[Doc] Update the readme content (#12500)
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README.md
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README.md
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@ -11,46 +11,40 @@ Dolphin Scheduler Official Website
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[](https://starchart.cc/apache/dolphinscheduler)
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[](README.md)
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[](README_zh_CN.md)
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## Design Features
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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`.
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## Features
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Its main objectives are as follows:
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- Highly Reliable,
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DolphinScheduler adopts a decentralized multi-master and multi-worker architecture design, which naturally supports easy expansion and high availability (not restricted by a single point of bottleneck), and its performance increases linearly with the increase of machines
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- High performance, supporting tens of millions of tasks every day
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- Support multi-tenant.
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- Cloud Native, DolphinScheduler supports multi-cloud/data center workflow management, also
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supports Kubernetes, Docker deployment and custom task types, distributed
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scheduling, with overall scheduling capability increased linearly with the
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scale of the cluster
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- Support various task types: Shell, MR, Spark, SQL (MySQL, PostgreSQL, hive, spark SQL), Python, Sub_Process, Procedure, etc.
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- Support scheduling of workflows and dependencies, manual scheduling to pause/stop/recover task, support failure task retry/alarm, recover specified nodes from failure, kill task, etc.
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- Associate the tasks according to the dependencies of the tasks in a DAG graph, which can visualize the running state of the task in real-time.
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- WYSIWYG online editing tasks
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- Support the priority of workflows & tasks, task failover, and task timeout alarm or failure.
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- Support workflow global parameters and node customized parameter settings.
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- Support online upload/download/management of resource files, etc. Support online file creation and editing.
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- Support task log online viewing and scrolling and downloading, etc.
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- Support the viewing of Master/Worker CPU load, memory, and CPU usage metrics.
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- Support 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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- Support back-filling data.
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- Support internationalization.
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- More features waiting for partners to explore...
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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`
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## What's in DolphinScheduler
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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 3 ways to create workflows:
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- Visually, create tasks by dragging and dropping tasks
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- Creating workflows by PyDolphinScheduler(Python way)
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- Creating workflows through Open API
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- Highly Reliable,
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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,
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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
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supports custom task type
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- More features waiting for partners to explore
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| Stability | Accessibility | Features | Scalability |
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|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| 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 |
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| 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. |
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| 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 | |
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## User Interface Screenshots
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<img width="1100" src="https://user-images.githubusercontent.com/15833811/197348110-1653ea32-ce07-436c-a0b8-6ac1af80aea5.png">
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@ -77,26 +71,28 @@ dolphinscheduler-dist/target/apache-dolphinscheduler-${latest.release.version}-b
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dolphinscheduler-dist/target/apache-dolphinscheduler-${latest.release.version}-src.tar.gz: Source code package of DolphinScheduler
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```
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## Thanks
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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.
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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!
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## Get Help
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1. Submit an [issue](https://github.com/apache/dolphinscheduler/issues/new/choose)
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2. [Join our slack](https://s.apache.org/dolphinscheduler-slack) and send your question to channel `#troubleshooting`
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2. [Join our slack](https://s.apache.org/dolphinscheduler-slack) and send your question to channel `#general`
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3. Send email to users@dolphinscheduler.apache.org or dev@dolphinscheduler.apache.org
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## Community
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You are very welcome to communicate with the developers and users of Dolphin Scheduler. There are two ways to find them:
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1. Join the Slack channel [Slack](https://asf-dolphinscheduler.slack.com/).
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2. Follow the [Twitter account of DolphinScheduler](https://twitter.com/dolphinschedule) and get the latest news on time.
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1. Join the Slack channel [Slack](https://asf-dolphinscheduler.slack.com/)
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2. Follow the [Twitter account of DolphinScheduler](https://twitter.com/dolphinschedule) and get the latest news on time
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## How to Contribute
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The community welcomes everyone to contribute, please refer to this page to find out more: [How to contribute](docs/docs/en/contribute/join/contribute.md).
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## Thanks
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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.
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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
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# Landscapes
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<p align="center">
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@ -109,4 +105,4 @@ DolphinScheduler enriches the <a href="https://landscape.cncf.io/?landscape=obse
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## License
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Please refer to the [LICENSE](https://github.com/apache/dolphinscheduler/blob/dev/LICENSE) file.
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Please refer to the [LICENSE](https://github.com/apache/dolphinscheduler/blob/dev/LICENSE) file
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