Provisions a Spark Cluster on Ubuntu Virtual Machines
Apache Spark is a fast and general engine for large-scale data processing. Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing.
This template deploys a Spark cluster on the Ubuntu virtual machines. This template also provisions a storage account, virtual network, availability sets, public IP addresses and network interfaces required by the installation. The template also creates 1 publicly accessible VM acting as a "jumpbox" and allowing to ssh into the Spark nodes for diagnostics or troubleshooting purposes.
How to Run the scripts
You can use the Deploy to Azure button or use the below methor with powershell
Creating a new deployment with powershell:
Remember to set your Username, Password and Unique Storage Account name in azuredeploy-parameters.json
Create a resource group:
PS C:\Users\azureuser1> New-AzureResourceGroup -Name "AZKFRGSPARKEA3" -Location 'EastAsia'
PS C:\Users\azureuser1> New-AzureResourceGroupDeployment -Name AZKFRGSPARKV2DEP1 -ResourceGroupName "AZKFRGSPARKEA3" -TemplateFile C:\gitsrc\azure-quickstart-templates\spark-on-ubuntu\azuredeploy.json -TemplateParameterFile C:\gitsrc\azure-quickstart-templates\spark-on-ubuntu\azuredeploy-parameters.json -Verbose
On successful deployment results will be like this
DeploymentName : AZKFRGSPARKV2DEP1
ResourceGroupName : AZKFRGSPARKEA3
ProvisioningState : Succeeded
Timestamp : 4/27/2015 2:00:48 PM
Mode : Incremental
Name Type Value
=============== ========================= ==========
adminUsername String adminuser
imagePublisher String Canonical
imageOffer String UbuntuServer
imageSKU String 14.04.5-LTS
storageAccountName String spkldeploysparknnuu1
region String West US
virtualNetworkName String sparkClustVnet
dataDiskSize Int 100
addressPrefix String 10.0.0.0/16
subnetName String Subnet1
subnetPrefix String 10.0.0.0/24
sparkVersion String 3.0.0
sparkClusterName String spark-arm-cluster
sparkNodeIPAddressPrefix String 10.0.0.1
sparkSlaveNodeIPAddressPrefix String 10.0.0.3
jumpbox String enabled
tshirtSize String S
To access the individual Spark nodes, you need to use the publicly accessible jumpbox VM and ssh from it into the VM instances running Spark.
To get started connect to the public ip of Jumpbox with username and password provided during deployment. From the jumpbox connect to any of the Spark workers eg: ssh 10.0.0.30 ,ssh 10.0.0.31, etc. Run the command ps-ef|grep spark to check that kafka process is running ok. To connect to master node you can use ssh 10.0.0.10
To access spark shell:
The deployment topology is comprised of Master and Slave Instance nodes running in the cluster mode. Spark version 1.2.1 is the default version and can be changed to any pre-built binaries avaiable on Spark repo. There is also a provision in the script to uncomment the build from source.
A static IP address will be assigned to each Spark Master node 10.0.0.10 A static IP address will be assigned to each Spark Slave node in order to work around the current limitation of not being able to dynamically compose a list of IP addresses from within the template (by default, the first node will be assigned the private IP of 10.0.0.30, the second node - 10.0.0.31, and so on)
To check deployment errors go to the new azure portal and look under Resource Group -> Last deployment -> Check Operation Details
##Known Issues and Limitations
- The deployment script is not yet idempotent and cannot handle updates
- SSH key is not yet implemented and the template currently takes a password for the admin user
- The deployment script is not yet handling data disks and using local storage. There will be a separate checkin for disks as per T shirt sizing.
- Spark cluster is current enabled for one master and multi slaves.
Tags: Microsoft.Resources/deployments, Microsoft.Network/networkInterfaces, Microsoft.Compute/virtualMachines, Microsoft.Compute/virtualMachines/extensions, CustomScript, Microsoft.Network/publicIPAddresses, Microsoft.Compute/availabilitySets, Microsoft.Network/virtualNetworks