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Watermark Table: What You Should Know

The watermark is added on-premises to the source table with one key called watermark_key. Each run adds a new row to this key of the  watermark column. With multiple updates, the watermark row is added to the key for each new run; therefore, multiple  watermark value row must be added at a time.  Note: Watermark  is not an updating key in Azure Data Factory. Instead, watermark_key is the only key that contains the date value associated with each entry in the high-watermark table. This update  value is not referenced in the update output of the source data.  Azure Data Factory and the High-Watermark table — Example —  Note: watermark_key is the only key that contains the date attribute, which is the watermark_time_stamp_value_key in the  Example Table.  You can also use an alternate key, watermark_value_key. An alternative key may include a column to store the incrementing key for the watermark value row. Example —  Incremental Data Loading Using Azure Data Factory — Example Table — Azure Data Factory  Incremental Data Loading with a control table — Example Table Incremental Data Loading in Azure SQL Database — Example Table Azure Data Factory + control table = Incremental Data Loading in Azure SQL Database Using Azure Data Factory + Azure data warehouse table = Incremental Data Loading in Azure SQL DB See, incremental loading is so easy. Once an Incremental Loading data is  presented to it, it can do all the heavy lifting itself and do it on-premises using on Azure watermark store.

FAQ

What is watermark column in SQL?
In this case, you define a watermark in your source database. A watermark is a column that has the last updated time stamp or an incrementing key. The delta loading solution loads the changed data between an old watermark and a new watermark.
How does Azure data Factory handle incremental load?
You perform the following steps in this tutorial. Prepare the data store to store the watermark value. Create a data factory. Create linked services. Create source, sink, and watermark datasets. Create a pipeline. Run the pipeline. Monitor the pipeline run. Review results.
How do you do a full load in ADF?
0.26 3.20 Incremental data loading with Azure Data Factory and Azure ... - YouTube YouTube Start of suggested clip End of suggested clip Under source options there's a there's a property called enable incremental extract this is inMoreUnder source options there's a there's a property called enable incremental extract this is in public preview. If you check that box you will then be prompted.
What is watermark column?
A watermark is a column that has the last updated time stamp or an incrementing key. The delta loading solution loads the changed data between an old watermark and a new watermark.
How does ADF handle incremental load?
You perform the following steps in this tutorial. Prepare the data store to store the watermark value. Create a data factory. Create linked services. Create source, sink, and watermark datasets. Create a pipeline. Run the pipeline. Monitor the pipeline run. Review results.
What is Azure data flow?
Mapping data flows are visually designed data transformations in Azure Data Factory. Data flows allow data engineers to develop data transformation logic without writing code. The resulting data flows are executed as activities within Azure Data Factory pipelines that use scaled-out Apache Spark clusters.
What is incremental load in ETL?
The ETL Incremental Loading technique is a fractional loading method. It reduces the amount of data that you add or change and that may need to be rectified in the event of any irregularity. Because less data is reviewed, it also takes less time to validate the data and review changes.
What is a watermark table?
A watermark is a column in the source table that has the last updated time stamp or an incrementing key. After every iteration of data loading, the maximum value of the watermark column for the source data table is recorded.