We’ve added a new mechanism to include Global Parameters in the ARM templates. This helps to solve an earlier issue, which overrode some configurations during deployments when users included global parameters in ARM templates.
3 new data transformation functions have been added to mapping data flows in Azure Data Factory and Azure Synapse Analytics. Now, users are able to use collectUnique(), to create a new collection of unique values in an array, substringIndex(), to extract the substring before n occurrences of a delimiter, and topN(), to return the top n results after sorting your data.
With the new user-defined functions feature, you can create customized expressions that can be reused across multiple mapping data flows. This will keep you from having to building complex logic over and over. User-defined functions will be grouped in libraries to help developers group common sets of functions.
Once you’ve created a data flow library, you can add in your user-defined functions. You can even add in multiple arguments to make your function more reusable.
Easier configuration of data flow runtime with preset compute sizes
Azure Data Factory has made it easier for users to configure Azure Integration Runtime for mapping data flows by adding new pre-configured categories for Spark Compute. You can still set your own custom configurations.