© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
R. L'EsteveThe Azure Data Lakehouse Toolkithttps://doi.org/10.1007/978-1-4842-8233-5_7

7. Schema Evolution

Ron L’Esteve1  
(1)
Chicago, IL, USA
 

For ELT scenarios where the schema of the data is constantly evolving, you may be seeking a method for accommodating these schema changes through schema evolution features available in Azure Databricks. Frequently, customers are interested in learning more about the features of schema evolution that are available in Azure Databricks and how they can get started with building notebooks and writing code that can accommodate evolving schemas.

Since every data frame in Apache Spark contains a schema, when it is written to ...

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