Currently, our Python API code is a module in apache/dolphinscheduler codebase, each time users change Python API code, they need to run all requests CI check for dolphinscheduler and Python API, But if the user does only change Python code, it could be merged if Python API CI pass and do not dependent on others CI. Besides, we release Python API as the same version of dolphinscheduler. It is easy for user to match Python API version. But when Python API does not change any code, but dolphinscheduler release a bugfix version, Python API has to release the new version to match dolphinscheduler. This happened when we released Python API 2.0.6 and 2.0.7. 2.0.6 and 2.0.7 is bugfix version, and Python API does not change any code, so the PyPI package is the same. Separate Python API also makes our code more sense, we will have more distinguished code in dolphinscheduler and Python API new repository. Have separate issue tracker and changelog for information to users. ref PR in other repository: apache/dolphinscheduler-sdk-python#1 see more detail in mail thread: https://lists.apache.org/thread/4z7l5l54c4d81smjlk1n8nq380p9f0oo |
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| dolphinscheduler-alert | ||
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| dolphinscheduler-api | ||
| dolphinscheduler-api-test | ||
| dolphinscheduler-bom | ||
| dolphinscheduler-common | ||
| dolphinscheduler-dao | ||
| dolphinscheduler-data-quality | ||
| dolphinscheduler-datasource-plugin | ||
| dolphinscheduler-dist | ||
| dolphinscheduler-e2e | ||
| dolphinscheduler-master | ||
| dolphinscheduler-meter | ||
| dolphinscheduler-microbench | ||
| dolphinscheduler-registry | ||
| dolphinscheduler-remote | ||
| dolphinscheduler-scheduler-plugin | ||
| dolphinscheduler-service | ||
| dolphinscheduler-spi | ||
| dolphinscheduler-standalone-server | ||
| dolphinscheduler-task-plugin | ||
| dolphinscheduler-tools | ||
| dolphinscheduler-ui | ||
| dolphinscheduler-worker | ||
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| .licenserc.yaml | ||
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| CONTRIBUTING.md | ||
| LICENSE | ||
| NOTICE | ||
| README.md | ||
| README_zh_CN.md | ||
| lombok.config | ||
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README.md
Dolphin Scheduler Official Website dolphinscheduler.apache.org
Features
Apache DolphinScheduler is the modern data workflow orchestration platform with powerful user interface, dedicated to solving complex task dependencies in the data pipeline and providing various types of jobs available out of the box
The key features for DolphinScheduler are as follows:
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Easy to deploy, we provide 4 ways to deploy, such as Standalone deployment,Cluster deployment,Docker / Kubernetes deployment and Rainbond deployment
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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
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Highly Reliable, DolphinScheduler uses a decentralized multi-master and multi-worker architecture, which naturally supports horizontal scaling and high availability
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High performance, its performance is N times faster than other orchestration platform and it can support tens of millions of tasks per day
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Supports multi-tenancy
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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
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Orchestrating workflows and dependencies, you can pause/stop/recover task any time, failed tasks can be set to automatically retry
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Visualizing the running state of the task in real-time and seeing the task runtime log
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What you see is what you get when you edit the task on the UI
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Backfill can be operated on the UI directly
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Perfect project, resource, data source-level permission control
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Displaying workflow history in tree/Gantt chart, as well as statistical analysis on the task status & process status in each workflow
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Supports internationalization
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Cloud Native, DolphinScheduler supports orchestrating multi-cloud/data center workflow, and supports custom task type
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More features waiting for partners to explore
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
Get Help
- Submit an issue
- Join our slack and send your question to channel
#general - Send email to users@dolphinscheduler.apache.org or dev@dolphinscheduler.apache.org
Community
You are very welcome to communicate with the developers and users of Dolphin Scheduler. There are two ways to find them:
- Join the Slack channel Slack
- 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.
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 DolphinScheduler. 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
Landscapes
DolphinScheduler enriches the CNCF CLOUD NATIVE Landscape.
License
Please refer to the LICENSE file




