![]() ![]() This means that it will compare with the last non ignored locked release before the current one. The compare functionality in the source graphical overview will now skip ignored releases.Example: deploy.cmd = sh C:\Users\name\Documents\agent\deploy.sh ” Added extra template variables for the custom deploy scripts in the agent, instead of only the zip name, you can now also get the generation id, the generation info, and the generation type, similar to the git commit message functionality.We renamed the “build flag” property to “ignored” everywhere in the application.In a separate screen, you can change the order of the HUB’s included in a many to many link or non-historical link. We added similar ability to reorder the linked hubs in many-to-many links ( and non historized links). So the keys in the different sources can now have different orders and names and still result in the same hash key calculation. We added a new screen where for each hub group the business keys of the grouped objects can be renamed and reordered, and the business keys of the hubs in the group can be reordered to match. We made it easier to change and re-order business keys in the Data Vault. This allows you to track progress in your source modelling and get things organized. The selection page can filter out completed objects, and there is also a button to remove all completed objects from the canvas. This status can be toggled by right-clicking on an object. We also made it possible to mark objects in the source editor as completed, the completed objects will be highlighted in green. You can also choose to exclude certain sources from your release. It has become a lot easier to indicate which version of which sources you would like to include in a specific data vault release. 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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