Dolphin Scheduler Official Website dolphinscheduler.apache.org
Dolphin Scheduler for Big Data
Dolphin Scheduler is a distributed and easy-to-extend visual DAG workflow scheduling system. It dedicates to solving the complex dependencies in data processing to make the scheduling system out of the box for the data processing process.
Its main objectives are as follows:
- 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.
- Support many task types: Shell, MR, Spark, SQL (MySQL, PostgreSQL, hive, spark SQL), Python, Sub_Process, Procedure, etc.
- Support process scheduling, dependency scheduling, manual scheduling, manual pause/stop/recovery, support for failed retry/alarm, recovery from specified nodes, Kill task, etc.
- Support the priority of process & task, task failover, and task timeout alarm or failure.
- Support process global parameters and node custom parameter settings.
- Support online upload/download of resource files, management, etc. Support online file creation and editing.
- Support task log online viewing and scrolling, online download log, etc.
- Implement cluster HA, decentralize Master cluster and Worker cluster through Zookeeper.
- Support the viewing of Master/Worker CPU load, memory, and CPU usage metrics.
- Support presenting tree or Gantt chart of workflow history as well as the statistics results of task & process status in each workflow.
- Support backfilling data.
- Support multi-tenant.
- Support internationalization.
- There are more waiting for partners to explore...
| Stability | Easy to use | Features | Scalability |
|---|---|---|---|
| Decentralized multi-master and multi-worker | Visualization process defines key information such as task status, task type, retry times, task running machine, visual variables, and so on at a glance. | Support pause, recover operation | Support custom task types |
| HA is supported by itself | All process definition operations are visualized, dragging tasks to draw DAGs, configuring data sources and resources. At the same time, for third-party systems, the API mode operation is provided. | Users on Dolphin Scheduler 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 uses distributed scheduling, and the overall scheduling capability will increase linearly with the scale of the cluster. Master and Worker support dynamic online and offline. |
| Overload processing: 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 |
The work plan of Dolphin Scheduler: R&D plan, which In Develop card shows the features that are currently being developed and TODO card lists what needs to be done(including feature ideas).
Welcome to participate in contributing, please refer to this website to find out more: [How to contribute]
./mvnw clean install -PreleaseArtifact:
dolphinscheduler-dist/target/apache-dolphinscheduler-incubating-${latest.release.version}-dolphinscheduler-bin.tar.gz: Binary package of DolphinScheduler
dolphinscheduler-dist/target/apache-dolphinscheduler-incubating-${latest.release.version}-src.zip: Source code package of DolphinScheduler
Dolphin Scheduler is based on a lot of excellent open-source projects, such as google guava, guice, grpc, netty, ali bonecp, 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 which contribute to making the dream of Dolphin Scheduler comes true. We hope that we are not only the beneficiaries of open-source, but also give back to the community. Besides, we expect the partners who have the same passion and conviction to open-source will join in and contribute to the open-source community!
- Submit an issue
- Subscribe to the mail list: https://dolphinscheduler.apache.org/en-us/docs/development/subscribe.html, then email dev@dolphinscheduler.apache.org
Please refer to the LICENSE file.