Fixes

Author: alexbuckgit

articles/data-factory/tutorial-bulk-copy.md

@@ -89,9 +89,9 @@ For both SQL Database and Azure Synapse Analytics, allow Azure services to acces
 2. Run the **Set-AzDataFactoryV2** cmdlet to create a data factory. Replace place-holders with your own values before executing the command. 
 
     ```powershell
-	$resourceGroupName = "<your resource group to create the factory>"
-	$dataFactoryName = "<specify the name of data factory to create. It must be globally unique.>"
-	Set-AzDataFactoryV2 -ResourceGroupName $resourceGroupName -Location "East US" -Name $dataFactoryName
+    $resourceGroupName = "<your resource group to create the factory>"
+    $dataFactoryName = "<specify the name of data factory to create. It must be globally unique.>"
+    Set-AzDataFactoryV2 -ResourceGroupName $resourceGroupName -Location "East US" -Name $dataFactoryName
     ```
 
     Note the following points:
@@ -478,31 +478,31 @@ This pipeline performs two steps:
 2. 	Run the following script to continuously check the run status of pipeline **GetTableListAndTriggerCopyData**, and print out the final pipeline run and activity run result.
 
     ```powershell
-	while ($True) {
+    while ($True) {
         $run = Get-AzDataFactoryV2PipelineRun -ResourceGroupName $resourceGroupName -DataFactoryName $DataFactoryName -PipelineRunId $runId
 
         if ($run) {
             if ($run.Status -ne 'InProgress') {
-                Write-Host "Pipeline run finished. The status is: " $run.Status -foregroundcolor "Yellow"
-                Write-Host "Pipeline run details:" -foregroundcolor "Yellow"
+                Write-Host "Pipeline run finished. The status is: " $run.Status -ForegroundColor "Yellow"
+                Write-Host "Pipeline run details:" -ForegroundColor "Yellow"
                 $run
                 break
             }
-            Write-Host  "Pipeline is running...status: InProgress" -foregroundcolor "Yellow"
+            Write-Host  "Pipeline is running...status: InProgress" -ForegroundColor "Yellow"
         }
 
         Start-Sleep -Seconds 15
     }
 
 	$result = Get-AzDataFactoryV2ActivityRun -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -PipelineRunId $runId -RunStartedAfter (Get-Date).AddMinutes(-30) -RunStartedBefore (Get-Date).AddMinutes(30)
-    Write-Host "Activity run details:" -foregroundcolor "Yellow"
+    Write-Host "Activity run details:" -ForegroundColor "Yellow"
     $result
     ```
 
     Here is the output of the sample run:
 
-    ```console
-	Pipeline run details:
+    ```output
+    Pipeline run details:
     ResourceGroupName : <resourceGroupName>
     DataFactoryName   : <dataFactoryName>
     RunId             : 0000000000-00000-0000-0000-000000000000
@@ -548,7 +548,7 @@ This pipeline performs two steps:
 3. You can get the run ID of pipeline "**IterateAndCopySQLTables**", and check the detailed activity run result as the following.
 
     ```powershell
-    Write-Host "Pipeline 'IterateAndCopySQLTables' run result:" -foregroundcolor "Yellow"
+    Write-Host "Pipeline 'IterateAndCopySQLTables' run result:" -ForegroundColor "Yellow"
     ($result | Where-Object {$_.ActivityName -eq "TriggerCopy"}).Output.ToString()
     ```
 
@@ -568,6 +568,7 @@ This pipeline performs two steps:
 3. Connect to your sink Azure Synapse Analytics and confirm that data has been copied from Azure SQL Database properly.
 
 ## Next steps
+
 You performed the following steps in this tutorial: 
 
 > [!div class="checklist"]
@@ -579,5 +580,6 @@ You performed the following steps in this tutorial:
 > * Monitor the pipeline and activity runs.
 
 Advance to the following tutorial to learn about copy data incrementally from a source to a destination:
+
 > [!div class="nextstepaction"]
->[Copy data incrementally](tutorial-incremental-copy-powershell.md)
+> [Copy data incrementally](tutorial-incremental-copy-powershell.md)

articles/data-factory/tutorial-incremental-copy-portal.md

@@ -65,23 +65,24 @@ If you don't have an Azure subscription, create a [free](https://azure.microsoft
 2. Run the following SQL command against your SQL database to create a table named `data_source_table` as the data source store:
 
     ```sql
-	create table data_source_table
-	(
-		PersonID int,
-		Name varchar(255),
-		LastModifytime datetime
-	);
-
-	INSERT INTO data_source_table
-	(PersonID, Name, LastModifytime)
-	VALUES
-	(1, 'aaaa','9/1/2017 12:56:00 AM'),
-	(2, 'bbbb','9/2/2017 5:23:00 AM'),
-	(3, 'cccc','9/3/2017 2:36:00 AM'),
-	(4, 'dddd','9/4/2017 3:21:00 AM'),
-	(5, 'eeee','9/5/2017 8:06:00 AM');
+    create table data_source_table
+    (
+        PersonID int,
+        Name varchar(255),
+        LastModifytime datetime
+    );
+
+    INSERT INTO data_source_table
+        (PersonID, Name, LastModifytime)
+    VALUES
+        (1, 'aaaa','9/1/2017 12:56:00 AM'),
+        (2, 'bbbb','9/2/2017 5:23:00 AM'),
+        (3, 'cccc','9/3/2017 2:36:00 AM'),
+        (4, 'dddd','9/4/2017 3:21:00 AM'),
+        (5, 'eeee','9/5/2017 8:06:00 AM');
     ```
-	In this tutorial, you use LastModifytime as the watermark column. The data in the data source store is shown in the following table:
+
+    In this tutorial, you use LastModifytime as the watermark column. The data in the data source store is shown in the following table:
 
     ```
     PersonID | Name | LastModifytime

articles/data-factory/v1/data-factory-build-your-first-pipeline-using-powershell.md

@@ -107,7 +107,7 @@ In this step, you link your Azure Storage account to your data factory. You use
 
 1. Create a JSON file named StorageLinkedService.json in the C:\ADFGetStarted folder with the following content. Create the folder ADFGetStarted if it does not already exist.
 
-	```json
+    ```json
     {
         "name": "StorageLinkedService",
         "properties": {
@@ -145,7 +145,7 @@ In this step, you link an on-demand HDInsight cluster to your data factory. The
 
 1. Create a JSON file named **HDInsightOnDemandLinkedService**.json in the **C:\ADFGetStarted** folder with the following content.
 
-	```json
+    ```json
     {
         "name": "HDInsightOnDemandLinkedService",
         "properties": {

articles/data-factory/v1/data-factory-build-your-first-pipeline-using-rest-api.md

@@ -291,7 +291,7 @@ In this step, you create an Azure Data Factory named **FirstDataFactoryREST**. A
 
     Confirm that the name of the data factory you specify here (ADFCopyTutorialDF) matches the name specified in the **datafactory.json**.
 
-	```powershell
+    ```powershell
     $cmd = {.\curl.exe -X PUT -H "Authorization: Bearer $accessToken" -H "Content-Type: application/json" --data "@datafactory.json" https://management.azure.com/subscriptions/$subscription_id/resourcegroups/$rg/providers/Microsoft.DataFactory/datafactories/FirstDataFactoryREST?api-version=2015-10-01};
 	```
 2. Run the command by using **Invoke-Command**.
@@ -317,14 +317,16 @@ Note the following points:
 
   * In Azure PowerShell, run the following command to register the Data Factory provider:
 
-	```powershell
-	Register-AzResourceProvider -ProviderNamespace Microsoft.DataFactory
-	```
+    ```powershell
+    Register-AzResourceProvider -ProviderNamespace Microsoft.DataFactory
+    ```
+
+    You can run the following command to confirm that the Data Factory provider is registered:
+
+    ```powershell
+    Get-AzResourceProvider
+    ```
 
-      You can run the following command to confirm that the Data Factory provider is registered:
-	```powershell
-	Get-AzResourceProvider
-	```
   * Login using the Azure subscription into the [Azure portal](https://portal.azure.com) and navigate to a Data Factory blade (or) create a data factory in the Azure portal. This action automatically registers the provider for you.
 
 Before creating a pipeline, you need to create a few Data Factory entities first. You first create linked services to link data stores/computes to your data store, define input and output datasets to represent data in linked data stores.
@@ -337,38 +339,42 @@ In this step, you link your Azure Storage account to your data factory. With thi
 
 1. Assign the command to variable named **cmd**.
 
-	```powershell
-    $cmd = {.\curl.exe -X PUT -H "Authorization: Bearer $accessToken" -H "Content-Type: application/json" --data “@azurestoragelinkedservice.json” https://management.azure.com/subscriptions/$subscription_id/resourcegroups/$rg/providers/Microsoft.DataFactory/datafactories/$adf/linkedservices/AzureStorageLinkedService?api-version=2015-10-01};
-	```
+    ```powershell
+    $cmd = { .\curl.exe -X PUT -H "Authorization: Bearer $accessToken" -H "Content-Type: application/json" --data “@azurestoragelinkedservice.json” https://management.azure.com/subscriptions/$subscription_id/resourcegroups/$rg/providers/Microsoft.DataFactory/datafactories/$adf/linkedservices/AzureStorageLinkedService?api-version=2015-10-01 };
+    ```
+
 2. Run the command by using **Invoke-Command**.
 
-	```powershell
-	$results = Invoke-Command -scriptblock $cmd;
-	```
+    ```powershell
+    $results = Invoke-Command -scriptblock $cmd;
+    ```
+
 3. View the results. If the linked service has been successfully created, you see the JSON for the linked service in the **results**; otherwise, you see an error message.
 
-	```powershell
-	Write-Host $results
-	```
+    ```powershell
+    Write-Host $results
+    ```
 
 ### Create Azure HDInsight linked service
 In this step, you link an on-demand HDInsight cluster to your data factory. The HDInsight cluster is automatically created at runtime and deleted after it is done processing and idle for the specified amount of time. You could use your own HDInsight cluster instead of using an on-demand HDInsight cluster. See [Compute Linked Services](data-factory-compute-linked-services.md) for details.
 
 1. Assign the command to variable named **cmd**.
 
-	```powershell
-	$cmd = {.\curl.exe -X PUT -H "Authorization: Bearer $accessToken" -H "Content-Type: application/json" --data "@hdinsightondemandlinkedservice.json" https://management.azure.com/subscriptions/$subscription_id/resourcegroups/$rg/providers/Microsoft.DataFactory/datafactories/$adf/linkedservices/hdinsightondemandlinkedservice?api-version=2015-10-01};
-	```
+    ```powershell
+    $cmd = {.\curl.exe -X PUT -H "Authorization: Bearer $accessToken" -H "Content-Type: application/json" --data "@hdinsightondemandlinkedservice.json" https://management.azure.com/subscriptions/$subscription_id/resourcegroups/$rg/providers/Microsoft.DataFactory/datafactories/$adf/linkedservices/hdinsightondemandlinkedservice?api-version=2015-10-01};
+    ```
+
 2. Run the command by using **Invoke-Command**.
 
-	```powershell
-	$results = Invoke-Command -scriptblock $cmd;
-	```
+    ```powershell
+    $results = Invoke-Command -scriptblock $cmd;
+    ```
+
 3. View the results. If the linked service has been successfully created, you see the JSON for the linked service in the **results**; otherwise, you see an error message.
 
-	```powershell
-	Write-Host $results
-	```
+    ```powershell
+    Write-Host $results
+    ```
 
 ## Create datasets
 In this step, you create datasets to represent the input and output data for Hive processing. These datasets refer to the **StorageLinkedService** you have created earlier in this tutorial. The linked service points to an Azure Storage account and datasets specify container, folder, file name in the storage that holds input and output data.

articles/data-factory/v1/data-factory-build-your-first-pipeline-using-vs.md

@@ -294,17 +294,17 @@ In this step, you publish the Data Factory entities (linked services, datasets,
 
 	:::image type="content" source="media/data-factory-build-your-first-pipeline-using-vs/publish-new-data-factory.png" alt-text="Publish - New data factory settings":::
 
-   1. select **Create New Data Factory** option.
+   1. Select **Create New Data Factory** option.
    2. Enter a unique **name** for the data factory. For example: **DataFactoryUsingVS09152016**. The name must be globally unique.
    3. Select the right subscription for the **Subscription** field. 
-		> [!IMPORTANT]
-		> If you do not see any subscription, ensure that you logged in using an account that is an admin or co-admin of the subscription.
+      > [!IMPORTANT]
+      > If you do not see any subscription, ensure that you logged in using an account that is an admin or co-admin of the subscription.
    4. Select the **resource group** for the data factory to be created.
    5. Select the **region** for the data factory.
    6. Click **Next** to switch to the **Publish Items** page. (Press **TAB** to move out of the Name field to if the **Next** button is disabled.)
-
       > [!IMPORTANT]
       > If you receive the error **Data factory name “DataFactoryUsingVS” is not available** when publishing, change the name (for example, yournameDataFactoryUsingVS). See [Data Factory - Naming Rules](data-factory-naming-rules.md) topic for naming rules for Data Factory artifacts.   
+
 1. In the **Publish Items** page, ensure that all the Data Factories entities are selected, and click **Next** to switch to the **Summary** page.
 
 	:::image type="content" source="media/data-factory-build-your-first-pipeline-using-vs/publish-items-page.png" alt-text="Publish items page":::     
@@ -316,20 +316,27 @@ In this step, you publish the Data Factory entities (linked services, datasets,
 Important points to note:
 
 - If you receive the error: **This subscription is not registered to use namespace Microsoft.DataFactory**, do one of the following and try publishing again:
-	- In Azure PowerShell, run the following command to register the Data Factory provider.
-		```powershell	
-		Register-AzResourceProvider -ProviderNamespace Microsoft.DataFactory
-        ```
-		You can run the following command to confirm that the Data Factory provider is registered.
-
-		```powershell
-		Get-AzResourceProvider
-        ```
-	- Login using the Azure subscription in to the [Azure portal](https://portal.azure.com) and navigate to a Data Factory blade (or) create a data factory in the Azure portal. This action automatically registers the provider for you.
+
+  - In Azure PowerShell, run the following command to register the Data Factory provider.
+
+    ```powershell
+    Register-AzResourceProvider -ProviderNamespace Microsoft.DataFactory
+    ```
+
+    You can run the following command to confirm that the Data Factory provider is registered.
+
+    ```powershell
+    Get-AzResourceProvider
+    ```
+
+  - Login using the Azure subscription in to the [Azure portal](https://portal.azure.com) and navigate to a Data Factory blade (or) create a data factory in the Azure portal. This action automatically registers the provider for you.
+
 - The name of the data factory may be registered as a DNS name in the future and hence become publicly visible.
+
 - To create Data Factory instances, you need to be an admin or co-admin of the Azure subscription
 
 ### Monitor pipeline
+
 In this step, you monitor the pipeline using Diagram View of the data factory. 
 
 #### Monitor pipeline using Diagram View

articles/data-factory/v1/data-factory-monitor-manage-pipelines.md

@@ -209,19 +209,22 @@ If the activity run fails in a pipeline, the dataset that is produced by the pip
    :::image type="content" source="./media/data-factory-monitor-manage-pipelines/activity-run-details-with-error.png" alt-text="Activity run details blade with error":::     
 
 #### Use PowerShell to debug an error
+
 1. Launch **PowerShell**.
-2. Run the **Get-AzDataFactorySlice** command to see the slices and their statuses. You should see a slice with the status of **Failed**.        
+2. Run the **Get-AzDataFactorySlice** command to see the slices and their statuses. You should see a slice with the status of **Failed**.
 
-	```powershell   
-	Get-AzDataFactorySlice [-ResourceGroupName] <String> [-DataFactoryName] <String> [-DatasetName] <String> [-StartDateTime] <DateTime> [[-EndDateTime] <DateTime> ] [-Profile <AzureProfile> ] [ <CommonParameters>]
-	```   
-   For example:
+    ```powershell
+    Get-AzDataFactorySlice [-ResourceGroupName] <String> [-DataFactoryName] <String> [-DatasetName] <String> [-StartDateTime] <DateTime> [[-EndDateTime] <DateTime> ] [-Profile <AzureProfile> ] [ <CommonParameters>]
+    ```
 
-	```powershell   
-	Get-AzDataFactorySlice -ResourceGroupName ADF -DataFactoryName LogProcessingFactory -DatasetName EnrichedGameEventsTable -StartDateTime 2014-05-04 20:00:00
-	```
+    For example:
+
+    ```powershell
+    Get-AzDataFactorySlice -ResourceGroupName ADF -DataFactoryName LogProcessingFactory -DatasetName EnrichedGameEventsTable -StartDateTime 2014-05-04 20:00:00
+    ```
 
    Replace **StartDateTime** with start time of your pipeline. 
+
 3. Now, run the **Get-AzDataFactoryRun** cmdlet to get details about the activity run for the slice.
 
 	```powershell   
@@ -231,14 +234,15 @@ If the activity run fails in a pipeline, the dataset that is produced by the pip
 
     For example:
 
-	```powershell   
+    ```powershell
     Get-AzDataFactoryRun -ResourceGroupName ADF -DataFactoryName LogProcessingFactory -DatasetName EnrichedGameEventsTable -StartDateTime "5/5/2014 12:00:00 AM"
-	```
+    ```
 
     The value of StartDateTime is the start time for the error/problem slice that you noted from the previous step. The date-time should be enclosed in double quotes.
+
 4. You should see output with details about the error that is similar to the following:
 
-	```   
+    ```output
     Id                      : 841b77c9-d56c-48d1-99a3-8c16c3e77d39
     ResourceGroupName       : ADF
     DataFactoryName         : LogProcessingFactory3
@@ -259,12 +263,13 @@ If the activity run fails in a pipeline, the dataset that is produced by the pip
     ActivityName            : PigEnrichLogs
     PipelineName            : EnrichGameLogsPipeline
     Type                    :
-	```
+    ```
+
 5. You can run the **Save-AzDataFactoryLog** cmdlet with the Id value that you see from the output, and download the log files by using the **-DownloadLogsoption** for the cmdlet.
 
-	```powershell
-	Save-AzDataFactoryLog -ResourceGroupName "ADF" -DataFactoryName "LogProcessingFactory" -Id "841b77c9-d56c-48d1-99a3-8c16c3e77d39" -DownloadLogs -Output "C:\Test"
-	```
+    ```powershell
+    Save-AzDataFactoryLog -ResourceGroupName "ADF" -DataFactoryName "LogProcessingFactory" -Id "841b77c9-d56c-48d1-99a3-8c16c3e77d39" -DownloadLogs -Output "C:\Test"
+    ```
 
 ## Rerun failures in a pipeline