update author and date

Author: alex-lin-msft

articles/stream-analytics/copy-job.md

@@ -1,34 +1,32 @@
 ---
 title: Copy, back up and move your Azure Stream Analytics jobs between regions
 description: This article describes how to move, copy, and back up an Azure Stream Analytics job.
-author: su-jie
-ms.author: sujie
-
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
 ms.custom: subject-moving-resources
-ms.date: 09/11/2019
+ms.date: 12/27/2012
 #Customer intent: As an Azure Stream Analytics job developer or admin, I want export my job so that I can reuse, move between Azure regions, or back up.
 ---
 
 # Copy, back up and move your Azure Stream Analytics jobs between regions
 
-When you want to move, copy or back up your deployed Azure Stream Analytics jobs, you can use the job exporting function in Stream Analytics extension for Visual Studio Code or Visual Studio to achieve. It will help you to export your job's definition to local, then you can backup it there or resubmit it to another region.
+If you want to move, copy or back up your Azure Stream Analytics jobs in Azure, the Azure Stream Analytics extension for Visual Studio Code allows you to export an existing job in the cloud to your local computer. All the configurations of your Stream Analytics job will be saved locally and you can resubmit it to another region.
 
 > [!NOTE] 
-> * We strongly recommend using [**Stream Analytics tools for Visual Studio Code**](./quick-create-visual-studio-code.md) for best local development experience. There are known feature gaps in Stream Analytics tools for Visual Studio 2019 (version 2.6.3000.0) and it won't be improved going forward. 
 > * Copying a job to another region does not copy the last output time. Therefore, you cannot use [**When last stopped**](./start-job.md#start-options) option when starting the copied job.
 
 ## Before you begin
 * If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/).
 
 * Sign in to the [Azure portal](https://portal.azure.com/).
 
-* Install [Azure Stream Analytics extension for Visual Studio Code](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension) or [Azure Stream Analytics tools for Visual Studio](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension).  
+* Install [Azure Stream Analytics extension for Visual Studio Code](quick-create-visual-studio-code.md#install-the-azure-stream-analytics-tools-extension).
 
 ## Visual Studio Code
 
-1. Click the **Azure** icon on the Visual Studio Code Activity Bar and then expand **Stream Analytics** node. Your jobs should appear under your subscriptions.
+1. Select the **Azure** icon on the Visual Studio Code Activity Bar and then expand **Stream Analytics** node. Your jobs should appear under your subscriptions.
 
    ![Open Stream Analytics Explorer](./media/vscode-explore-jobs/open-explorer.png)
 
@@ -42,13 +40,6 @@ When you want to move, copy or back up your deployed Azure Stream Analytics jobs
 
     ![Publish to Azure in Visual Studio Code](./media/quick-create-visual-studio-code/submit-job.png)
 
-## Visual Studio
-
-1. Follow the [export a deployed Azure Stream Analytics job to a project instructions](./stream-analytics-vs-tools.md#export-jobs-to-a-project).
-
-2. Open the \*.asaql file in the Query Editor, select **Submit To Azure** in the script editor and follow the instructions to publish the job to another region or backup using a new name.
-
 ## Next steps
 
-* [Quickstart: Create a Stream Analytics job by using Visual Studio Code](quick-create-visual-studio-code.md)
-* [Quickstart: Create a Stream Analytics job by using Visual Studio](stream-analytics-quick-create-vs.md)
+* [Quickstart: Create a Stream Analytics job by using Visual Studio Code](quick-create-visual-studio-code.md)

articles/stream-analytics/job-config-json.md

@@ -1,11 +1,11 @@
 ---
 title: Azure Stream Analytics JobConfig.json fields
 description: This article lists the supported fields for the Azure Stream Analytics JobConfig.json file used to create jobs in Visual Studio Code.
-author: su-jie
-ms.author: sujie
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
-ms.date: 02/14/2020
+ms.date: 12/27/2022
 ---
 
 # Azure Stream Analytics JobConfig.json fields

articles/stream-analytics/visual-studio-code-custom-deserializer.md

@@ -1,25 +1,23 @@
 ---
 title: Tutorial - Create custom .NET deserializers for Azure Stream Analytics cloud jobs using Visual Studio Code
 description: This tutorial demonstrates how to create a custom .NET deserializer for an Azure Stream Analytics cloud job using Visual Studio Code.
-author: su-jie
-ms.author: sujie
+author: alexlzx
+ms.author: zhenxilin
 ms.service: stream-analytics
 ms.topic: how-to
-ms.date: 12/22/2020
+ms.date: 12/27/2022
 ---
 
 
 # Tutorial: Custom .NET deserializers for Azure Stream Analytics in Visual Studio Code
 
-Azure Stream Analytics has [built-in support for three data formats](stream-analytics-parsing-json.md): JSON, CSV, and Avro. With custom .NET deserializers, you can read data from other formats such as [Protocol Buffer](https://developers.google.com/protocol-buffers/), [Bond](https://github.com/Microsoft/bond) and other user defined formats for cloud jobs.
+Azure Stream Analytics has built-in support for three data formats: JSON, CSV, and Avro as shown in this [doc](stream-analytics-parsing-json.md). With custom .NET deserializers, you can process data in other formats such as [Protocol Buffer](https://developers.google.com/protocol-buffers/), [Bond](https://github.com/Microsoft/bond) and other user defined formats for cloud jobs. This tutorial demonstrates how to create, test, and debug a custom .NET deserializer for an Azure Stream Analytics job using Visual Studio Code.
 
-This tutorial demonstrates how to create, test, and debug a custom .NET deserializer for an Azure Stream Analytics cloud job using Visual Studio Code. To learn how to create .NET deserializers in Visual Studio, see [Create .NET deserializers for Azure Stream Analytics jobs in Visual Studio](custom-deserializer.md).
-
-In this tutorial, you learn how to:
+You'll learn how to:
 
 > [!div class="checklist"]
 > * Create a custom deserializer for protocol buffer.
-> * Create an Azure Stream Analytics job in Visual Studio.
+> * Create an Azure Stream Analytics job in Visual Studio Code.
 > * Configure your Stream Analytics job to use the custom deserializer.
 > * Run your Stream Analytics job locally to test and debug the custom deserializer.
 
@@ -92,17 +90,17 @@ Open Visual Studio Code and select **Ctrl+Shift+P** to open the command palette.
 
    |Setting|Suggested Value|
    |-------|---------------|
-   |Select local file path|Click CodeLens to select < The file path for the downloaded sample protobuf input file>|
+   |Select local file path|Select CodeLens to select < The file path for the downloaded sample protobuf input file>|
 
 ## Execute the Stream Analytics job
 
 1. Open **ProtobufCloudDeserializer.asaql** and select **Run Locally** from CodeLens then choose **Use Local Input** from the dropdown list.
 
-2. Observe the results in **Results** tab in job diagram view on the right. You can also click the steps in the job diagram to view intermediate result. More details please see [Debug locally using job diagram](debug-locally-using-job-diagram-vs-code.md).
+2. Under the **Results** tab in the Job diagram, you can view the output results. You can also click on the steps in the job diagram to view intermediate result. For more details, please see [Debug locally using job diagram](debug-locally-using-job-diagram-vs-code.md).
 
    :::image type="content" source="./media/custom-deserializer/check-local-run-result-vscode.png" alt-text="Check local run result.":::
 
-You have successfully implemented a custom deserializer for your Stream Analytics job! In this tutorial, you tested the custom deserializer locally with local input data. You can also test it [using live data input in the cloud](visual-studio-code-local-run-live-input.md). For running the job in the cloud, you would properly configure the input and output. Then submit the job to Azure from Visual Studio Code to run your job in the cloud using the custom deserializer you just implemented.
+You've successfully implemented a custom deserializer for your Stream Analytics job! In this tutorial, you tested the custom deserializer locally with local input data. You can also test it [using live data input in the cloud](visual-studio-code-local-run-live-input.md). For running the job in the cloud, you would properly configure the input and output. Then submit the job to Azure from Visual Studio Code to run your job in the cloud using the custom deserializer you implemented.
 
 ## Debug your deserializer
 
@@ -125,7 +123,7 @@ You can debug your .NET deserializer locally the same way you debug standard .NE
 
 ## Clean up resources
 
-When no longer needed, delete the resource group, the streaming job, and all related resources. Deleting the job avoids billing the streaming units consumed by the job. If you're planning to use the job in future, you can stop it and restart it later when you need. If you are not going to continue to use this job, delete all resources created by this tutorial by using the following steps:
+When no longer needed, delete the resource group, the streaming job, and all related resources. Deleting the job avoids billing the streaming units consumed by the job. If you're planning to use the job in future, you can stop it and restart it later when you need. If you aren't going to continue to use this job, delete all resources created by this tutorial by using the following steps:
 
 1. From the left-hand menu in the Azure portal, select **Resource groups** and then select the name of the resource you created.  
 

articles/stream-analytics/visual-studio-code-explore-jobs.md

@@ -2,15 +2,15 @@
 title: Explore Azure Stream Analytics jobs in Visual Studio Code
 description: This article shows you how to export an Azure Stream Analytics job to a local project, list jobs and view job entities.
 ms.service: stream-analytics
-author: su-jie
-ms.author: sujie
-ms.date: 07/21/2021
+author: alexlzx
+ms.author: zhenxilin
+ms.date: 12/27/2022
 ms.topic: how-to
 ---
 
-# Explore Azure Stream Analytics with Visual Studio Code (Preview)
+# Explore Azure Stream Analytics with Visual Studio Code
 
-The Azure Stream Analytics for Visual Studio Code extension gives developers a lightweight experience for managing their Stream Analytics jobs. It can be used on Windows, Mac and Linux. With the Azure Stream Analytics extension, you can:
+The Azure Stream Analytics extension for Visual Studio Code gives you a seamless experience for managing Stream Analytics jobs in the cloud. It can be used on Windows, Mac and Linux. With the Azure Stream Analytics extension, you can:
 
 - [Create](quick-create-visual-studio-code.md), start, and stop jobs
 - Export existing jobs to a local project
@@ -83,4 +83,4 @@ You can view your job’s diagnostic logs and activity logs for troubleshooting.
 
 ## Next steps
 
-* [Create an Azure Stream Analytics cloud job in Visual Studio Code (Preview)](quick-create-visual-studio-code.md)
+* [Create an Azure Stream Analytics cloud job in Visual Studio Code](quick-create-visual-studio-code.md)

articles/stream-analytics/vs-code-intellisense.md

@@ -2,9 +2,9 @@
 title: IntelliSense in Azure Stream Analytics tools for Visual Studio Code
 description: This article describes how to use IntelliSense features in Azure Stream Analytics tools for Visual Studio Code.
 ms.service: stream-analytics
-author: su-jie
-ms.author: sujie
-ms.date: 4/11/2020
+author: alexlzx
+ms.author: zhenxilin
+ms.date: 12/27/2022
 ms.topic: how-to
 ---
 # IntelliSense in Azure Stream Analytics tools for Visual Studio Code