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Code Issues Packages Projects Releases Wiki Activity

Feature/cu5 features (#11046)

Browse Source 
* openshift bdc target (#10358)

* openshift bdc target

* openshift bdc target

* comments

* new ad settings (#10390)

* ad settings

* comments

* bump version requirement (#10587)

* fix error

* update the notebook description (#10888)

* update notebooks
This commit is contained in:
Alan Ren
2020-06-22 19:04:51 -07:00
committed by GitHub
parent e01723f195
commit c9c4ec2035
18 changed files with 1028 additions and 135 deletions
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34
extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-aks.ipynb
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@@ -23,7 +23,7 @@
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/src/sql/media/microsoft-small-logo.png)\n",
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
" \n",
"## Create Azure Kubernetes Service cluster and deploy SQL Server 2019 Big Data Cluster\n",
" \n",
@@ -32,7 +32,7 @@
"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
"* 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",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {
"azdata_cell_guid": "4f6bc3bc-3592-420a-b534-384011189005"
@@ -47,7 +47,7 @@
"|Tools|Description|Installation|\n",
"|---|---|---|\n",
"|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",
"|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",
"|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",
"|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": {
@@ -87,7 +87,7 @@
]
},
"outputs": [],
"execution_count": 1
"execution_count": null
},
{
"cell_type": "markdown",
@@ -122,7 +122,7 @@
]
},
"outputs": [],
"execution_count": 0
"execution_count": null
},
{
"cell_type": "markdown",
@@ -155,7 +155,7 @@
]
},
"outputs": [],
"execution_count": 2
"execution_count": null
},
{
"cell_type": "markdown",
@@ -181,7 +181,7 @@
]
},
"outputs": [],
"execution_count": 5
"execution_count": null
},
{
"cell_type": "markdown",
@@ -209,7 +209,7 @@
]
},
"outputs": [],
"execution_count": 6
"execution_count": null
},
{
"cell_type": "markdown",
@@ -232,7 +232,7 @@
]
},
"outputs": [],
"execution_count": 7
"execution_count": null
},
{
"cell_type": "markdown",
@@ -255,7 +255,7 @@
]
},
"outputs": [],
"execution_count": 8
"execution_count": null
},
{
"cell_type": "markdown",
@@ -278,7 +278,7 @@
]
},
"outputs": [],
"execution_count": 9
"execution_count": null
},
{
"cell_type": "markdown",
@@ -312,7 +312,7 @@
]
},
"outputs": [],
"execution_count": 10
"execution_count": null
},
{
"cell_type": "markdown",
@@ -341,7 +341,7 @@
]
},
"outputs": [],
"execution_count": 11
"execution_count": null
},
{
"cell_type": "markdown",
@@ -364,7 +364,7 @@
]
},
"outputs": [],
"execution_count": 12
"execution_count": null
},
{
"cell_type": "markdown",
@@ -394,7 +394,7 @@
]
},
"outputs": [],
"execution_count": 13
"execution_count": null
},
{
"cell_type": "markdown",
@@ -423,7 +423,7 @@
]
},
"outputs": [],
"execution_count": 14
"execution_count": null
}
]
}
}

26
extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-existing-aks.ipynb
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@@ -23,7 +23,7 @@
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/src/sql/media/microsoft-small-logo.png)\n",
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
" \n",
"## Deploy SQL Server 2019 Big Data Cluster on an existing Azure Kubernetes Service (AKS) cluster\n",
" \n",
@@ -32,7 +32,7 @@
"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
"* The **Required information** will check and prompt you for password if it is not set in the environment variable. The password can be used to access the cluster controller, SQL Server, and Knox.\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {
"azdata_cell_guid": "82e60c1a-7acf-47ee-877f-9e85e92e11da"
@@ -46,7 +46,7 @@
" \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",
"|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",
"|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": {
@@ -86,7 +86,7 @@
]
},
"outputs": [],
"execution_count": 1
"execution_count": null
},
{
"cell_type": "markdown",
@@ -120,7 +120,7 @@
]
},
"outputs": [],
"execution_count": 0
"execution_count": null
},
{
"cell_type": "markdown",
@@ -153,7 +153,7 @@
]
},
"outputs": [],
"execution_count": 3
"execution_count": null
},
{
"cell_type": "markdown",
@@ -177,7 +177,7 @@
]
},
"outputs": [],
"execution_count": 0
"execution_count": null
},
{
"cell_type": "markdown",
@@ -211,7 +211,7 @@
]
},
"outputs": [],
"execution_count": 6
"execution_count": null
},
{
"cell_type": "markdown",
@@ -240,7 +240,7 @@
]
},
"outputs": [],
"execution_count": 7
"execution_count": null
},
{
"cell_type": "markdown",
@@ -263,7 +263,7 @@
]
},
"outputs": [],
"execution_count": 8
"execution_count": null
},
{
"cell_type": "markdown",
@@ -293,7 +293,7 @@
]
},
"outputs": [],
"execution_count": 9
"execution_count": null
},
{
"cell_type": "markdown",
@@ -322,7 +322,7 @@
]
},
"outputs": [],
"execution_count": 10
"execution_count": null
}
]
}
}

350
extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-existing-aro.ipynb Normal file
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@@ -0,0 +1,350 @@
{
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
}
},
"nbformat_minor": 2,
"nbformat": 4,
"cells": [
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
" \n",
"## Deploy SQL Server 2019 Big Data Cluster on an existing Azure Red Hat OpenShift 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 Azure Red Hat OpenShift cluster.\n",
" \n",
"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
"* The **Required information** will check and prompt you for password if it is not set in the environment variable. The password can be used to access the cluster controller, SQL Server, and Knox.\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {
"azdata_cell_guid": "23954d96-3932-4a8e-ab73-da605f99b1a4"
}
},
{
"cell_type": "markdown",
"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 Kubernetes 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": {
"azdata_cell_guid": "1d7f4c6a-0cb8-4ecc-81c8-544712253a3f"
}
},
{
"cell_type": "markdown",
"source": [
"### **Setup**"
],
"metadata": {
"azdata_cell_guid": "a31f9894-903f-4e19-a5a8-6fd888ff013b"
}
},
{
"cell_type": "code",
"source": [
"import pandas,sys,os,json,html,getpass,time\n",
"pandas_version = pandas.__version__.split('.')\n",
"pandas_major = int(pandas_version[0])\n",
"pandas_minor = int(pandas_version[1])\n",
"pandas_patch = int(pandas_version[2])\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)):\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…).')\n",
"def run_command(command):\n",
" print(\"Executing: \" + command)\n",
" !{command}\n",
" if _exit_code != 0:\n",
" sys.exit(f'Command execution failed with exit code: {str(_exit_code)}.\\n\\t{command}\\n')\n",
" print(f'Successfully executed: {command}')"
],
"metadata": {
"azdata_cell_guid": "26fa8bc4-4b8e-4c31-ae11-50484821cea8",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Set variables**\n",
"Generated by Azure Data Studio using the values collected in the Deploy Big Data Cluster wizard"
],
"metadata": {
"azdata_cell_guid": "e70640d0-6059-4cab-939e-e985a978c0da"
}
},
{
"cell_type": "markdown",
"source": [
"### **Check dependencies**"
],
"metadata": {
"azdata_cell_guid": "869d0397-a280-4dc4-be76-d652189b5131"
}
},
{
"cell_type": "code",
"source": [
"run_command('kubectl version --client=true')\n",
"run_command('azdata --version')"
],
"metadata": {
"azdata_cell_guid": "c38afb67-1132-495e-9af1-35bf067acbeb",
"tags": []
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Required information**"
],
"metadata": {
"azdata_cell_guid": "7b383b0d-5687-45b3-a16f-ba3b170c796e"
}
},
{
"cell_type": "code",
"source": [
"invoked_by_wizard = \"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\" in os.environ\n",
"if invoked_by_wizard:\n",
" mssql_password = os.environ[\"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\"]\n",
" if mssql_auth_mode == \"ad\":\n",
" mssql_domain_service_account_password = os.environ[\"AZDATA_NB_VAR_BDC_AD_DOMAIN_SVC_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",
" if mssql_auth_mode == \"ad\":\n",
" mssql_domain_service_account_password = getpass.getpass(prompt = 'Domain service account password')\n",
" if mssql_domain_service_account_password == \"\":\n",
" sys.exit(f'Domain service account password is required.')\n",
"print('You can also use the controller password to access Knox and SQL Server.')"
],
"metadata": {
"azdata_cell_guid": "b5970f2b-cf13-41af-b0a2-5133d840325e",
"tags": []
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Set and show current context**"
],
"metadata": {
"azdata_cell_guid": "6456bd0c-5b64-4d76-be59-e3a5b32697f5"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'kubectl config use-context {mssql_cluster_context}')\n",
"run_command('kubectl config current-context')"
],
"metadata": {
"azdata_cell_guid": "a38f8b3a-f93a-484c-b9e2-4eba3ed99cc2"
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Make sure the target namespace already exists**"
],
"metadata": {
"azdata_cell_guid": "3bf1d902-2217-4c99-b2d6-38e45de8e308"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'kubectl get namespace {mssql_cluster_name}')"
],
"metadata": {
"azdata_cell_guid": "6ca9bf71-049a-458e-8000-311d4c15b1ca"
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Create deployment configuration files**"
],
"metadata": {
"azdata_cell_guid": "6d78da36-6af5-4309-baad-bc81bb2cdb7f"
}
},
{
"cell_type": "code",
"source": [
"mssql_target_profile = 'ads-bdc-custom-profile'\n",
"if not os.path.exists(mssql_target_profile):\n",
" os.mkdir(mssql_target_profile)\n",
"bdcJsonObj = json.loads(bdc_json)\n",
"controlJsonObj = json.loads(control_json)\n",
"bdcJsonFile = open(f'{mssql_target_profile}/bdc.json', 'w')\n",
"bdcJsonFile.write(json.dumps(bdcJsonObj, indent = 4))\n",
"bdcJsonFile.close()\n",
"controlJsonFile = open(f'{mssql_target_profile}/control.json', 'w')\n",
"controlJsonFile.write(json.dumps(controlJsonObj, indent = 4))\n",
"controlJsonFile.close()\n",
"print(f'Created deployment configuration folder: {mssql_target_profile}')"
],
"metadata": {
"azdata_cell_guid": "3110ab23-ecfc-4e36-a1c5-28536b7edebf",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Create SQL Server 2019 Big Data Cluster**"
],
"metadata": {
"azdata_cell_guid": "7d56d262-8cd5-49e4-b745-332c6e7a3cb2"
}
},
{
"cell_type": "code",
"source": [
"print (f'Creating SQL Server 2019 Big Data Cluster: {mssql_cluster_name} using configuration {mssql_target_profile}')\n",
"os.environ[\"ACCEPT_EULA\"] = 'yes'\n",
"os.environ[\"AZDATA_USERNAME\"] = mssql_username\n",
"os.environ[\"AZDATA_PASSWORD\"] = mssql_password\n",
"if mssql_auth_mode == \"ad\":\n",
" os.environ[\"DOMAIN_SERVICE_ACCOUNT_USERNAME\"] = mssql_domain_service_account_username\n",
" os.environ[\"DOMAIN_SERVICE_ACCOUNT_PASSWORD\"] = mssql_domain_service_account_password\n",
"if os.name == 'nt':\n",
" 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",
"run_command(f'azdata bdc create -c {mssql_target_profile}')"
],
"metadata": {
"azdata_cell_guid": "0a743e88-e7d0-4b41-b8a3-e43985d15f2b",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Login to SQL Server 2019 Big Data Cluster**"
],
"metadata": {
"azdata_cell_guid": "7929fd90-324d-482a-a101-ae29cb183691"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'azdata login -n {mssql_cluster_name}')"
],
"metadata": {
"azdata_cell_guid": "3a49909b-e09e-4e62-a825-c39de2cffc94",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Show SQL Server 2019 Big Data Cluster endpoints**"
],
"metadata": {
"azdata_cell_guid": "038e801a-a393-4f8d-8e2d-97bc3b740b0c"
}
},
{
"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": {
"azdata_cell_guid": "2a8c8d5d-862c-4672-9309-38aa03afc4e6",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Connect to SQL Server Master instance in Azure Data Studio**\n",
"Click the link below to connect to the SQL Server Master instance of the SQL Server 2019 Big Data Cluster."
],
"metadata": {
"azdata_cell_guid": "0bd809fa-8225-4954-a50c-da57ea167896"
}
},
{
"cell_type": "code",
"source": [
"sqlEndpoints = [x for x in endpoints if x['name'] == 'sql-server-master']\n",
"if sqlEndpoints and len(sqlEndpoints) == 1:\n",
" connectionParameter = '{\"serverName\":\"' + sqlEndpoints[0]['endpoint'] + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":' + json.dumps(mssql_username) + ',\"password\":' + json.dumps(mssql_password) + '}'\n",
" 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",
"else:\n",
" sys.exit('Could not find the SQL Server Master instance endpoint.')"
],
"metadata": {
"azdata_cell_guid": "d591785d-71aa-4c5d-9cbb-a7da79bca503",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
}
]
}

30
extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-existing-kubeadm.ipynb
View File

@@ -23,7 +23,7 @@
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/src/sql/media/microsoft-small-logo.png)\n",
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
" \n",
"## Deploy SQL Server 2019 Big Data Cluster on an existing cluster deployed using kubeadm\n",
" \n",
@@ -32,7 +32,7 @@
"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
"* The **Required information** will check and prompt you for password if it is not set in the environment variable. The password can be used to access the cluster controller, SQL Server, and Knox.\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {
"azdata_cell_guid": "23954d96-3932-4a8e-ab73-da605f99b1a4"
@@ -46,7 +46,7 @@
" \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",
"|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",
"|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": {
@@ -82,11 +82,11 @@
"metadata": {
"azdata_cell_guid": "26fa8bc4-4b8e-4c31-ae11-50484821cea8",
"tags": [
"hide_input"
]
"hide_input"
]
},
"outputs": [],
"execution_count": 1
"execution_count": null
},
{
"cell_type": "markdown",
@@ -120,7 +120,7 @@
]
},
"outputs": [],
"execution_count": 0
"execution_count": null
},
{
"cell_type": "markdown",
@@ -159,7 +159,7 @@
]
},
"outputs": [],
"execution_count": 3
"execution_count": null
},
{
"cell_type": "markdown",
@@ -180,7 +180,7 @@
"azdata_cell_guid": "a38f8b3a-f93a-484c-b9e2-4eba3ed99cc2"
},
"outputs": [],
"execution_count": 0
"execution_count": null
},
{
"cell_type": "markdown",
@@ -214,7 +214,7 @@
]
},
"outputs": [],
"execution_count": 6
"execution_count": null
},
{
"cell_type": "markdown",
@@ -246,7 +246,7 @@
]
},
"outputs": [],
"execution_count": 7
"execution_count": null
},
{
"cell_type": "markdown",
@@ -269,7 +269,7 @@
]
},
"outputs": [],
"execution_count": 8
"execution_count": null
},
{
"cell_type": "markdown",
@@ -299,7 +299,7 @@
]
},
"outputs": [],
"execution_count": 9
"execution_count": null
},
{
"cell_type": "markdown",
@@ -328,7 +328,7 @@
]
},
"outputs": [],
"execution_count": 10
"execution_count": null
}
]
}
}

352
extensions/resource-deployment/notebooks/bdc/2019/deploy-bdc-existing-openshift.ipynb Normal file
View File

@@ -0,0 +1,352 @@
{
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
}
},
"nbformat_minor": 2,
"nbformat": 4,
"cells": [
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
" \n",
"## Deploy SQL Server 2019 Big Data Cluster on an existing OpenShift 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 OpenShift cluster.\n",
" \n",
"* Follow the instructions in the **Prerequisites** cell to install the tools if not already installed.\n",
"* The **Required information** will check and prompt you for password if it is not set in the environment variable. The password can be used to access the cluster controller, SQL Server, and Knox.\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {
"azdata_cell_guid": "23954d96-3932-4a8e-ab73-da605f99b1a4"
}
},
{
"cell_type": "markdown",
"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 Kubernetes 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": {
"azdata_cell_guid": "1d7f4c6a-0cb8-4ecc-81c8-544712253a3f"
}
},
{
"cell_type": "markdown",
"source": [
"### **Setup**"
],
"metadata": {
"azdata_cell_guid": "a31f9894-903f-4e19-a5a8-6fd888ff013b"
}
},
{
"cell_type": "code",
"source": [
"import pandas,sys,os,json,html,getpass,time\n",
"pandas_version = pandas.__version__.split('.')\n",
"pandas_major = int(pandas_version[0])\n",
"pandas_minor = int(pandas_version[1])\n",
"pandas_patch = int(pandas_version[2])\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)):\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…).')\n",
"def run_command(command):\n",
" print(\"Executing: \" + command)\n",
" !{command}\n",
" if _exit_code != 0:\n",
" sys.exit(f'Command execution failed with exit code: {str(_exit_code)}.\\n\\t{command}\\n')\n",
" print(f'Successfully executed: {command}')"
],
"metadata": {
"azdata_cell_guid": "26fa8bc4-4b8e-4c31-ae11-50484821cea8",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Set variables**\n",
"Generated by Azure Data Studio using the values collected in the Deploy Big Data Cluster wizard"
],
"metadata": {
"azdata_cell_guid": "e70640d0-6059-4cab-939e-e985a978c0da"
}
},
{
"cell_type": "markdown",
"source": [
"### **Check dependencies**"
],
"metadata": {
"azdata_cell_guid": "869d0397-a280-4dc4-be76-d652189b5131"
}
},
{
"cell_type": "code",
"source": [
"run_command('kubectl version --client=true')\n",
"run_command('azdata --version')"
],
"metadata": {
"azdata_cell_guid": "c38afb67-1132-495e-9af1-35bf067acbeb",
"tags": []
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Required information**"
],
"metadata": {
"azdata_cell_guid": "7b383b0d-5687-45b3-a16f-ba3b170c796e"
}
},
{
"cell_type": "code",
"source": [
"invoked_by_wizard = \"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\" in os.environ\n",
"if invoked_by_wizard:\n",
" mssql_password = os.environ[\"AZDATA_NB_VAR_BDC_ADMIN_PASSWORD\"]\n",
" if mssql_auth_mode == \"ad\":\n",
" mssql_domain_service_account_password = os.environ[\"AZDATA_NB_VAR_BDC_AD_DOMAIN_SVC_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",
" if mssql_auth_mode == \"ad\":\n",
" mssql_domain_service_account_password = getpass.getpass(prompt = 'Domain service account password')\n",
" if mssql_domain_service_account_password == \"\":\n",
" sys.exit(f'Domain service account password is required.')\n",
"print('You can also use the controller password to access Knox and SQL Server.')"
],
"metadata": {
"azdata_cell_guid": "b5970f2b-cf13-41af-b0a2-5133d840325e",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Set and show current context**"
],
"metadata": {
"azdata_cell_guid": "6456bd0c-5b64-4d76-be59-e3a5b32697f5"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'kubectl config use-context {mssql_cluster_context}')\n",
"run_command('kubectl config current-context')"
],
"metadata": {
"azdata_cell_guid": "a38f8b3a-f93a-484c-b9e2-4eba3ed99cc2"
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Make sure the target namespace already exists**"
],
"metadata": {
"azdata_cell_guid": "b903f09b-0eeb-45c0-8173-1741cce3790c"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'kubectl get namespace {mssql_cluster_name}')"
],
"metadata": {
"azdata_cell_guid": "174c02ea-8876-43be-bd93-3a39223e25ec"
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Create deployment configuration files**"
],
"metadata": {
"azdata_cell_guid": "6d78da36-6af5-4309-baad-bc81bb2cdb7f"
}
},
{
"cell_type": "code",
"source": [
"mssql_target_profile = 'ads-bdc-custom-profile'\n",
"if not os.path.exists(mssql_target_profile):\n",
" os.mkdir(mssql_target_profile)\n",
"bdcJsonObj = json.loads(bdc_json)\n",
"controlJsonObj = json.loads(control_json)\n",
"bdcJsonFile = open(f'{mssql_target_profile}/bdc.json', 'w')\n",
"bdcJsonFile.write(json.dumps(bdcJsonObj, indent = 4))\n",
"bdcJsonFile.close()\n",
"controlJsonFile = open(f'{mssql_target_profile}/control.json', 'w')\n",
"controlJsonFile.write(json.dumps(controlJsonObj, indent = 4))\n",
"controlJsonFile.close()\n",
"print(f'Created deployment configuration folder: {mssql_target_profile}')"
],
"metadata": {
"azdata_cell_guid": "3110ab23-ecfc-4e36-a1c5-28536b7edebf",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Create SQL Server 2019 Big Data Cluster**"
],
"metadata": {
"azdata_cell_guid": "7d56d262-8cd5-49e4-b745-332c6e7a3cb2"
}
},
{
"cell_type": "code",
"source": [
"print (f'Creating SQL Server 2019 Big Data Cluster: {mssql_cluster_name} using configuration {mssql_target_profile}')\n",
"os.environ[\"ACCEPT_EULA\"] = 'yes'\n",
"os.environ[\"AZDATA_USERNAME\"] = mssql_username\n",
"os.environ[\"AZDATA_PASSWORD\"] = mssql_password\n",
"if mssql_auth_mode == \"ad\":\n",
" os.environ[\"DOMAIN_SERVICE_ACCOUNT_USERNAME\"] = mssql_domain_service_account_username\n",
" os.environ[\"DOMAIN_SERVICE_ACCOUNT_PASSWORD\"] = mssql_domain_service_account_password\n",
"if os.name == 'nt':\n",
" 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",
"run_command(f'azdata bdc create -c {mssql_target_profile}')"
],
"metadata": {
"azdata_cell_guid": "0a743e88-e7d0-4b41-b8a3-e43985d15f2b",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Login to SQL Server 2019 Big Data Cluster**"
],
"metadata": {
"azdata_cell_guid": "7929fd90-324d-482a-a101-ae29cb183691"
}
},
{
"cell_type": "code",
"source": [
"run_command(f'azdata login -n {mssql_cluster_name}')"
],
"metadata": {
"azdata_cell_guid": "3a49909b-e09e-4e62-a825-c39de2cffc94",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Show SQL Server 2019 Big Data Cluster endpoints**"
],
"metadata": {
"azdata_cell_guid": "038e801a-a393-4f8d-8e2d-97bc3b740b0c"
}
},
{
"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": {
"azdata_cell_guid": "2a8c8d5d-862c-4672-9309-38aa03afc4e6",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
},
{
"cell_type": "markdown",
"source": [
"### **Connect to SQL Server Master instance in Azure Data Studio**\n",
"Click the link below to connect to the SQL Server Master instance of the SQL Server 2019 Big Data Cluster."
],
"metadata": {
"azdata_cell_guid": "0bd809fa-8225-4954-a50c-da57ea167896"
}
},
{
"cell_type": "code",
"source": [
"sqlEndpoints = [x for x in endpoints if x['name'] == 'sql-server-master']\n",
"if sqlEndpoints and len(sqlEndpoints) == 1:\n",
" connectionParameter = '{\"serverName\":\"' + sqlEndpoints[0]['endpoint'] + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":' + json.dumps(mssql_username) + ',\"password\":' + json.dumps(mssql_password) + '}'\n",
" 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",
"else:\n",
" sys.exit('Could not find the SQL Server Master instance endpoint.')"
],
"metadata": {
"azdata_cell_guid": "d591785d-71aa-4c5d-9cbb-a7da79bca503",
"tags": [
"hide_input"
]
},
"outputs": [],
"execution_count": null
}
]
}

116
extensions/resource-deployment/notebooks/docker/2017/deploy-sql2017-image.ipynb
View File

@@ -6,7 +6,7 @@
},
"language_info": {
"name": "python",
"version": "3.7.3",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
@@ -23,21 +23,27 @@
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/src/sql/media/microsoft-small-logo.png)\n",
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
"## Run SQL Server 2017 container images with Docker\n",
"This notebook will use Docker to pull and run the SQL Server 2017 container image and connect to it in Azure Data Studio\n",
"\n",
"### Dependencies\n",
"- Docker Engine. For more information, see [Install Docker](https://docs.docker.com/engine/installation/).\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "1d10b817-e9f4-4532-b69f-4d47504d590b"
}
},
{
"cell_type": "markdown",
"source": "### Check dependencies",
"metadata": {}
"source": [
"### Check dependencies"
],
"metadata": {
"azdata_cell_guid": "630e76af-01a6-4905-90a7-2d643126cdb4"
}
},
{
"cell_type": "code",
@@ -60,9 +66,11 @@
"cmd = 'docker version'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "64f3e119-408a-4b61-bce4-68114e2a727c"
},
"outputs": [],
"execution_count": 1
"execution_count": null
},
{
"cell_type": "markdown",
@@ -70,7 +78,9 @@
"### List existing containers\n",
"You can view the ports that have been used by existing containers"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "b671aaac-226f-4bbd-9839-552ec676c027"
}
},
{
"cell_type": "code",
@@ -78,14 +88,20 @@
"cmd = f'docker ps -a'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "dd665751-efbc-4089-af1b-0fa456a4fb58"
},
"outputs": [],
"execution_count": 2
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Required information",
"metadata": {}
"source": [
"### Required information"
],
"metadata": {
"azdata_cell_guid": "9927c86e-e929-497e-bced-ced60e6a5a7c"
}
},
{
"cell_type": "code",
@@ -106,14 +122,20 @@
"print(f'{password_name}: ******')\n",
"print(f'Port: {sql_port}')"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "a2e06bb2-23f3-4fc7-81bc-d38e250b24c0"
},
"outputs": [],
"execution_count": 3
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Pull the container image",
"metadata": {}
"source": [
"### Pull the container image"
],
"metadata": {
"azdata_cell_guid": "ca95b65d-e6f9-43a3-b06e-aa9cfc917725"
}
},
{
"cell_type": "code",
@@ -121,14 +143,20 @@
"cmd = f'docker pull mcr.microsoft.com/mssql/server:2017-latest'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "d75ae87c-2e59-4cf5-b61e-43f4bf8ac680"
},
"outputs": [],
"execution_count": 4
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Start a new container",
"metadata": {}
"source": [
"### Start a new container"
],
"metadata": {
"azdata_cell_guid": "5bbde6b1-4933-417d-90cc-0c853e002552"
}
},
{
"cell_type": "code",
@@ -141,14 +169,20 @@
"cmd = f'docker run -e ACCEPT_EULA=Y -e \"SA_PASSWORD={sql_password}\" -p {sql_port}:1433 --name {container_name} -d mcr.microsoft.com/mssql/server:2017-latest'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "73585d5d-0c8c-4786-92f2-7e0fd2653f9e"
},
"outputs": [],
"execution_count": 5
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### List all the containers",
"metadata": {}
"source": [
"### List all the containers"
],
"metadata": {
"azdata_cell_guid": "e338290a-0e1d-4780-aad5-3416447be0a1"
}
},
{
"cell_type": "code",
@@ -156,9 +190,11 @@
"cmd = f'docker ps -a'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "5e30c110-a631-4c9b-8485-cd64d34c54d5"
},
"outputs": [],
"execution_count": 6
"execution_count": null
},
{
"cell_type": "markdown",
@@ -166,7 +202,9 @@
"### Connect to SQL Server in Azure Data Studio\n",
"It might take a couple minutes for SQL Server to launch"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "11add202-2f03-4d20-8411-d4f274910107"
}
},
{
"cell_type": "code",
@@ -175,14 +213,20 @@
"connectionParameter = '{\"serverName\":\"localhost,' + sql_port + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":\"sa\",\"password\":' + json.dumps(sql_password) + '}'\n",
"display(HTML('<br/><a href=\"command:azdata.connect?' + html.escape(connectionParameter)+'\"><font size=\"3\">Click here to connect to SQL Server</font></a><br/>'))"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "182517d3-f6d6-4ecc-b2cb-4c21a0f23b4e"
},
"outputs": [],
"execution_count": 7
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Stop and remove the container",
"metadata": {}
"source": [
"### Stop and remove the container"
],
"metadata": {
"azdata_cell_guid": "416a7e11-0ea7-487d-804f-b8449f0ce5fc"
}
},
{
"cell_type": "code",
@@ -193,9 +237,11 @@
"display(HTML(\"Stop the container: <a href=\\\"command:workbench.action.terminal.sendSequence?%7B%22text%22%3A%22\"+stop_container_command.replace(\" \",\"%20\")+\"%22%7D\\\">\" + stop_container_command + \"</a>\"))\n",
"display(HTML(\"Remove the container: <a href=\\\"command:workbench.action.terminal.sendSequence?%7B%22text%22%3A%22\"+remove_container_command.replace(\" \",\"%20\")+\"%22%7D\\\">\" + remove_container_command + \"</a>\"))"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "1593a0a6-7009-4d0b-9f3f-ac7ed6d2bb1e"
},
"outputs": [],
"execution_count": 8
"execution_count": null
}
]
}
}

116
extensions/resource-deployment/notebooks/docker/2019/deploy-sql2019-image.ipynb
View File

@@ -6,7 +6,7 @@
},
"language_info": {
"name": "python",
"version": "3.7.3",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
@@ -23,21 +23,27 @@
{
"cell_type": "markdown",
"source": [
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/src/sql/media/microsoft-small-logo.png)\n",
"![Microsoft](https://raw.githubusercontent.com/microsoft/azuredatastudio/main/extensions/resource-deployment/images/microsoft-small-logo.png)\n",
"## Run SQL Server 2019 container image with Docker\n",
"This notebook will use Docker to pull and run the SQL Server 2019 container image and connect to it in Azure Data Studio\n",
"\n",
"### Dependencies\n",
"- Docker Engine. For more information, see [Install Docker](https://docs.docker.com/engine/installation/).\n",
"\n",
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run Cells\" button to run the notebook</font></span>"
"<span style=\"color:red\"><font size=\"3\">Please press the \"Run all\" button to run the notebook</font></span>"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "e5fb2be9-e904-4821-8473-b69b90760c6a"
}
},
{
"cell_type": "markdown",
"source": "### Check dependencies",
"metadata": {}
"source": [
"### Check dependencies"
],
"metadata": {
"azdata_cell_guid": "76c571ab-358a-4b07-810c-53020ee1745a"
}
},
{
"cell_type": "code",
@@ -60,9 +66,11 @@
"cmd = 'docker version'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "6196300e-f896-489b-8dca-b2c42eda2d6d"
},
"outputs": [],
"execution_count": 1
"execution_count": null
},
{
"cell_type": "markdown",
@@ -70,7 +78,9 @@
"### List existing containers\n",
"You can view the ports that have been used by existing containers"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "87b07614-d57d-4731-ac3e-a8b324d231f2"
}
},
{
"cell_type": "code",
@@ -78,14 +88,20 @@
"cmd = f'docker ps -a'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "26170d1b-4332-4383-bcc4-1d97030daffc"
},
"outputs": [],
"execution_count": 2
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Required information",
"metadata": {}
"source": [
"### Required information"
],
"metadata": {
"azdata_cell_guid": "52b1faf2-d7c7-446b-ba0b-4f8b744da0bb"
}
},
{
"cell_type": "code",
@@ -106,14 +122,20 @@
"print(f'{password_name}: ******')\n",
"print(f'Port: {sql_port}')"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "93cb0147-7bf6-4630-b796-3811dfd1354b"
},
"outputs": [],
"execution_count": 3
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Pull the container image",
"metadata": {}
"source": [
"### Pull the container image"
],
"metadata": {
"azdata_cell_guid": "643ccaca-fd1d-4482-b81e-aee29b627e34"
}
},
{
"cell_type": "code",
@@ -121,14 +143,20 @@
"cmd = f'docker pull mcr.microsoft.com/mssql/server:2019-latest'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "7b102447-3198-488f-a995-982ae1fc8555"
},
"outputs": [],
"execution_count": 4
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Start a new container",
"metadata": {}
"source": [
"### Start a new container"
],
"metadata": {
"azdata_cell_guid": "a4527a5f-c2c5-4f60-bfd1-b119576178c5"
}
},
{
"cell_type": "code",
@@ -141,14 +169,20 @@
"cmd = f'docker run -e ACCEPT_EULA=Y -e \"SA_PASSWORD={sql_password}\" -p {sql_port}:1433 --name {container_name} -d mcr.microsoft.com/mssql/server:2019-latest'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "82f27460-88eb-4484-92ee-40305e650d70"
},
"outputs": [],
"execution_count": 5
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### List all the containers",
"metadata": {}
"source": [
"### List all the containers"
],
"metadata": {
"azdata_cell_guid": "e267aa7d-dd22-43ac-9b03-cf282ef15f67"
}
},
{
"cell_type": "code",
@@ -156,9 +190,11 @@
"cmd = f'docker ps -a'\n",
"run_command()"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "211ee198-f1d1-4781-9daa-8497c2665de6"
},
"outputs": [],
"execution_count": 6
"execution_count": null
},
{
"cell_type": "markdown",
@@ -166,7 +202,9 @@
"### Connect to SQL Server in Azure Data Studio\n",
"It might take a couple minutes for SQL Server to launch"
],
"metadata": {}
"metadata": {
"azdata_cell_guid": "5f5860c4-7962-439e-a15b-7f24f504dc18"
}
},
{
"cell_type": "code",
@@ -175,14 +213,20 @@
"connectionParameter = '{\"serverName\":\"localhost,' + sql_port + '\",\"providerName\":\"MSSQL\",\"authenticationType\":\"SqlLogin\",\"userName\":\"sa\",\"password\":' + json.dumps(sql_password) + '}'\n",
"display(HTML('<br/><a href=\"command:azdata.connect?' + html.escape(connectionParameter)+'\"><font size=\"3\">Click here to connect to SQL Server</font></a><br/>'))"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "4bc64915-c5ae-4507-8fb0-9e413ccc2fd0"
},
"outputs": [],
"execution_count": 7
"execution_count": null
},
{
"cell_type": "markdown",
"source": "### Stop and remove the container",
"metadata": {}
"source": [
"### Stop and remove the container"
],
"metadata": {
"azdata_cell_guid": "9a1039fa-fdd3-408b-b649-8fde0fcee660"
}
},
{
"cell_type": "code",
@@ -193,9 +237,11 @@
"display(HTML(\"Stop the container: <a href=\\\"command:workbench.action.terminal.sendSequence?%7B%22text%22%3A%22\"+stop_container_command.replace(\" \",\"%20\")+\"%22%7D\\\">\" + stop_container_command + \"</a>\"))\n",
"display(HTML(\"Remove the container: <a href=\\\"command:workbench.action.terminal.sendSequence?%7B%22text%22%3A%22\"+remove_container_command.replace(\" \",\"%20\")+\"%22%7D\\\">\" + remove_container_command + \"</a>\"))"
],
"metadata": {},
"metadata": {
"azdata_cell_guid": "f9e0f1ad-ba6e-4c17-84ea-cc5dceb1289b"
},
"outputs": [],
"execution_count": 8
"execution_count": null
}
]
}
}

56
extensions/resource-deployment/package.json
View File

@@ -231,6 +231,14 @@
{
"name": "existing-kubeadm",
"displayName": "%bdc-deployment-target-existing-kubeadm%"
},
{
"name": "existing-aro",
"displayName": "%bdc-deployment-target-existing-aro%"
},
{
"name": "existing-openshift",
"displayName": "%bdc-deployment-target-existing-openshift%"
}
]
}
@@ -251,7 +259,7 @@
},
{
"name": "azdata",
"version": "15.0.4013"
"version": "20.0.0"
}
],
"when": "target=new-aks&&version=bdc2019"
@@ -263,10 +271,12 @@
},
"requiredTools": [
{
"name": "kubectl"
"name": "kubectl",
"version": "1.13.0"
},
{
"name": "azdata"
"name": "azdata",
"version": "20.0.0"
}
],
"when": "target=existing-aks&&version=bdc2019"
@@ -278,13 +288,49 @@
},
"requiredTools": [
{
"name": "kubectl"
"name": "kubectl",
"version": "1.13.0"
},
{
"name": "azdata"
"name": "azdata",
"version": "20.0.0"
}
],
"when": "target=existing-kubeadm&&version=bdc2019"
},
{
"bdcWizard": {
"type": "existing-aro",
"notebook": "%bdc-2019-existing-aro-notebook%"
},
"requiredTools": [
{
"name": "kubectl",
"version": "1.13.0"
},
{
"name": "azdata",
"version": "20.0.0"
}
],
"when": "target=existing-aro&&version=bdc2019"
},
{
"bdcWizard": {
"type": "existing-openshift",
"notebook": "%bdc-2019-existing-openshift-notebook%"
},
"requiredTools": [
{
"name": "kubectl",
"version": "1.13.0"
},
{
"name": "azdata",
"version": "20.0.0"
}
],
"when": "target=existing-openshift&&version=bdc2019"
}
],
"agreement": {

4
extensions/resource-deployment/package.nls.json
View File

@@ -17,9 +17,13 @@
"bdc-deployment-target-new-aks": "New Azure Kubernetes Service Cluster",
"bdc-deployment-target-existing-aks": "Existing Azure Kubernetes Service Cluster",
"bdc-deployment-target-existing-kubeadm": "Existing Kubernetes Cluster (kubeadm)",
"bdc-deployment-target-existing-aro": "Existing Azure Red Hat OpenShift cluster",
"bdc-deployment-target-existing-openshift": "Existing OpenShift cluster",
"bdc-2019-aks-notebook": "./notebooks/bdc/2019/deploy-bdc-aks.ipynb",
"bdc-2019-existing-aks-notebook": "./notebooks/bdc/2019/deploy-bdc-existing-aks.ipynb",
"bdc-2019-existing-kubeadm-notebook": "./notebooks/bdc/2019/deploy-bdc-existing-kubeadm.ipynb",
"bdc-2019-existing-aro-notebook": "./notebooks/bdc/2019/deploy-bdc-existing-aro.ipynb",
"bdc-2019-existing-openshift-notebook": "./notebooks/bdc/2019/deploy-bdc-existing-openshift.ipynb",
"docker-sql-2017-title": "Deploy SQL Server 2017 container images",
"docker-sql-2019-title": "Deploy SQL Server 2019 container images",
"docker-container-name-field": "Container name",

4
extensions/resource-deployment/src/interfaces.ts
View File

@@ -347,7 +347,9 @@ export interface ITool {
export const enum BdcDeploymentType {
NewAKS = 'new-aks',
ExistingAKS = 'existing-aks',
ExistingKubeAdm = 'existing-kubeadm'
ExistingKubeAdm = 'existing-kubeadm',
ExistingARO = 'existing-aro',
ExistingOpenShift = 'existing-openshift'
}
export const enum ArcDeploymentType {

6
extensions/resource-deployment/src/services/azdataService.ts
View File

@@ -35,6 +35,12 @@ export class AzdataService implements IAzdataService {
case BdcDeploymentType.ExistingKubeAdm:
profilePrefix = 'kubeadm';
break;
case BdcDeploymentType.ExistingARO:
profilePrefix = 'aro';
break;
case BdcDeploymentType.ExistingOpenShift:
profilePrefix = 'openshift';
break;
default:
throw new Error(`Unknown deployment type: ${deploymentType}`);
}

4
extensions/resource-deployment/src/services/bigDataClusterDeploymentProfile.ts
View File

@@ -30,6 +30,8 @@ export interface ActiveDirectorySettings {
clusterAdmins: string;
appReaders?: string;
appOwners?: string;
subdomain?: string;
accountPrefix?: string;
}
export class BigDataClusterDeploymentProfile {
@@ -280,6 +282,8 @@ export class BigDataClusterDeploymentProfile {
activeDirectoryObject.dnsIpAddresses = this.splitByComma(adSettings.dnsIPAddresses);
activeDirectoryObject.domainControllerFullyQualifiedDns = this.splitByComma(adSettings.domainControllerFQDNs.toLowerCase());
activeDirectoryObject.domainDnsName = adSettings.domainDNSName;
activeDirectoryObject.subdomain = adSettings.subdomain;
activeDirectoryObject.accountPrefix = adSettings.accountPrefix;
activeDirectoryObject.realm = adSettings.domainDNSName.toUpperCase();
activeDirectoryObject.clusterAdmins = this.splitByComma(adSettings.clusterAdmins);
activeDirectoryObject.clusterUsers = this.splitByComma(adSettings.clusterUsers);

6
extensions/resource-deployment/src/ui/deployClusterWizard/constants.ts
View File

@@ -17,8 +17,10 @@ export const DomainDNSName_VariableName = 'AZDATA_NB_VAR_BDC_AD_DOMAIN_DNS_NAME'
export const Realm_VariableName = 'AZDATA_NB_VAR_BDC_AD_REALM';
export const DomainServiceAccountUserName_VariableName = 'AZDATA_NB_VAR_BDC_AD_DOMAIN_SVC_USERNAME';
export const DomainServiceAccountPassword_VariableName = 'AZDATA_NB_VAR_BDC_AD_DOMAIN_SVC_PASSWORD';
export const AppOwners_VariableName = 'AZDATA_NB_VAR_AD_BDC_APP_OWNERS';
export const AppReaders_VariableName = 'AZDATA_NB_VAR_AD_BDC_APP_READERS';
export const AppOwners_VariableName = 'AZDATA_NB_VAR_BDC_AD_APP_OWNERS';
export const AppReaders_VariableName = 'AZDATA_NB_VAR_AD_BDC_AD_APP_READERS';
export const Subdomain_VariableName = 'AZDATA_NB_VAR_BDC_AD_SUBDOMAIN';
export const AccountPrefix_VariableName = 'AZDATA_NB_VAR_BDC_AD_ACCOUNTPREFIX';
export const SubscriptionId_VariableName = 'AZDATA_NB_VAR_BDC_AZURE_SUBSCRIPTION';
export const ResourceGroup_VariableName = 'AZDATA_NB_VAR_BDC_RESOURCEGROUP_NAME';
export const Location_VariableName = 'AZDATA_NB_VAR_BDC_AZURE_REGION';

14
extensions/resource-deployment/src/ui/deployClusterWizard/deployClusterWizard.ts
View File

@@ -94,14 +94,9 @@ export class DeployClusterWizard extends WizardBase<DeployClusterWizard, WizardP
new SummaryPage(this));
break;
case BdcDeploymentType.ExistingAKS:
pages.push(
new DeploymentProfilePage(this),
new TargetClusterContextPage(this),
new ClusterSettingsPage(this),
new ServiceSettingsPage(this),
new SummaryPage(this));
break;
case BdcDeploymentType.ExistingKubeAdm:
case BdcDeploymentType.ExistingARO:
case BdcDeploymentType.ExistingOpenShift:
pages.push(
new DeploymentProfilePage(this),
new TargetClusterContextPage(this),
@@ -171,6 +166,11 @@ export class DeployClusterWizard extends WizardBase<DeployClusterWizard, WizardP
return localize('deployCluster.ExistingAKSWizardTitle', "Deploy SQL Server 2019 Big Data Cluster on an existing AKS cluster");
case BdcDeploymentType.ExistingKubeAdm:
return localize('deployCluster.ExistingKubeAdm', "Deploy SQL Server 2019 Big Data Cluster on an existing kubeadm cluster");
case BdcDeploymentType.ExistingARO:
return localize('deployCluster.ExistingARO', "Deploy SQL Server 2019 Big Data Cluster on an existing Azure Red Hat OpenShift cluster");
case BdcDeploymentType.ExistingOpenShift:
return localize('deployCluster.ExistingOpenShift', "Deploy SQL Server 2019 Big Data Cluster on an existing OpenShift cluster");
default:
throw new Error(`Unknown deployment type: ${type}`);
}

9
extensions/resource-deployment/src/ui/deployClusterWizard/deployClusterWizardModel.ts
View File

@@ -132,7 +132,9 @@ export class DeployClusterWizardModel extends Model {
clusterAdmins: this.getStringValue(VariableNames.ClusterAdmins_VariableName)!,
clusterUsers: this.getStringValue(VariableNames.ClusterUsers_VariableName)!,
appOwners: this.getStringValue(VariableNames.AppOwners_VariableName),
appReaders: this.getStringValue(VariableNames.AppReaders_VariableName)
appReaders: this.getStringValue(VariableNames.AppReaders_VariableName),
subdomain: this.getStringValue(VariableNames.Subdomain_VariableName),
accountPrefix: this.getStringValue(VariableNames.AccountPrefix_VariableName)
});
}
return targetDeploymentProfile;
@@ -148,7 +150,10 @@ export class DeployClusterWizardModel extends Model {
statements.push(`azure_vm_size = '${this.getStringValue(VariableNames.VMSize_VariableName)}'`);
statements.push(`azure_vm_count = '${this.getStringValue(VariableNames.VMCount_VariableName)}'`);
statements.push(`aks_cluster_name = '${this.getStringValue(VariableNames.AksName_VariableName)}'`);
} else if (this.deploymentTarget === BdcDeploymentType.ExistingAKS || this.deploymentTarget === BdcDeploymentType.ExistingKubeAdm) {
} else if (this.deploymentTarget === BdcDeploymentType.ExistingAKS
|| this.deploymentTarget === BdcDeploymentType.ExistingKubeAdm
|| this.deploymentTarget === BdcDeploymentType.ExistingARO
|| this.deploymentTarget === BdcDeploymentType.ExistingOpenShift) {
statements.push(`mssql_kube_config_path = '${this.escapeForNotebookCodeCell(this.getStringValue(VariableNames.KubeConfigPath_VariableName)!)}'`);
statements.push(`mssql_cluster_context = '${this.getStringValue(VariableNames.ClusterContext_VariableName)}'`);
statements.push('os.environ["KUBECONFIG"] = mssql_kube_config_path');

17
extensions/resource-deployment/src/ui/deployClusterWizard/pages/clusterSettingsPage.ts
View File

@@ -186,6 +186,18 @@ export class ClusterSettingsPage extends WizardPageBase<DeployClusterWizard> {
variableName: VariableNames.AppReaders_VariableName,
placeHolder: localize('deployCluster.AppReadersPlaceHolder', "Use comma to separate the values."),
description: localize('deployCluster.AppReadersDescription', "The Active Directory users or groups of app readers. Use comma as separator them if there are multiple users/groups.")
}, {
type: FieldType.Text,
label: localize('deployCluster.Subdomain', "Subdomain"),
required: false,
variableName: VariableNames.Subdomain_VariableName,
description: localize('deployCluster.SubdomainDescription', "A unique DNS subdomain to use for this SQL Server Big Data Cluster. If not provided, the cluster name will be used as the default value.")
}, {
type: FieldType.Text,
label: localize('deployCluster.AccountPrefix', "Account prefix"),
required: false,
variableName: VariableNames.AccountPrefix_VariableName,
description: localize('deployCluster.AccountPrefixDescription', "A unique prefix for AD accounts SQL Server Big Data Cluster will generate. If not provided, the subdomain name will be used as the default value. If a subdomain is not provided, the cluster name will be used as the default value.")
}
]
};
@@ -279,10 +291,9 @@ export class ClusterSettingsPage extends WizardPageBase<DeployClusterWizard> {
variableDNSPrefixMapping[VariableNames.SQLServerDNSName_VariableName] = 'bdc-sql';
variableDNSPrefixMapping[VariableNames.ServiceProxyDNSName_VariableName] = 'bdc-proxy';
const subdomain = this.wizard.model.getStringValue(VariableNames.Subdomain_VariableName) || this.wizard.model.getStringValue(VariableNames.ClusterName_VariableName);
Object.keys(variableDNSPrefixMapping).forEach((variableName: string) => {
if (!this.wizard.model.getStringValue(variableName)) {
this.wizard.model.setPropertyValue(variableName, `${variableDNSPrefixMapping[variableName]}.${this.wizard.model.getStringValue(VariableNames.DomainDNSName_VariableName)}`);
}
this.wizard.model.setPropertyValue(variableName, `${variableDNSPrefixMapping[variableName]}.${subdomain}.${this.wizard.model.getStringValue(VariableNames.DomainDNSName_VariableName)}`);
});
}
this.wizard.wizardObject.registerNavigationValidator((pcInfo) => {

4
extensions/resource-deployment/src/ui/deployClusterWizard/pages/deploymentProfilePage.ts
View File

@@ -246,6 +246,10 @@ export class DeploymentProfilePage extends WizardPageBase<DeployClusterWizard> {
return 'aks-dev-test';
case BdcDeploymentType.ExistingKubeAdm:
return 'kubeadm-dev-test';
case BdcDeploymentType.ExistingARO:
return 'aro-dev-test';
case BdcDeploymentType.ExistingOpenShift:
return 'openshift-dev-test';
default:
throw new Error(`Unknown deployment type: ${this.wizard.deploymentType}`);
}

15
extensions/resource-deployment/src/ui/deployClusterWizard/pages/summaryPage.ts
View File

@@ -161,6 +161,21 @@ export class SummaryPage extends WizardPageBase<DeployClusterWizard> {
labelCSSStyles: { fontWeight: FontWeight.Bold }
}]
});
clusterSectionInfo.rows!.push({
items: [
{
type: FieldType.ReadonlyText,
label: localize('deployCluster.Subdomain', "Subdomain"),
defaultValue: this.wizard.model.getStringValue(VariableNames.Subdomain_VariableName),
labelCSSStyles: { fontWeight: FontWeight.Bold }
},
{
type: FieldType.ReadonlyText,
label: localize('deployCluster.AccountPrefix', "Account prefix"),
defaultValue: this.wizard.model.getStringValue(VariableNames.AccountPrefix_VariableName),
labelCSSStyles: { fontWeight: FontWeight.Bold }
}]
});
clusterSectionInfo.rows!.push({
items: [
{