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* Add `python.exe` to the PATH environment variable
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4. Install [Microsoft Visual C++ 14.0 and build tools for Visual Studio](https://visualstudio.microsoft.com/downloads/) - You can find the download under "Tools For Visual Studio 2019".
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4. Install [Microsoft Visual C++ 14.0 and build tools for Visual Studio](https://visualstudio.microsoft.com/downloads/). You can find the download under "Tools For Visual Studio 2019".
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5. Install [Microsoft ODBC Driver 17 for SQL Server](https://www.microsoft.com/download/details.aspx?id=56567).
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6. Install [Azure Data Studio](/sql/azure-data-studio/download-azure-data-studio/)
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7. Open Azure Data Studio and configure Python for notebooks. For details, see [Configure Python for Notebooks](/sql/azure-data-studio/sql-notebooks#configure-python-for-notebooks).This step can take several minutes.
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8. Install the latest version of [Azure CLI](https://github.com/Azure/azure-powershell/releases/tag/v3.5.0-February2020).
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## Deploy Azure resources using PowerShell Script
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Deploy the Azure resources required by this Azure SQL Edge tutorial. These can be deployed either by using a PowerShell script below or through the Azure portal. This tutorial uses a PowerShell script.
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Deploy the Azure resources required by this Azure SQL Edge tutorial. These can be deployed either by using a PowerShell script or through the Azure portal. This tutorial uses a PowerShell script.
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1. Import the modules needed to run the PowerShell script in this tutorial.
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@@ -148,127 +148,127 @@ Deploy the Azure resources required by this Azure SQL Edge tutorial. These can b
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10. Push the ARM/AMD docker images to the container registry.
Copy file name to clipboardExpand all lines: articles/azure-sql-edge/set-up-iot-edge-modules.md
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@@ -18,7 +18,9 @@ In part two of this three-part tutorial for predicting iron ore impurities in Az
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- Azure SQL Edge
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- A data generator module
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Before proceeding, create an Azure Stream Analytics module that will be used in the tutorial. To learn more about using streaming jobs with SQL Edge, see [Using streaming jobs with SQL Database Edge](https://docs.microsoft.com/azure/sql-database-edge/stream-analytics#using-streaming-jobs-with-sql-database-edge).
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## Create Azure Stream Analytics module
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Create an Azure Stream Analytics module that will be used in this tutorial. To learn more about using streaming jobs with SQL Edge, see [Using streaming jobs with SQL Database Edge](https://docs.microsoft.com/azure/sql-database-edge/stream-analytics#using-streaming-jobs-with-sql-database-edge).
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Once the Azure Stream Analytics job is created with the hosting environment set as Edge, set up the inputs and outputs for the tutorial.
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3. Navigate to the **Query** section and set up the query as follows:
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`SELECT * INTO `*name_of_your_output_stream*` FROM `*name_of_your_input_stream*
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`SELECT * INTO <name_of_your_output_stream> FROM <name_of_your_input_stream>`
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4. Under **Configure**, select **Publish**, and then select the **Publish** button. Save the SAS URI for use with the SQL Database Edge module.
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@@ -100,7 +102,7 @@ Now, specify the container credentials in the IoT Edge module.
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