the Data Factory pipeline?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B.Correct Answer: A.
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The solution provided by Hugh appears to meet the requirements of enabling schema drift in the Data Factory pipeline.
Schema drift refers to the ability to read columns that are not defined in the dataset schema. This can be useful when dealing with data sources that have dynamic or changing schemas.
In the given scenario, Hugh is using Azure Data Factory (ADF) to build complex solutions with data flow's schema drift feature. He needs to apply schema drift in source settings in ADF to define the source data flow as drifted. To achieve this, he has checked the option "Allow schema drift" and "infer drifted column types" in the source settings of the ADF pipeline.
"Allow schema drift" is an option in ADF that enables the pipeline to read columns that are not defined in the dataset schema. "Infer drifted column types" is another option that allows ADF to automatically infer the data type of the drifted column. These settings are commonly used together to enable schema drift in a pipeline.
Therefore, it can be concluded that Hugh's solution meets the requirements of enabling schema drift in the Data Factory pipeline as he has enabled the necessary settings to allow the pipeline to read columns not defined in the dataset schema. The correct answer is A. Yes.