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docs/big-data-cluster/big-data-cluster-overview.md

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Management and monitoring are provided through a combination of command-line tools, APIs, portals, and dynamic management views.
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You can use [Azure Data Studio](../azure-data-studio/what-is-azure-data-studio.md) to perform a variety of tasks on the big data cluster:
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You can use [Azure Data Studio](/azure-data-studio/what-is-azure-data-studio) to perform a variety of tasks on the big data cluster:
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- Built-in snippets for common management tasks.
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- Ability to browse HDFS, upload files, preview files, and create directories.

docs/big-data-cluster/cluster-monitor-ads.md

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## <a id="datastudio"></a> Use Azure Data Studio
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After downloading the latest **insiders build** of [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md), you can view service endpoints and the status of a big data cluster with the SQL Server big data cluster dashboard. Some of the features below are only first available in the insiders build of Azure Data Studio.
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After downloading the latest **insiders build** of [Azure Data Studio](/azure-data-studio/download-azure-data-studio), you can view service endpoints and the status of a big data cluster with the SQL Server big data cluster dashboard. Some of the features below are only first available in the insiders build of Azure Data Studio.
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1. First, create a connection to your big data cluster in Azure Data Studio. For more information, see [Connect to a SQL Server big data cluster with Azure Data Studio](connect-to-big-data-cluster.md).
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docs/big-data-cluster/data-virtualization-csv.md

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## Prerequisites
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- [A deployed big data cluster](deployment-guidance.md)
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- [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md)
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- [Azure Data Studio](/azure-data-studio/download-azure-data-studio)
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## Select or upload a CSV file for data virtualization
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docs/big-data-cluster/deploy-big-data-tools.md

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| `python` | Yes | Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Many parts of big data clusters for SQL Server use python. | [Install python](#python)|
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| [!INCLUDE [azure-data-cli-azdata](../includes/azure-data-cli-azdata.md)] | Yes | Command-line tool for installing and managing a big data cluster. | [Install](../azdata/install/deploy-install-azdata.md) |
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| `kubectl`<sup>1</sup> | Yes | Command-line tool for monitoring the underlying Kubernetes cluster ([More info](https://kubernetes.io/docs/tasks/tools/install-kubectl/)). | [Windows](https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-with-powershell-from-psgallery) \| [Linux](https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-using-native-package-management) |
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| **Azure Data Studio** | Yes | Cross-platform graphical tool for querying SQL Server. | [Install](../azure-data-studio/download-azure-data-studio.md) |
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| **Data Virtualization extension** | Yes | Extension for Azure Data Studio that provides a Data Virtualization wizard. | [Install](../azure-data-studio/extensions/data-virtualization-extension.md) |
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| **Azure Data Studio** | Yes | Cross-platform graphical tool for querying SQL Server. | [Install](/azure-data-studio/download-azure-data-studio) |
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| **Data Virtualization extension** | Yes | Extension for Azure Data Studio that provides a Data Virtualization wizard. | [Install](/azure-data-studio/extensions/data-virtualization-extension) |
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| **Azure CLI**<sup>2</sup> | For AKS | Modern command-line interface for managing Azure services. Used with AKS big data cluster deployments ([More info](/cli/azure/)). | [Install](/cli/azure/install-azure-cli) |
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| **mssql-cli** | Optional | Modern command-line interface for querying SQL Server ([More info](../tools/mssql-cli.md)). | [Windows](https://github.com/dbcli/mssql-cli/blob/master/doc/installation/windows.md) \| [Linux](https://github.com/dbcli/mssql-cli/blob/master/doc/installation/linux.md) |
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| **sqlcmd** | For some scripts | Legacy command-line tool for querying SQL Server ([More info](../tools/sqlcmd/sqlcmd-utility.md)). You might need to install the Microsoft ODBC Driver 11 for SQL Server before installing the SQLCMD package. | [Windows](https://www.microsoft.com/download/details.aspx?id=36433) \| [Linux](../linux/sql-server-linux-setup-tools.md) |
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Azure Data Studio provides capabilities and features specifically for SQL Server Big Data Clusters.
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[Get the latest Azure Data Studio](../azure-data-studio/download-azure-data-studio.md).
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[Get the latest Azure Data Studio](/azure-data-studio/download-azure-data-studio).
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For details about the latest release, see the [release notes](./release-notes-big-data-cluster.md).
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docs/big-data-cluster/deployment-guidance.md

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- [!INCLUDE [azure-data-cli-azdata](../includes/azure-data-cli-azdata.md)]
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- `kubectl`
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- Azure Data Studio
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- [Data Virtualization extension](../azure-data-studio/extensions/data-virtualization-extension.md) for Azure Data Studio
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- [Data Virtualization extension](/azure-data-studio/extensions/data-virtualization-extension) for Azure Data Studio
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- [Azure CLI](/cli/azure/install-azure-cli), if deploying to AKS
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docs/big-data-cluster/known-issues.md

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- **Issue and customer effect**: For new big data clusters deployed using SQL Server Big Data Clusters CU5, gateway username isn't `root`. If the application used to connect to gateway endpoint is using the wrong credentials, you'll see an authentication error. This change is a result of running applications within the big data cluster as non-root user (a new default behavior starting with SQL Server Big Data Clusters CU5 release, when you deploy a new big data cluster using CU5, the username for the gateway endpoint is based on the value passed through `AZDATA_USERNAME` environment variable. It is the same username used for the controller and SQL Server endpoints. This only affects new deployments. Existing big data clusters deployed with any of the previous releases continue to use `root`. There is no effect to credentials when the cluster is deployed to use Active Directory authentication.
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- **Workaround**: Azure Data Studio handles the credentials change transparently for the connection made to gateway to enable HDFS browsing experience in the Object Explorer. You must install [latest Azure Data Studio release](../azure-data-studio/download-azure-data-studio.md) that includes the necessary changes that address this use case.
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- **Workaround**: Azure Data Studio handles the credentials change transparently for the connection made to gateway to enable HDFS browsing experience in the Object Explorer. You must install [latest Azure Data Studio release](/azure-data-studio/download-azure-data-studio) that includes the necessary changes that address this use case.
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For other scenarios where you must provide credentials for accessing service through the gateway (for example, logging in with [!INCLUDE [azure-data-cli-azdata](../includes/azure-data-cli-azdata.md)], accessing web dashboards for Spark), you must ensure the correct credentials are used. If you're targeting an existing cluster deployed before CU5 you'll continue using the `root` username to connect to gateway, even after upgrading the cluster to CU5. If you deploy a new cluster using CU5 build, sign in by providing the username corresponding to `AZDATA_USERNAME` environment variable.
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### Pods and nodes metrics not being collected

docs/big-data-cluster/manage-with-controller-dashboard.md

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The following prerequisites are required to launch the notebook:
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* Latest version of [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md)
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* [[!INCLUDE[sql-server-2019](../includes/sssql19-md.md)] extension installed in Azure Data Studio](../azure-data-studio/data-virtualization-extension.md)
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* Latest version of [Azure Data Studio](/azure-data-studio/download-azure-data-studio)
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* [[!INCLUDE[sql-server-2019](../includes/sssql19-md.md)] extension installed in Azure Data Studio](/azure-data-studio/extensions/data-virtualization-extension)
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In addition to above, SQL Server 2019 Big Data Cluster also requires:
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docs/big-data-cluster/non-root-containers.md

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## Use the latest Azure Data Studio
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Azure Data Studio handles the credentials change transparently for the connection made through gateway to enable HDFS browsing experience in the Object Explorer or submitting Spark jobs through notebooks. Install the [latest Azure Data Studio insiders build](../azure-data-studio/download-azure-data-studio.md#download-the-insiders-build-of-azure-data-studio). This build includes the necessary changes for this use case.
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Azure Data Studio handles the credentials change transparently for the connection made through gateway to enable HDFS browsing experience in the Object Explorer or submitting Spark jobs through notebooks. Install the [latest Azure Data Studio insiders build](/azure-data-studio/download-azure-data-studio#download-the-insiders-build-of-azure-data-studio). This build includes the necessary changes for this use case.
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For other scenarios where you must provide credentials for accessing the service through the gateway (e.g. logging in with [!INCLUDE [azure-data-cli-azdata](../includes/azure-data-cli-azdata.md)], accessing web dashboards for Spark), ensure the correct credentials are used. If you are targeting an existing cluster deployed before CU5 you will continue using `root` username to connect to gateway, even after upgrading the cluster to CU5. If you deploy a new cluster using CU5 build, you will login by providing the username corresponding to `AZDATA_USERNAME` environment variable.
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docs/big-data-cluster/notebooks-deploy.md

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SQL Server provides an extension for Azure Data Studio that includes deployment notebooks. A deployment notebook includes documentation and code that you can use in Azure Data Studio to create a SQL Server big data cluster.
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Implemented initially as an open-source project, [notebooks](../azure-data-studio/notebooks/notebooks-guidance.md) have been implemented into [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md). You can use markdown for text in the text cells and one of the available kernels to write code in the code cells.
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Implemented initially as an open-source project, [notebooks](/azure-data-studio/notebooks/notebooks-guidance) have been implemented into [Azure Data Studio](/azure-data-studio/download-azure-data-studio). You can use markdown for text in the text cells and one of the available kernels to write code in the code cells.
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You can use notebooks to deploy [!INCLUDE[big-data-clusters-nover](../includes/ssbigdataclusters-ss-nover.md)].
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docs/big-data-cluster/notebooks-manage-bdc.md

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[!INCLUDE[sql-server-2019](../includes/sssql19-md.md)] provides an extension for Azure Data Studio that includes notebooks. A notebook provides documentation and code that you can use in Azure Data Studio to manage SQL Server 2019 Big Data Clusters.
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Originally implemented as an open-source project, [notebooks](../azure-data-studio/notebooks/notebooks-guidance.md) have been incorporated into [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md). You can use markdown for text in the text cells and one of the available kernels to write code in the code cells.
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Originally implemented as an open-source project, [notebooks](/azure-data-studio/notebooks/notebooks-guidance) have been incorporated into [Azure Data Studio](/azure-data-studio/download-azure-data-studio). You can use markdown for text in the text cells and one of the available kernels to write code in the code cells.
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You can use notebooks to deploy big data clusters for [!INCLUDE[sql-server-2019](../includes/sssql19-md.md)].
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You need these prerequisites to open a notebook:
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* The latest version of [Azure Data Studio](../azure-data-studio/download-azure-data-studio.md)
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* The latest version of [Azure Data Studio](/azure-data-studio/download-azure-data-studio)
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* The [!INCLUDE[sql-server-2019](../includes/sssql19-md.md)] extension, installed in Azure Data Studio
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In addition to those prerequisites, to deploy SQL Server 2019 Big Data Clusters, you also need:
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## Next steps
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For more information about notebooks in Azure Data Studio, see [How to use notebooks with SQL Server](../azure-data-studio/notebooks/notebooks-guidance.md).
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For more information about notebooks in Azure Data Studio, see [How to use notebooks with SQL Server](/azure-data-studio/notebooks/notebooks-guidance).
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For the location of big data cluster administration notebooks, see [Where to find SQL Server Big Data Clusters administration notebooks](view-cluster-status.md#where-to-find--administration-notebooks).

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