Dolphin Scheduler Official Website dolphinscheduler.apache.org

Design Features

DolphinScheduler is a distributed and extensible workflow scheduler platform with powerful DAG visual interfaces, dedicated to solving complex job dependencies in the data pipeline and providing various types of jobs available out of the box.

The key features for DolphinScheduler are as follows:

• Easy to deploy, we provide 4 ways to deploy, such as Standalone deployment,Cluster deployment,Docker / Kubernetes deployment and Rainbond deployment

• Easy to use, there are four ways to create workflows:

  • Visually, create tasks by dragging and dropping tasks
  • PyDolphinScheduler, Creating workflows via Python API, aka workflow-as-code
  • Yaml definition, mapping yaml into workflow(have to install PyDolphinScheduler currently)
  • Open API, Creating workflows

• Highly Reliable, DolphinScheduler uses a decentralized multi-master and multi-worker architecture, which naturally supports horizontal scaling and high availability

• High performance, its performance is N times faster than other orchestration platform and it can support tens of millions of tasks per day

• Supports multi-tenancy

• Supports various task types: Shell, MR, Spark, SQL (MySQL, PostgreSQL, Hive, Spark SQL), Python, Procedure, Sub_Workflow, Http, K8s, Jupyter, MLflow, SageMaker, DVC, Pytorch, Amazon EMR, etc

• Orchestrating workflows and dependencies, you can pause/stop/recover task any time, failed tasks can be set to automatically retry

• Visualizing the running state of the task in real-time and seeing the task runtime log

• What you see is what you get when you edit the task on the UI

• Backfill can be operated on the UI directly

• Perfect project, resource, data source-level permission control

• Displaying workflow history in tree/Gantt chart, as well as statistical analysis on the task status & process status in each workflow

• Supports internationalization

• Cloud Native, DolphinScheduler supports orchestrating multi-cloud/data center workflow, and supports custom task type

• More features waiting for partners to explore

1347a8f94 ([chore] Separate Python API into another repository (#12779))

Stability	Accessibility	Features	Scalability
Decentralized multi-master and multi-worker	Visualization of workflow key information, such as task status, task type, retry times, task operation machine information, visual variables, and so on at a glance.	Support pause, recover operation	Support customized task types
support HA	Visualization of all workflow operations, dragging tasks to draw DAGs, configuring data sources and resources. At the same time, for third-party systems, provide API mode operations.	Users on DolphinScheduler can achieve many-to-one or one-to-one mapping relationship through tenants and Hadoop users, which is very important for scheduling large data jobs.	The scheduler supports distributed scheduling, and the overall scheduling capability will increase linearly with the scale of the cluster. Master and Worker support dynamic adjustment.
Overload processing: By using the task queue mechanism, the number of schedulable tasks on a single machine can be flexibly configured. Machine jam can be avoided with high tolerance to numbers of tasks cached in task queue.	One-click deployment	Support traditional shell tasks, and big data platform task scheduling: MR, Spark, SQL (MySQL, PostgreSQL, hive, spark SQL), Python, Procedure, Sub_Process

User Interface Screenshots

QuickStart in Docker

Please refer the official website document: QuickStart in Docker

QuickStart in Kubernetes

Please refer to the official website document: QuickStart in Kubernetes

How to Build

./mvnw clean install -Prelease

Artifact:

dolphinscheduler-dist/target/apache-dolphinscheduler-${latest.release.version}-bin.tar.gz: Binary package of DolphinScheduler
dolphinscheduler-dist/target/apache-dolphinscheduler-${latest.release.version}-src.tar.gz: Source code package of DolphinScheduler

Thanks

DolphinScheduler is based on a lot of excellent open-source projects, such as Google guava, grpc, netty, quartz, and many open-source projects of Apache and so on. We would like to express our deep gratitude to all the open-source projects used in Dolphin Scheduler. We hope that we are not only the beneficiaries of open-source, but also give back to the community. Besides, we hope everyone who have the same enthusiasm and passion for open source could join in and contribute to the open-source community!

Get Help

1. Submit an issue
2. Join our slack and send your question to channel #troubleshooting

Community

You are very welcome to communicate with the developers and users of Dolphin Scheduler. There are two ways to find them:

1. Join the Slack channel Slack.
2. Follow the Twitter account of DolphinScheduler and get the latest news on time.

How to Contribute

The community welcomes everyone to contribute, please refer to this page to find out more: How to contribute.

Landscapes

  

DolphinScheduler enriches the CNCF CLOUD NATIVE Landscape.

License

Please refer to the LICENSE file.