Use Rainbond Deployment

Use Rainbond Deployment

This section describes the one-click deployment of high availability DolphinScheduler clusters through the Rainbond cloud native application management platform. This method is suitable for users who don’t know much about complex technologies such as Kubernetes, lowering the threshold for deploying DolphinScheduler in Kubernetes mode.

Prerequisites

Available Rainbond cloud native application management platform is a prerequisite，please refer to the official Rainbond documentation Rainbond Quick install

DolphinScheduler Cluster One-click Deployment

Logging in and accessing the built-in open source app store, search the keyword dolphinscheduler to find the DolphinScheduler App.

Click install on the right side of DolphinScheduler to go to the installation page. Fill in the corresponding information and click OK to start the installation. You will get automatically redirected to the application view.

Select item	Description
Team name	user workspace，Isolate by namespace
Cluster name	select kubernetes cluster
Select app	select application
app version	select DolphinScheduler version

Wait a few minutes, the installation completes and DolphinScheduler will be running.

Access DolphinScheduler-API components and the default user credentials are admin / dolphinscheduler123.

API Master Worker Node Telescopic

DolphinScheduler API、Master、Worker all support scaling multiple instances, ensuring the high availability of the entire service.

Take worker as an example: enter the component -> Telescopic page, and set the number of instances.

To verify worker node, enter DolphinScheduler UI -> Monitoring -> Worker page to view detailed node information.

Configuration file

API and Worker Services share the configuration file /opt/dolphinscheduler/conf/common.properties. To modify the configurations, you only need to modify that of the API service.

How to support Python 3？

Worker service is installed with default Python3，you can add environment variables PYTHON_HOME=/usr/bin/python3

How to support Hadoop, Spark, DataX ？

Take DataX as an example:

Install the plugin。Rainbond Team View -> Plugin -> Install plugin from the App Store -> search initialization plugin Install.
Open plugin.enter Worker component -> plugin -> open initialization plugin and modify the configuration.
- FILE_URL：http://datax-opensource.oss-cn-hangzhou.aliyuncs.com/datax.tar.gz
- FILE_PATH：/opt/soft
- LOCK_PATH：/opt/soft
Update component, the plug-in Datax will be downloaded automatically and decompress to /opt/soft