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.
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`.
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 various task types: Shell, MR, Spark, SQL (MySQL, PostgreSQL, hive, spark SQL), Python, Sub_Process, Procedure, etc.
- 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.
- Support the priority of workflows & tasks, task failover, and task timeout alarm or failure.
- Support workflow global parameters and node customized parameter settings.
- Support online upload/download/management of resource files, etc. Support online file creation and editing.
- Support task log online viewing and scrolling and downloading, etc.
- Have implemented 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 displaying workflow history in tree/Gantt chart, as well as statistical analysis on the task status& process status in each workflow.
- Support back-filling data.
- Support multi-tenant.
- Support internationalization.
- There are more waiting for partners to explore...
- More features waiting for partners to explore...
### What's in DolphinScheduler
### What's in DolphinScheduler
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 | |
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 | |
Please referer the official website document:[[QuickStart in Docker](https://dolphinscheduler.apache.org/en-us/docs/1.3.4/user_doc/docker-deployment.html)]
### Recent R&D plan
The work plan of Dolphin Scheduler: [R&D plan](https://github.com/apache/incubator-dolphinscheduler/projects/1), which `In Develop` card shows the features that are currently being developed and TODO card lists what needs to be done(including feature ideas).
### How to contribute
Welcome to participate in contributing, please refer to this website to find out more: [[How to contribute](https://dolphinscheduler.apache.org/en-us/docs/development/contribute.html)]
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!
DolphinScheduler 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 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
1. Submit an [[issue](https://github.com/apache/incubator-dolphinscheduler/issues/new/choose)]
1. Subscribe to the mail list: https://dolphinscheduler.apache.org/en-us/docs/development/subscribe.html, then email dev@dolphinscheduler.apache.org
### How to Contribute
The community welcomes everyone to participate in contributing, please refer to this website to find out more: [[How to contribute](https://dolphinscheduler.apache.org/en-us/community/development/contribute.html)]
### License
Please refer to the [LICENSE](https://github.com/apache/incubator-dolphinscheduler/blob/dev/LICENSE) file.
logger.error("user {} didn't has permission of {}: {}",user.getUserName(),authorizationType.getDescp(),unauthorizedList);
thrownewRuntimeException(String.format("user %s didn't has permission of %s %s",user.getUserName(),authorizationType.getDescp(),unauthorizedList.get(0)));
if(CollectionUtils.isNotEmpty(unauthorizedList)){
logger.error("user {} doesn't have permission of {}: {}",user.getUserName(),authorizationType.getDescp(),unauthorizedList);
thrownewServiceException(String.format("user %s doesn't have permission of %s %s",user.getUserName(),authorizationType.getDescp(),unauthorizedList.get(0)));
@ -85,7 +91,8 @@ public class ZookeeperOperator implements InitializingBean {
privateCuratorFrameworkbuildClient(){
logger.info("zookeeper registry center init, server lists is: {}.",zookeeperConfig.getServerList());
CuratorFrameworkFactory.Builderbuilder=CuratorFrameworkFactory.builder().ensembleProvider(newDefaultEnsembleProvider(checkNotNull(zookeeperConfig.getServerList(),"zookeeper quorum can't be null")))
lenboo
4 years ago