📄️ History in Fabric Lakehouse
Overview
📄️ History Tables Load Options
Data can be loaded into Fabric with different options. Full load is the most common, but can take a long time in case of a lot of data. So for those situations, it would be nice to load just a fraction of the data. This can be done in several different ways, often depending on what is possible in the source. This page explains the following situation:
📄️ Custom extensions
Every data platform has its unique characteristics. While many situations are similar, each company has its own specific requirements. Sometimes, it is necessary to perform actions that do not fit the standard workflow. In these scenarios, it is helpful to know that custom actions can be added to the flow.
📄️ Blob file trigger
The blob file trigger can be used to automatically trigger events as soon as a file is created to an Azure Blob storage. This can be useful when users or third-parties are delivering files to your dataplatform. In some cases it's not possible to give immediate access to Fabric itself. A separate Azure Blob storage is solid solution in such cases.
📄️ DataFrame Display Extension
The display extension provides a convenient way to visualize PySpark DataFrames within Microsoft Fabric notebooks. It automatically handles the environment context to ensure interactive visualization works where possible.
📄️ Read latest Silver snapshot
The getsilversnapshot function is designed to retrieve the current state (snapshot) of a dataset from its Silver history table. It effectively deduplicates history records into a single representative row for each primary key.
📄️ Gold Loader
The Gold Layer loader in EasyFabric is designed to load data into dimension and fact tables while handling surrogate key generation, validation, and different load types.