Install SQL Server 2019 big data tools
Applies to: SQL Server 2019 (15.x)
The Microsoft SQL Server 2019 Big Data Clusters add-on will be retired. Support for SQL Server 2019 Big Data Clusters will end on February 28, 2025. All existing users of SQL Server 2019 with Software Assurance will be fully supported on the platform and the software will continue to be maintained through SQL Server cumulative updates until that time. For more information, see the announcement blog post and Big data options on the Microsoft SQL Server platform.
This article describes the client tools that should be installed for creating, managing, and using SQL Server 2019 Big Data Clusters. The following section provides a list of tools and links to installation instructions. Before deploying a big data cluster, configure the tools marked required on Windows or Linux.
Big data cluster tools
The following table lists common big data cluster tools and how to install them:
||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|
|Azure Data CLI (
||Yes||Command-line tool for installing and managing a big data cluster.||Install|
||Yes||Command-line tool for monitoring the underlying Kubernetes cluster (More info).||Windows | Linux|
|Azure Data Studio||Yes||Cross-platform graphical tool for querying SQL Server.||Install|
|Data Virtualization extension||Yes||Extension for Azure Data Studio that provides a Data Virtualization wizard.||Install|
|Azure CLI2||For AKS||Modern command-line interface for managing Azure services. Used with AKS big data cluster deployments (More info).||Install|
|mssql-cli||Optional||Modern command-line interface for querying SQL Server (More info).||Windows | Linux|
|sqlcmd||For some scripts||Legacy command-line tool for querying SQL Server (More info). You might need to install the Microsoft ODBC Driver 11 for SQL Server before installing the SQLCMD package.||Windows | Linux|
||For some scripts||Command-line tool for transferring data with URLs.||Windows | Linux: install curl package|
||Required for Red Hat OpenShift and Azure Redhat OpenShift deployments.||
||Installing the CLI|
1 You must use
kubectl version 1.13 or later. Also, the version of
kubectl should be plus or minus one minor version of your Kubernetes cluster. If you want to install a specific version on
kubectl client, see Install
kubectl binary via curl (on Windows 10 and Windows 11, use
cmd.exe and not Windows PowerShell to run curl).
kubectl with a previously deployed cluster on Azure Kubernetes Service (AKS), you must set the cluster context with the following Azure CLI command:
az aks get-credentials --name <aks_cluster_name> --resource-group <azure_resource_group_name>
2 You must be using Azure CLI version 2.0.4 or later. Run
az --version to find the version if needed.
3 If you are running on Windows 10 or Windows 11,
curl is already in your PATH when running from a cmd prompt. For other versions of Windows, download
curl using the link and place it in your PATH.
Which tools are required?
The previous table provides all of the common tools that are used with big data clusters. Which tools are required depends on your scenario. But in general, the following tools are most important for managing, connecting to, and querying the cluster:
- Azure Data CLI (
- Azure Data Studio
- Data Virtualization extension
The remaining tools are only required in certain scenarios. Azure CLI can be used to manage Azure services associated with AKS deployments. mssql-cli is an optional but useful tool that allows you to connect to the SQL Server master instance in the cluster and run queries from the command line. And sqlcmd and
curl are required if you plan to install sample data with the GitHub script.
Install python offline
On a machine with internet access, download one of the following compressed files containing Python:
Operating system Download Windows https://go.microsoft.com/fwlink/?linkid=2074021 Linux https://go.microsoft.com/fwlink/?linkid=2065975 OSX https://go.microsoft.com/fwlink/?linkid=2065976
Copy the compressed file to the target machine and extract it to a folder of your choice.
For Windows only, run
installLocalPythonPackages.batfrom that folder and pass the full path to the same folder as a parameter.
Download and install Azure Data Studio
Azure Data Studio provides capabilities and features specifically for SQL Server Big Data Clusters.
Get the latest Azure Data Studio.
For details about the latest release, see the release notes.
After configuring the tools, deploy a SQL Server 2019 big data cluster to Kubernetes in the Cloud or on-premises. For more information, see the following deployment articles:
- Quickstart: Deploy SQL Server big data cluster on Azure Kubernetes Service (AKS)
- How to deploy SQL Server Big Data Clusters on Kubernetes
For More info about big data clusters, see Introducing SQL Server 2019 Big Data Clusters.
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