azuredatastudio/extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-existing-aks.ipynb

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            "cell_type": "markdown",
            "source": [
                "![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/master/src/sql/media/microsoft-small-logo.png)\n",
                " \n",
                "## Deploy SQL Server 2019 big data cluster on an existing Azure Kubernetes Service (AKS) cluster\n",
                " \n",
                "This notebook walks through the process of deploying a <a href=\"https://docs.microsoft.com/sql/big-data-cluster/big-data-cluster-overview?view=sqlallproducts-allversions\">SQL Server 2019 big data cluster</a> on an existing AKS cluster.\n",
                " \n",
                "* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
                "* Make sure you have the target cluster set as the current context in your kubectl config file.\n",
                "        The config file would typically be under C:\\Users\\(userid)\\.kube on Windows, and under ~/.kube/ for macOS and Linux for a default installation.\n",
                "        In the kubectl config file, look for \"current-context\" and ensure it is set to the AKS cluster that the SQL Server 2019 big data cluster will be deployed to.\n",
                "* The **Required information** cell will prompt you for password that will be used to access the cluster controller, SQL Server, and Knox.\n",
                "* The values in the **Default settings** cell can be changed as appropriate.\n",
                "\n",
                "<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
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            "source": [
                "### **Prerequisites** \n",
                "Ensure the following tools are installed and added to PATH before proceeding.\n",
                " \n",
                "|Tools|Description|Installation|\n",
                "|---|---|---|\n",
                "|kubectl | Command-line tool for monitoring the underlying Kuberentes cluster | [Installation](https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-kubectl-binary-using-native-package-management) |\n",
                "|azdata | Command-line tool for installing and managing a big data cluster |[Installation](https://docs.microsoft.com/en-us/sql/big-data-cluster/deploy-install-azdata?view=sqlallproducts-allversions) |"
            ],
            "metadata": {}
        },
        {
            "cell_type": "markdown",
            "source": "### **Check dependencies**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "import pandas,sys,os,json,html,getpass,time\r\n",
                "pandas_version = pandas.__version__.split('.')\r\n",
                "pandas_major = int(pandas_version[0])\r\n",
                "pandas_minor = int(pandas_version[1])\r\n",
                "pandas_patch = int(pandas_version[2])\r\n",
                "if not (pandas_major > 0 or (pandas_major == 0 and pandas_minor > 24) or (pandas_major == 0 and pandas_minor == 24 and pandas_patch >= 2)):\r\n",
                "    sys.exit('Please upgrade the Notebook dependency before you can proceed, you can do it by running the \"Reinstall Notebook dependencies\" command in command palette (View menu -> Command Palette…).')\r\n",
                "def run_command():\r\n",
                "    print(\"Executing: \" + cmd)\r\n",
                "    !{cmd}\r\n",
                "    if _exit_code != 0:\r\n",
                "        sys.exit(f'Command execution failed with exit code: {str(_exit_code)}.\\n\\t{cmd}\\n')\r\n",
                "    print(f'Successfully executed: {cmd}')\r\n",
                "\r\n",
                "cmd = 'kubectl version --client=true'\r\n",
                "run_command()\r\n",
                "cmd = 'azdata --version'\r\n",
                "run_command()"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 1
        },
        {
            "cell_type": "markdown",
            "source": "### **Show current context**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "cmd = ' kubectl config current-context'\r\n",
                "run_command()"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 2
        },
        {
            "cell_type": "markdown",
            "source": "### **Required information**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "env_var_flag = \"AZDATA_NB_VAR_BDC_CONTROLLER_PASSWORD\" in os.environ\n",
                "if env_var_flag:\n",
                "    mssql_password = os.environ[\"AZDATA_NB_VAR_BDC_CONTROLLER_PASSWORD\"]\n",
                "else: \n",
                "    mssql_password = getpass.getpass(prompt = 'SQL Server 2019 big data cluster controller password')\n",
                "    if mssql_password == \"\":\n",
                "        sys.exit(f'Password is required.')\n",
                "    confirm_password = getpass.getpass(prompt = 'Confirm password')\n",
                "    if mssql_password != confirm_password:\n",
                "        sys.exit(f'Passwords do not match.')\n",
                "print('You can also use the same password to access Knox and SQL Server.')"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 3
        },
        {
            "cell_type": "markdown",
            "source": "### **Default settings**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "if env_var_flag:\n",
                "    mssql_cluster_name = os.environ[\"AZDATA_NB_VAR_BDC_NAME\"]\n",
                "    mssql_controller_username = os.environ[\"AZDATA_NB_VAR_BDC_CONTROLLER_USERNAME\"]\n",
                "else:\n",
                "    mssql_cluster_name = 'mssql-cluster'\n",
                "    mssql_controller_username = 'admin'\n",
                "configuration_profile = 'aks-dev-test'\n",
                "configuration_folder = 'mssql-bdc-configuration'\n",
                "print(f'SQL Server big data cluster name: {mssql_cluster_name}')\n",
                "print(f'SQL Server big data cluster controller user name: {mssql_controller_username}')\n",
                "print(f'Deployment configuration profile: {configuration_profile}')\n",
                "print(f'Deployment configuration: {configuration_folder}')"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 4
        },
        {
            "cell_type": "markdown",
            "source": "### **Create a deployment configuration file**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "os.environ[\"ACCEPT_EULA\"] = 'yes'\n",
                "cmd = f'azdata bdc config init --source {configuration_profile} --target {configuration_folder} --force'\n",
                "run_command()\n",
                "cmd = f'azdata bdc config replace -c {configuration_folder}/bdc.json -j metadata.name={mssql_cluster_name}'\n",
                "run_command()"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 6
        },
        {
            "cell_type": "markdown",
            "source": "### **Create SQL Server 2019 big data cluster**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "print (f'Creating SQL Server 2019 big data cluster: {mssql_cluster_name} using configuration {configuration_folder}')\n",
                "os.environ[\"CONTROLLER_USERNAME\"] = mssql_controller_username\n",
                "os.environ[\"CONTROLLER_PASSWORD\"] = mssql_password\n",
                "os.environ[\"MSSQL_SA_PASSWORD\"] = mssql_password\n",
                "os.environ[\"KNOX_PASSWORD\"] = mssql_password\n",
                "cmd = f'azdata bdc create -c {configuration_folder}'\n",
                "run_command()"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 7
        },
        {
            "cell_type": "markdown",
            "source": "### **Login to SQL Server 2019 big data cluster**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "cmd = f'azdata login --cluster-name {mssql_cluster_name}'\n",
                "run_command()"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 8
        },
        {
            "cell_type": "markdown",
            "source": "### **Show SQL Server 2019 big data cluster endpoints**",
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "from IPython.display import *\n",
                "pandas.set_option('display.max_colwidth', -1)\n",
                "cmd = f'azdata bdc endpoint list'\n",
                "cmdOutput = !{cmd}\n",
                "endpoints = json.loads(''.join(cmdOutput))\n",
                "endpointsDataFrame = pandas.DataFrame(endpoints)\n",
                "endpointsDataFrame.columns = [' '.join(word[0].upper() + word[1:] for word in columnName.split()) for columnName in endpoints[0].keys()]\n",
                "display(HTML(endpointsDataFrame.to_html(index=False, render_links=True)))"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 9
        },
        {
            "cell_type": "markdown",
            "source": [
                "### **Connect to master SQL Server instance in Azure Data Studio**\r\n",
                "Click the link below to connect to the master SQL Server instance of the SQL Server 2019 big data cluster."
            ],
            "metadata": {}
        },
        {
            "cell_type": "code",
            "source": [
                "sqlEndpoints = [x for x in endpoints if x['name'] == 'sql-server-master']\r\n",
                "if sqlEndpoints and len(sqlEndpoints) == 1:\r\n",
                "    connectionParameter = '{\"serverName\":\"' + sqlEndpoints[0]['endpoint'] + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":\"sa\",\"password\":' + json.dumps(mssql_password) + '}'\r\n",
                "    display(HTML('<br/><a href=\"command:azdata.connect?' + html.escape(connectionParameter)+'\"><font size=\"3\">Click here to connect to master SQL Server instance</font></a><br/>'))\r\n",
                "else:\r\n",
                "    sys.exit('Could not find the master SQL Server instance endpoint')"
            ],
            "metadata": {},
            "outputs": [],
            "execution_count": 10
        }
    ]
}