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

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Use SQL Server Big Data Clusters to:
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- [Deploy scalable clusters](../big-data-cluster/deploy-get-started.md) of SQL Server, Spark, and HDFS containers running on Kubernetes.
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- [Deploy scalable clusters](./deploy-get-started.md) of SQL Server, Spark, and HDFS containers running on Kubernetes.
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- Read, write, and process big data from Transact-SQL or Spark.
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- Easily combine and analyze high-value relational data with high-volume big data.
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- Query external data sources.
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- Store big data in HDFS managed by SQL Server.
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- Query data from multiple external data sources through the cluster.
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- Use the data for AI, machine learning, and other analysis tasks.
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- [Deploy and run applications](../big-data-cluster/concept-application-deployment.md) in [!INCLUDE[big-data-clusters](../includes/ssbigdataclusters-nover.md)].
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- [Deploy and run applications](./concept-application-deployment.md) in [!INCLUDE[big-data-clusters](../includes/ssbigdataclusters-nover.md)].
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- Virtualize data with [PolyBase](../relational-databases/polybase/polybase-guide.md). Query data from external SQL Server, Oracle, Teradata, MongoDB, and ODBC data sources with external tables.
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- Provide high availability for the SQL Server master instance and all databases by using Always On availability group technology.
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## Next steps
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For more information about deploying SQL Server Big Data Clusters, see [Get started with SQL Server Big Data Clusters](deploy-get-started.md).
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For more information about deploying SQL Server Big Data Clusters, see [Get started with SQL Server Big Data Clusters](deploy-get-started.md).

‎docs/big-data-cluster/concept-application-deployment.md‎

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SQL Server 2019 CU5 enables support for Big Data Clusters deployment on Red Hat OpenShift as well as an updated security model for BDC so privileged containers no longer required. In addition to non-privileged, containers are running as non-root user by default for all new deployments using SQL Server 2019 CU5.
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At the time of the CU5 release, the setup step of the applications deployed with [app deploy](concept-application-deployment.md) interfaces will still run as *root* user. This is required since during setup additional packages that application will use are installed. Other user code deployed as part of the application will run as low privilege user.
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At the time of the CU5 release, the setup step of the applications deployed with [app deploy]() interfaces will still run as *root* user. This is required since during setup additional packages that application will use are installed. Other user code deployed as part of the application will run as low privilege user.
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In addition, **CAP_AUDIT_WRITE** capability is an optional capability necessary to allow scheduling SSIS applications using cron jobs. When the application’s yaml specification file specifies a schedule, the application will be triggered via a cron job, which requires the additional capability. Alternatively, the application can be triggered on demand with *azdata app run* through a web service call, which does not require the CAP_AUDIT_WRITE capability.
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To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following overview:
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- [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
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- [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)

‎docs/big-data-cluster/concept-controller.md‎

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Authentication to the controller service endpoint is either using an Active Directory identity or based on username and password. These credentials are provisioned at cluster bootstrap time using the input for environment variables `AZDATA_USERNAME` and `AZDATA_PASSWORD`.
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> [!NOTE]
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> You must provide a password that is in compliance with [SQL Server password complexity requirements](https://docs.microsoft.com/sql/relational-databases/security/password-policy?view=sql-server-2017).
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> You must provide a password that is in compliance with [SQL Server password complexity requirements](../relational-databases/security/password-policy.md?view=sql-server-2017).
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## Next steps
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To learn more about the [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)], see the following resources:
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- [What are [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ver15.md)]?](big-data-cluster-overview.md)
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- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)
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- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/microsoft/sqlworkshops-bdc)

‎docs/big-data-cluster/concept-data-persistence.md‎

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Here are some important aspects to consider when you're planning storage configuration for your big data cluster:
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- For a successful big data cluster deployment, make sure you have the required number of persistent volumes available. If you're deploying on an Azure Kubernetes Service (AKS) cluster and you're using a built-in storage class (`default` or `managed-premium`), this class supports dynamic provisioning for the persistent volumes. Therefore, you don't have to pre-create the persistent volumes, but you must make sure the available worker nodes in the AKS cluster can attach as many disks as the number of persistent volumes that are required for the deployment. Depending on the [VM size](https://docs.microsoft.com/azure/virtual-machines/linux/sizes) specified for the worker nodes, each node can attach a certain number of disks. For a default size cluster (with no high availability), a minimum of 24 disks are required. If you're enabling high availability or scaling up any pool, make sure you have at least two persisted volumes per each additional replica, regardless of the resource you're scaling up.
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- For a successful big data cluster deployment, make sure you have the required number of persistent volumes available. If you're deploying on an Azure Kubernetes Service (AKS) cluster and you're using a built-in storage class (`default` or `managed-premium`), this class supports dynamic provisioning for the persistent volumes. Therefore, you don't have to pre-create the persistent volumes, but you must make sure the available worker nodes in the AKS cluster can attach as many disks as the number of persistent volumes that are required for the deployment. Depending on the [VM size](/azure/virtual-machines/linux/sizes) specified for the worker nodes, each node can attach a certain number of disks. For a default size cluster (with no high availability), a minimum of 24 disks are required. If you're enabling high availability or scaling up any pool, make sure you have at least two persisted volumes per each additional replica, regardless of the resource you're scaling up.
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- If the storage provisioner for the storage class you're providing in the configuration doesn't support dynamic provisioning, you must pre-create the persisted volumes. For example, the `local-storage` provisioner doesn't enable dynamic provisioning. See this [sample script](https://github.com/microsoft/sql-server-samples/tree/master/samples/features/sql-big-data-cluster/deployment/kubeadm/ubuntu) for guidance on how to proceed in a Kubernetes cluster deployed with `kubeadm`.
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- For complete documentation about volumes in Kubernetes, see the [Kubernetes documentation on volumes](https://kubernetes.io/docs/concepts/storage/volumes/).
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- For more information about deploying a SQL Server big data cluster, see [How to deploy SQL Server big data cluster on Kubernetes](deployment-guidance.md).
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- For more information about deploying a SQL Server big data cluster, see [How to deploy SQL Server big data cluster on Kubernetes](deployment-guidance.md).

‎docs/big-data-cluster/deploy-active-directory.md‎

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>[!NOTE]
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>Active Directory requires the account names to be limited to 20 characters. BDC cluster needs to use 8 of the characters for distinguishing pods and StatefulSets. This leaves us 12 characters as a limit for the account prefix
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[Check AD group scope](https://docs.microsoft.com/powershell/module/activedirectory/get-adgroup?view=winserver2012-ps&viewFallbackFrom=winserver2012r2-ps), to determine if it is DomainLocal.
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[Check AD group scope](/powershell/module/activedirectory/get-adgroup?view=winserver2012-ps&viewFallbackFrom=winserver2012r2-ps), to determine if it is DomainLocal.
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If you have not already initialized the deployment configuration file, you can run this command to get a copy of the configuration. Examples below use the `kubeadm-prod` profile, same applies to `openshift-prod`.
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- Before SQL Server 2019 CU5 release, only one BDC per domain (Active Directory) is allowed. Enabling multiple BDCs per domain is available starting with CU5 release.
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- None of the AD groups specified in security configurations can be DomainLocal scoped. You can check the scope of an AD group by following [these instructions](https://docs.microsoft.com/powershell/module/activedirectory/get-adgroup?view=winserver2012-ps&viewFallbackFrom=winserver2012r2-ps).
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- None of the AD groups specified in security configurations can be DomainLocal scoped. You can check the scope of an AD group by following [these instructions](/powershell/module/activedirectory/get-adgroup?view=winserver2012-ps&viewFallbackFrom=winserver2012r2-ps).
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- AD account that can be used to login into BDC are allowed from the same domain that was configured for BDC. Enabling logins from other trusted domain is not supported.
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## Next steps
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[Troubleshoot SQL Server Big Data Cluster Active Directory integration](troubleshoot-active-directory.md)
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[Concept: deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] in Active Directory mode](active-directory-deployment-background.md)
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[Concept: deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] in Active Directory mode](active-directory-deployment-background.md)

‎docs/big-data-cluster/deploy-big-data-tools.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](https://aka.ms/getazuredatastudio) |
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| **Data Virtualization extension** | Yes | Extension for Azure Data Studio that provides a Data Virtualization wizard. | [Install](../azure-data-studio/data-virtualization-extension.md) |
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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](https://docs.microsoft.com/cli/azure/?view=azure-cli-latest)). | [Install](https://docs.microsoft.com/cli/azure/install-azure-cli?view=azure-cli-latest) |
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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/?view=azure-cli-latest)). | [Install](/cli/azure/install-azure-cli?view=azure-cli-latest) |
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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](https://docs.microsoft.com/sql/tools/sqlcmd-utility?view=sql-server-ver15)). 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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| **sqlcmd** | For some scripts | Legacy command-line tool for querying SQL Server ([More info](../tools/sqlcmd-utility.md?view=sql-server-ver15)). 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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| `curl` <sup>3</sup> | For some scripts | Command-line tool for transferring data with URLs. | [Windows](https://curl.haxx.se/windows/) \| Linux: install curl package |
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| `oc` | Required for Red Hat OpenShift and Azure Redhat OpenShift deployments. |`oc` is the Open Shift command line interface (CLI). | [Installing the CLI](https://docs.openshift.com/container-platform/4.4/cli_reference/openshift_cli/getting-started-cli.html#installing-the-cli)
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[Get the latest Azure Data Studio](https://aka.ms/getazuredatastudio).
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For details about the latest release, see the [release notes](./release-notes-big-data-cluster.md).
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- [Quickstart: Deploy SQL Server big data cluster on Azure Kubernetes Service (AKS)](quickstart-big-data-cluster-deploy.md)
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- [How to deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] on Kubernetes](deployment-guidance.md)
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‎docs/big-data-cluster/deploy-on-aks.md‎

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> [!TIP]
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> Azure infrastructure offers multiple size options for VMs, see [here](/azure/virtual-machines/windows/sizes) for selections in the region you are planning to deploy.
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1. Create a Kubernetes cluster in AKS with the [az aks create](/cli/azure/aks) command. The following example creates a Kubernetes cluster named *kubcluster* with one Linux agent node of size **Standard_L8s**.
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1. To configure kubectl to connect to your Kubernetes cluster, run the [az aks get-credentials](/cli/azure/aks?view=azure-cli-latest#az-aks-get-credentials) command. This step downloads credentials and configures the kubectl CLI to use them.
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- Make sure that you have installed the [latest Azure CLI](/cli/azure/install-azure-cli?view=azure-cli-latest).
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[How to deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] on Kubernetes](deployment-guidance.md)
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[How to deploy [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] on Kubernetes](deployment-guidance.md)

‎docs/big-data-cluster/deployment-guidance.md‎

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|Edition|Notes|
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|Enterprise<br/>Standard<br/>Developer| Big Data Cluster edition is determined by the edition of SQL Server master instance. At deployment time Developer edition is deployed by default. You can change the edition after deployment. See [Configure SQL Server master instance](../big-data-cluster/configure-sql-server-master-instance.md). |
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|Enterprise<br/>Standard<br/>Developer| Big Data Cluster edition is determined by the edition of SQL Server master instance. At deployment time Developer edition is deployed by default. You can change the edition after deployment. See [Configure SQL Server master instance](./configure-sql-server-master-instance.md). |
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- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)
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- [Workshop: Microsoft [!INCLUDE[big-data-clusters-2019](../includes/ssbigdataclusters-ss-nover.md)] Architecture](https://github.com/Microsoft/sqlworkshops/tree/master/sqlserver2019bigdataclusters)

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