Airflow 2.0 requirements9/27/2023 The new release comes with a few other changes like a better screen to create a new data vault release. Using this functionality can obviously save a lot of time when integrating similar sources into your Data Vault model. All you need to do is identify and configure objects or settings that are specific only for the new source, but you can now skip all similar configuration you had already done for the EU source. Using the source copy functionality, they can now copy the entire source configuration from EU Sales to US Sales. The only difference is that they have a few additional modules activated in the US. To give an example: Company ABC has the same version of their Sales CRM running in both Europe and the US. In some cases, an organization will need to integrate multiple sources that share a lot of similarities between them. Users will also have the ability to copy existing sources. You’re able to generate and deploy workflows and run all the code needed to load your Data Vault. Just like before, once you’ve installed our plugin into your Airflow environment, Airflow becomes VaultSpeed aware. ![]() All code will still work for previous Airflow versions. The VaultSpeed plugin for Airflow and all generated code have been reworked. The target Database type is still Spark, but the ETL generation type has to be set to Databricks SQL.Īpache Airflow 2.0 brings a truckload of great new features like a modernized user interface, the Airflow API, improved performance of the scheduler, the Taskflow API and others. Integration with Azure Data Factory is coming soon. Airflow will launch those jobs, running the Notebooks. The deployment will create Spark SQL notebooks in Databricks for all your Data Vault mappings. You are now able to generate and deploy Spark code to Databricks and run it with Airflow. Run your Data Vault in the Databricks data lakehouse! These, and many more changes, come with VaultSpeed R4.2.4! Databricks Also, VaultSpeed users can now copy an entire source configuration. We added support for Databricks, we updated our Flow Management connector to work with Apache Airflow 2.0. ![]() We’re back with a new release, and it is stuffed with new features.
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