Merge pull request #217257 from jonburchel/2022-11-04-public-prs

2022 11 04 public prs

Author: 19BMG00

articles/data-factory/continuous-integration-delivery-improvements.md

@@ -119,7 +119,7 @@ Follow these steps to get started:
    ```json
    {
        "scripts":{
-           "build":"node node_modules/@microsoft/azure-data-factory-utilities/lib/index",
+           "build":"node node_modules/@microsoft/azure-data-factory-utilities/lib/index"
        },
        "dependencies":{
            "@microsoft/azure-data-factory-utilities":"^1.0.0"

articles/data-factory/create-self-hosted-integration-runtime.md

@@ -421,6 +421,9 @@ Based on your source and sinks, you might need to allow additional domains and o
 
 For some cloud databases, such as Azure SQL Database and Azure Data Lake, you might need to allow IP addresses of self-hosted integration runtime machines on their firewall configuration.
 
+> [!NOTE]
+> It is not right to install both Integration Runtime and Power BI gateway in same machine, because mainly Integration Runtime uses port number 443, which is one of the main ports being used by Power BI gateway as well.
+
 ### Get URL of Azure Relay
 
 One required domain and port that need to be put in the allowlist of your firewall is for the communication to Azure Relay. The self-hosted integration runtime uses it for interactive authoring such as test connection, browse folder list and table list, get schema, and preview data. If you don't want to allow **.servicebus.windows.net** and would like to have more specific URLs, then you can see all the FQDNs that are required by your self-hosted integration runtime from the service portal. Follow these steps:

articles/data-factory/media/wrangling-data-flow/power-query-new-sink.png

@@ -29,7 +29,7 @@ The other method is in the activities pane of the pipeline canvas. Open the **Po
 
 > [!VIDEO https://www.microsoft.com/videoplayer/embed/RWJd3T]
 > 
-Add a **Source dataset** for your Power Query mash-up. You can either choose an existing dataset or create a new one. After you have saved your mash-up, you can then add the Power Query data wrangling activity to your pipeline and select a sink dataset to tell ADF where to land your data. While you can choose one or more source datasets, only one sink is allowed at this time. Choosing a sink dataset is optional, but at least one source dataset is required.
+Add a **Source dataset** for your Power Query mash-up. You can either choose an existing dataset or create a new one. After you have saved your mash-up, you can then create a pipeline, add the Power Query data wrangling activity to your pipeline and select a sink dataset to tell ADF where to land your data. While you can choose one or more source datasets, only one sink is allowed at this time. Choosing a sink dataset is optional, but at least one source dataset is required.
 
 :::image type="content" source="media/wrangling-data-flow/tutorial4.png" alt-text="Wrangling":::
 
@@ -39,7 +39,7 @@ First, you will choose a dataset source for the mashup editor.
 
 :::image type="content" source="media/wrangling-data-flow/power-query-new-source.png" alt-text="Power Query source.":::
 
-Once you have completed building your Power Query, you can save it and add the mashup as an activity to your pipeline. That is when you will set the sink dataset properties.
+Once you have completed building your Power Query, you can save it and then create a pipeline. You need to add the mashup as an activity to your pipeline. That is when you will create/select the sink dataset to land your data. You can also set the sink dataset properties by clicking on the second button on the right side of the sinked dataset. Remember to change the "partition option" under "Optimize" to "Single partition" if you only want to get a single output file.
 
 :::image type="content" source="media/wrangling-data-flow/power-query-new-sink.png" alt-text="Power Query sink.":::