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Copy file name to clipboardExpand all lines: docs/azure-data-studio/quickstart-sql-database.md
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title: "Quickstart: Connect and query an Azure SQL database using Azure Data Studio | Microsoft Docs"
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description: This quickstart shows how to use Azure Data Studio to connect to a SQL database and run a query
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ms.custom: "tools|sos"
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ms.date: "09/24/2018"
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ms.date: "12/03/2018"
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ms.prod: sql
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ms.technology: azure-data-studio
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ms.reviewer: "alayu; sstein"
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---
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# Quickstart: Use [!INCLUDE[name-sos](../includes/name-sos-short.md)] to connect and query Azure SQL database
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This quickstart demonstrates how to use *[!INCLUDE[name-sos](../includes/name-sos-short.md)]* to connect to an Azure SQL database, and then use Transact-SQL (T-SQL) statements to create the *TutorialDB*used in [!INCLUDE[name-sos](../includes/name-sos-short.md)] tutorials.
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This quickstart demonstrates how to use [!INCLUDE[name-sos](../includes/name-sos-short.md)] to connect to an Azure SQL Database server and then use Transact-SQL (T-SQL) statements to create and query the TutorialDB database, which is used in other[!INCLUDE[name-sos](../includes/name-sos-short.md)] tutorials.
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## Prerequisites
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To complete this quickstart, you need [!INCLUDE[name-sos](../includes/name-sos-short.md)], and an Azure SQL server.
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To complete this quickstart, you need [!INCLUDE[name-sos](../includes/name-sos-short.md)], and an Azure SQL Database server.
If you don't already have an Azure SQL server, complete one of the following Azure SQL Database quickstarts (remember the server name, and login credentials!):
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If you don't already have an Azure SQL server, complete one of the following Azure SQL Database quickstarts (remember the fully qualified server name and sign in credentials for steps in the next section):
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-[Create DB - Portal](https://docs.microsoft.com/azure/sql-database/sql-database-get-started-portal)
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-[Create DB - CLI](https://docs.microsoft.com/azure/sql-database/sql-database-get-started-cli)
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Use [!INCLUDE[name-sos](../includes/name-sos-short.md)] to establish a connection to your Azure SQL Database server.
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1. The first time you run [!INCLUDE[name-sos](../includes/name-sos-short.md)] the **Connection** page should open. If you don't see the **Connection** page, click**Add Connection**, or the **New Connection** icon in the **SERVERS** sidebar:
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1. The first time you run [!INCLUDE[name-sos](../includes/name-sos-short.md)] the **Connection** page should open. If you don't see the **Connection** page, select**Add Connection**, or the **New Connection** icon in the **SERVERS** sidebar:
2. This article uses *SQL Login*, but *Windows Authentication* is also supported. Fill in the fields as follows using the server name, user name, and password for *your* Azure SQL server:
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2. This article uses SQL Login, but Windows Authentication is also supported. Fill in the following fields using the server name, user name, and password for your Azure SQL server:
3. If your server doesn't have a firewall rule allowing Azure Data Studio to connect, the **Create new firewall rule** form opens. Complete the form to create a new firewall rule. For details, see [Firewall rules](https://docs.microsoft.com/azure/sql-database/sql-database-firewall-configure).
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3. Select **Connect**.
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4. If your server doesn't have a firewall rule allowing Azure Data Studio to connect, the **Create new firewall rule** form opens. Complete the form to create a new firewall rule. For details, see [Firewall rules](https://docs.microsoft.com/azure/sql-database/sql-database-firewall-configure).
1.Paste the following snippet into the query editor and click **Run**:
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1.Create a `Customers` table.
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> [!NOTE]
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> You can append this to, or overwrite the previous query in the editor. Note that clicking **Run** executes only the query that is selected. If nothing is selected, clicking **Run** executes all queries in the editor.
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Overwrite the previous query in the query editor with this SQL snippet and select **Run**.
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```sql
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-- Create a new table called 'Customers' in schema 'dbo'
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```
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## Insert rows
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## Insert rows into the table
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- Paste the following snippet into the query editor and click**Run**:
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Overwrite the previous query in the query editor with this SQL snippet and select**Run**.
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```sql
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-- Insert rows into table 'Customers'
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## View the result
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1. Paste the following snippet into the query editor and click**Run**:
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Overwrite the previous query in the query editor with this SQL snippet and select**Run**.
Other articles in this collection build upon this quickstart. If you plan to continue on to work with subsequent quickstarts, do not clean up the resources created in this quickstart. If you do not plan to continue, use the following steps to delete resources created by this quickstart in the Azure portal.
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Clean up resources by deleting the resource groups you no longer need. For details, see [Clean up resources](https://docs.microsoft.com/azure/sql-database/sql-database-get-started-portal#clean-up-resources).
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Later quickstart articles build upon the resources created here. If you plan to work through these articles, be sure not to delete these resources. Otherwise, in the Azure portal, you can delete the resources you no longer need. For details, see [Clean up resources](https://docs.microsoft.com/azure/sql-database/sql-database-get-started-portal#clean-up-resources).
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## Next steps
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Now that you've successfully connected to an Azure SQL database and ran a query, try out the [Code editor tutorial](tutorial-sql-editor.md).
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Now that you have successfully connected to an Azure SQL database and run a query, try out the [Code editor tutorial](tutorial-sql-editor.md).
Copy file name to clipboardExpand all lines: docs/big-data-cluster/quickstart-big-data-cluster-deploy.md
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# Quickstart: Deploy SQL Server big data cluster on Azure Kubernetes Service (AKS)
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Install SQL Server big data cluster on AKS in a default configuration suitable for dev/test environments. In addition to a SQL Master instance, the cluster includes one compute pool instance, one data pool instance, and two storage pool instances. Data is persisted using Kubernetes persistent volumes that use AKS default storage classes. To further customize your configuration, see the environment variables at [deployment guidance](deployment-guidance.md).
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In this quickstart, you will deploy a SQL Server 2019 big data cluster (preview) on AKS in a default configuration suitable for dev/test environments.
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> [!NOTE]
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> AKS is just one location to host Kubernetes. Big data clusters can be deployed to Kubernetes regardless of the underlying infrastructure. For more information, see [How to deploy SQL Server big data clusters on Kubernetes](deployment-guidance.md).
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In addition to a SQL Master instance, the cluster includes one compute pool instance, one data pool instance, and two storage pool instances. Data is persisted using Kubernetes persistent volumes that use AKS default storage classes. To further customize your configuration, see the environment variables in the [deployment guidance](deployment-guidance.md).
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If you would prefer to run a script to create your AKS cluster and install a big data cluster at the same time, see [Deploy a SQL Server big data cluster on Azure Kubernetes Service (AKS)](https://github.com/Microsoft/sql-server-samples/tree/master/samples/features/sql-big-data-cluster/deployment/aks).
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[!INCLUDE [Limited public preview note](../includes/big-data-cluster-preview-note.md)]
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Look for the **External-IP** value that is assigned to the services. Connect to the SQL Server master instance using the IP address for the `service-master-pool-lb` at port 31433 (Ex: **\<ip-address\>,31433**) and to the SQL Server big data cluster endpoint using the external-IP for the `service-security-lb` service. That big data cluster end point is where you can interact with HDFS and submit Spark jobs through Knox.
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## Sample deployment script
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For a sample python script that deploys both AKS and SQL Server big data cluster, see [Deploy a SQL Server big data cluster on Azure Kubernetes Service (AKS)](https://github.com/Microsoft/sql-server-samples/tree/master/samples/features/sql-big-data-cluster/deployment/aks).
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## Next steps
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Now that the SQL Server big data cluster is deployed, try out some of the new capabilities:
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