mirror of
https://github.com/ckaczor/azuredatastudio.git
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431 lines
18 KiB
Plaintext
431 lines
18 KiB
Plaintext
{
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"metadata": {
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python",
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"version": "3.6.6",
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"mimetype": "text/x-python",
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"pygments_lexer": "ipython3",
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"nbconvert_exporter": "python",
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"file_extension": ".py"
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}
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},
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"nbformat_minor": 2,
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"nbformat": 4,
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"\n",
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" \n",
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"## Create Azure Kubernetes Service cluster and deploy SQL Server 2019 Big Data Cluster\n",
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" \n",
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"This notebook walks through the process of creating a new Azure Kubernetes Service cluster first, and then deploys 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 the newly created AKS cluster.\n",
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" \n",
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"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
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"* The **Required information** will check and prompt you for password if it is not set in the environment variable. The password will be used to access the cluster controller, SQL Server, and Knox.\n",
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"\n",
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"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
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],
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"metadata": {
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"azdata_cell_guid": "4f6bc3bc-3592-420a-b534-384011189005"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Prerequisites**\n",
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"Ensure the following tools are installed and added to PATH before proceeding.\n",
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"\n",
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"|Tools|Description|Installation|\n",
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"|---|---|---|\n",
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"|Azure CLI |Command-line tool for managing Azure services. Used to create AKS cluster | [Installation](https://docs.microsoft.com/cli/azure/install-azure-cli?view=azure-cli-latest) |\n",
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"|kubectl | Command-line tool for monitoring the underlying Kubernetes cluster | [Installation](https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-kubectl-binary-using-native-package-management) |\n",
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"|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) |"
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],
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"metadata": {
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"azdata_cell_guid": "d949980e-ad3f-4d02-ae84-7e4fbb19a087"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Setup**"
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],
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"metadata": {
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"azdata_cell_guid": "a56d3413-a730-4997-b5c2-c8abd972757e"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"import pandas,sys,os,json,html,getpass,time\n",
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"pandas_version = pandas.__version__.split('.')\n",
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"pandas_major = int(pandas_version[0])\n",
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"pandas_minor = int(pandas_version[1])\n",
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"pandas_patch = int(pandas_version[2])\n",
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"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)):\n",
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" 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…).')\n",
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"def run_command(command):\n",
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" print(\"Executing: \" + command)\n",
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" !{command}\n",
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" if _exit_code != 0:\n",
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" sys.exit(f'Command execution failed with exit code: {str(_exit_code)}.\\n\\t{command}\\n')\n",
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" print(f'Successfully executed: {command}')"
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],
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"metadata": {
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"azdata_cell_guid": "326645cf-022a-47f2-8aff-37de71da8955",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Set variables**\n",
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"Generated by Azure Data Studio using the values collected in the Deploy Big Data Cluster wizard"
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],
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"metadata": {
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"azdata_cell_guid": "8716915b-1439-431b-ab0a-0221ef94cb7f"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Check dependencies**"
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],
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"metadata": {
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"azdata_cell_guid": "db8b1e21-eb2c-4c35-b973-bc4ef38bb1d0"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command('kubectl version --client=true')\n",
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"run_command('azdata --version')\n",
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"run_command('az --version')"
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],
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"metadata": {
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"azdata_cell_guid": "9361deaf-28b1-4d02-912d-2011cae97e8a",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Required information**"
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],
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"metadata": {
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"azdata_cell_guid": "720c200c-322a-49dd-9aa3-8bf7946aa251"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"invoked_by_wizard = \"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\" in os.environ\n",
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"if invoked_by_wizard:\n",
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" mssql_password = os.environ[\"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\"]\n",
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"else:\n",
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" mssql_password = getpass.getpass(prompt = 'SQL Server 2019 Big Data Cluster controller password')\n",
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" if mssql_password == \"\":\n",
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" sys.exit(f'Password is required.')\n",
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" confirm_password = getpass.getpass(prompt = 'Confirm password')\n",
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" if mssql_password != confirm_password:\n",
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" sys.exit(f'Passwords do not match.')\n",
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"print('You can also use the controller password to access Knox and SQL Server.')"
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],
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"metadata": {
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"azdata_cell_guid": "17e5d087-7128-4d02-8c16-fe1ddee675e5",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Login to Azure**\n",
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"\n",
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"This will open a web browser window to enable credentials to be entered. If this cells is hanging forever, it might be because your Web browser windows is waiting for you to enter your Azure credentials!\n",
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""
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],
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"metadata": {
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"azdata_cell_guid": "baddf2d9-93ee-4c42-aaf1-b42116bb1912"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command(f'az login')"
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],
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"metadata": {
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"azdata_cell_guid": "8f1404a6-216d-49fb-b6ad-81beeea50083",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"\n",
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"### **Set active Azure subscription**"
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],
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"metadata": {
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"azdata_cell_guid": "230dc0f1-bf6e-474a-bfaa-aae6f8aad12e"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"if azure_subscription_id != \"\":\n",
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" run_command(f'az account set --subscription {azure_subscription_id}')\n",
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"else:\n",
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" print('Using the default Azure subscription', {azure_subscription_id})\n",
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"run_command(f'az account show')"
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],
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"metadata": {
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"azdata_cell_guid": "ab230931-2e99-483b-a229-3847684a8c1c",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Create Azure resource group**"
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],
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"metadata": {
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"azdata_cell_guid": "d51db914-f484-489f-990d-72edb3065068"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command(f'az group create --name {azure_resource_group} --location {azure_region}')"
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],
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"metadata": {
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"azdata_cell_guid": "7c53eb23-c327-41bf-8936-bd34a02ebdd5",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Create AKS cluster**"
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],
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"metadata": {
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"azdata_cell_guid": "818eb705-71e2-4013-8420-44886a5468b2"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command(f'az aks create --name {aks_cluster_name} --resource-group {azure_resource_group} --generate-ssh-keys --node-vm-size {azure_vm_size} --node-count {azure_vm_count}')"
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],
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"metadata": {
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"azdata_cell_guid": "3cea1da0-0c18-4030-a5aa-79bc98a5a14d",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Set the new AKS cluster as current context**"
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],
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"metadata": {
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"azdata_cell_guid": "5ade8453-5e71-478f-b6b6-83c55626243d"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command(f'az aks get-credentials --resource-group {azure_resource_group} --name {aks_cluster_name} --admin --overwrite-existing')"
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],
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"metadata": {
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"azdata_cell_guid": "9ccb9adf-1cf6-4dcb-8bd9-7ae9a85c2437",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Create deployment configuration files**"
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],
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"metadata": {
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"azdata_cell_guid": "57eb69fb-c68f-4ba8-818d-ffbaa0bc7aec"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"mssql_target_profile = 'ads-bdc-custom-profile'\n",
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"if not os.path.exists(mssql_target_profile):\n",
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" os.mkdir(mssql_target_profile)\n",
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"bdcJsonObj = json.loads(bdc_json)\n",
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"controlJsonObj = json.loads(control_json)\n",
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"bdcJsonFile = open(f'{mssql_target_profile}/bdc.json', 'w')\n",
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"bdcJsonFile.write(json.dumps(bdcJsonObj, indent = 4))\n",
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"bdcJsonFile.close()\n",
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"controlJsonFile = open(f'{mssql_target_profile}/control.json', 'w')\n",
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"controlJsonFile.write(json.dumps(controlJsonObj, indent = 4))\n",
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"controlJsonFile.close()\n",
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"print(f'Created deployment configuration folder: {mssql_target_profile}')"
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],
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"metadata": {
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"azdata_cell_guid": "3fd73c04-8a79-4d08-9049-1dad30265558",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Create SQL Server 2019 Big Data Cluster**"
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],
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"metadata": {
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"azdata_cell_guid": "6e82fad8-0fd0-4952-87ce-3fea1edd98cb"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"print (f'Creating SQL Server 2019 Big Data Cluster: {mssql_cluster_name} using configuration {mssql_target_profile}')\n",
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"os.environ[\"ACCEPT_EULA\"] = 'yes'\n",
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"os.environ[\"AZDATA_USERNAME\"] = mssql_username\n",
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"os.environ[\"AZDATA_PASSWORD\"] = mssql_password\n",
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"if os.name == 'nt':\n",
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" print(f'If you don\\'t see output produced by azdata, you can run the following command in a terminal window to check the deployment status:\\n\\t{os.environ[\"AZDATA_NB_VAR_KUBECTL\"]} get pods -n {mssql_cluster_name} ')\n",
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"run_command(f'azdata bdc create -c {mssql_target_profile}')"
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],
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"metadata": {
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"azdata_cell_guid": "c43ea026-ca5e-4e2a-8602-fcc786354168",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Login to SQL Server 2019 Big Data Cluster**"
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],
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"metadata": {
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"azdata_cell_guid": "9c5428f4-08b9-4799-a35d-867c91dc29fb"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"run_command(f'azdata login --namespace {mssql_cluster_name}')"
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],
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"metadata": {
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"azdata_cell_guid": "5120c387-1088-435b-856e-e59f147c45a2",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Show SQL Server 2019 Big Data Cluster endpoints**"
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],
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"metadata": {
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"azdata_cell_guid": "97974eda-e108-4c21-a58e-c6bb58f14ef1"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"from IPython.display import *\n",
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"pandas.set_option('display.max_colwidth', -1)\n",
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"cmd = f'azdata bdc endpoint list'\n",
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"cmdOutput = !{cmd}\n",
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"endpoints = json.loads(''.join(cmdOutput))\n",
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"endpointsDataFrame = pandas.DataFrame(endpoints)\n",
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"endpointsDataFrame.columns = [' '.join(word[0].upper() + word[1:] for word in columnName.split()) for columnName in endpoints[0].keys()]\n",
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"display(HTML(endpointsDataFrame.to_html(index=False, render_links=True)))"
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],
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"metadata": {
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"azdata_cell_guid": "9a5d0aef-a8da-4845-b470-d714435f0304",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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},
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{
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"cell_type": "markdown",
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"source": [
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"### **Connect to SQL Server Master instance in Azure Data Studio**\n",
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"Click the link below to connect to the SQL Server Master instance of the SQL Server 2019 Big Data Cluster."
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],
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"metadata": {
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"azdata_cell_guid": "4a49b629-bd7a-43ba-bf18-6cdc0737b0f9"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"sqlEndpoints = [x for x in endpoints if x['name'] == 'sql-server-master']\n",
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"if sqlEndpoints and len(sqlEndpoints) == 1:\n",
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" connectionParameter = '{\"serverName\":\"' + sqlEndpoints[0]['endpoint'] + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":' + json.dumps(mssql_username) + ',\"password\":' + json.dumps(mssql_password) + '}'\n",
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" display(HTML('<br/><a href=\"command:azdata.connect?' + html.escape(connectionParameter)+'\"><font size=\"3\">Click here to connect to SQL Server Master instance</font></a><br/>'))\n",
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" display(HTML('<br/><span style=\"color:red\"><font size=\"2\">NOTE: The SQL Server password is included in this link, you may want to clear the results of this code cell before saving the notebook.</font></span>'))\n",
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"else:\n",
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" sys.exit('Could not find the SQL Server Master instance endpoint.')"
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],
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"metadata": {
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"azdata_cell_guid": "1c9d1f2c-62ba-4070-920a-d30b67bdcc7c",
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"tags": [
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"hide_input"
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]
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},
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"outputs": [],
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"execution_count": null
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}
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]
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}
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