Merge pull request #216821 from kromerm/cdcupdates

Cdcupdates

Author: prmerger-automator[bot]

articles/data-factory/concepts-change-data-capture.md

@@ -9,7 +9,7 @@ ms.service: data-factory
 ms.subservice: data-movement
 ms.custom: synapse
 ms.topic: conceptual
-ms.date: 10/18/2022
+ms.date: 11/01/2022
 ---
 
 # Change data capture in Azure Data Factory and Azure Synapse Analytics
@@ -26,7 +26,7 @@ When you perform data integration and ETL processes in the cloud, your jobs can
 
 ### Native change data capture in mapping data flow
 
-The changed data including inserted, updated and deleted rows can be automatically detected and extracted by ADF mapping data flow from the source databases.  No timestamp or ID columns are required to identify the changes since it uses the native change data capture technology in the databases.  By simply chaining a source transform and a sink transform reference to a database dataset in a mapping data flow, you will see the changes happened on the source database to be automatically applied to the target database, so that you can easily synchronize data between two tables.  You can also add any transformations in between for any business logic to process the delta data.
+The changed data including inserted, updated and deleted rows can be automatically detected and extracted by ADF mapping data flow from the source databases.  No timestamp or ID columns are required to identify the changes since it uses the native change data capture technology in the databases.  By simply chaining a source transform and a sink transform reference to a database dataset in a mapping data flow, you will see the changes happened on the source database to be automatically applied to the target database, so that you can easily synchronize data between two tables.  You can also add any transformations in between for any business logic to process the delta data. When defining your sink data destination, you can set insert, update, upsert, and delete operations in your sink without the need of an Alter Row transformation because ADF is able to automatically detect the row makers.
 
 **Supported connectors**
 -   [SAP CDC](connector-sap-change-data-capture.md)

articles/data-factory/data-flow-alter-row.md

@@ -9,7 +9,7 @@ ms.service: data-factory
 ms.subservice: data-flows
 ms.topic: conceptual
 ms.custom: synapse, ignite-2022
-ms.date: 08/03/2022
+ms.date: 11/01/2022
 ---
 
 # Alter row transformation in mapping data flow
@@ -26,6 +26,9 @@ Alter Row transformations only operate on database, REST, or Azure Cosmos DB sin
 
 > [!VIDEO https://www.microsoft.com/en-us/videoplayer/embed/RE4vJYc]
 
+> [!NOTE]
+> An Alter Row transformation is not needed for Change Data Capture data flows that use native CDC sources like SQL Server or SAP. In those instances, ADF will automatically detect the row marker so Alter Row policies are unnecessary.
+
 ## Specify a default row policy
 
 Create an Alter Row transformation and specify a row policy with a condition of `true()`. Each row that doesn't match any of the previously defined expressions will be marked for the specified row policy. By default, each row that doesn't match any conditional expression will be marked for `Insert`.

articles/data-factory/data-flow-sink.md

@@ -9,7 +9,7 @@ ms.service: data-factory
 ms.subservice: data-flows
 ms.topic: conceptual
 ms.custom: seo-lt-2019, ignite-2022
-ms.date: 10/26/2022
+ms.date: 11/01/2022
 ---
 
 # Sink transformation in mapping data flow
@@ -106,6 +106,10 @@ For example, if I specify a single key column of `column1` in a cache sink calle
 
 **Write to activity output** The cached sink can optionally write your output data to the input of the next pipeline activity. This will allow you to quickly and easily pass data out of your data flow activity without needing to persist the data in a data store.
 
+## Update method
+
+For database sink types, the Settings tab will include an "Update method" property. The default is insert but also includes checkbox options for update, upsert, and delete. To utilize those additional options, you will need to add an [Alter Row transformation](data-flow-alter-row.md) before the sink. The Alter Row will allow you to define the conditions for each of the database actions. If your source is a native CDC enable source, then you can set the update methods without an Alter Row as ADF is already aware of the row markers for insert, update, upsert, and delete.
+
 ## Field mapping
 
 Similar to a select transformation, on the **Mapping** tab of the sink, you can decide which incoming columns will get written. By default, all input columns, including drifted columns, are mapped. This behavior is known as *automapping*.