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* move updateTaskState into try/catch block in case of exception * fix NPE * using conf.getInt instead of getString * for AbstractZKClient, remove the log, for it will print the same log message in createZNodePath. for AlertDao, correct the spelling. * duplicate * refactor getTaskWorkerGroupId * add friendly log * update hearbeat thread num = 1 * fix the bug when worker execute task using queue. and remove checking Tenant user anymore in TaskScheduleThread * 1. move verifyTaskInstanceIsNull after taskInstance 2. keep verifyTenantIsNull/verifyTaskInstanceIsNull clean and readable * fix the message * delete before check to avoid KeeperException$NoNodeException * fix the message * check processInstance state before delete tenant * check processInstance state before delete worker group * refactor * merge api constants into common constatns * update the resource perm * update the dataSource perm * fix CheckUtils.checkUserParams method * update AlertGroupService, extends from BaseService, remove duplicate methods * refactor * modify method name * add hasProjectAndPerm method * using checkProject instead of getResultStatus * delete checkAuth method, using hasProjectAndPerm instead. * correct spelling * add transactional for deleteWorkerGroupById * add Transactional for deleteProcessInstanceById method * change sqlSessionTemplate singleton * change sqlSessionTemplate singleton and reformat code * fix unsuitable error message * update shutdownhook methods * fix worker log bug * fix api server debug mode bug * upgrade zk version * delete this line ,for zkClient.close() will do the whole thing * fix master server shutdown error * degrade zk version and add FourLetterWordMain class * fix PathChildrenCache not close * add Transactional for createSession method * add more message for java-doc * delete App, let spring manage connectionFactory * add license * add class Application for test support * refactor masterServer and workerServer * add args * fix the spring transaction not work bug * remove author * delete @Bean annotation * rename application.properties to application-dao.properties |
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Easy Scheduler
Easy Scheduler for Big Data
Design features:
A distributed and easy-to-expand visual DAG workflow scheduling system. Dedicated to solving the complex dependencies in data processing, making the scheduling system out of the box for data processing.
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 task in real time.
- Support for many task types: Shell, MR, Spark, SQL (mysql, postgresql, hive, sparksql), 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 process priority, task priority and task failover and task timeout alarm/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 online viewing of
Master/Workercpu load, memory - Support process running history tree/gantt chart display, support task status statistics, process status statistics
- Support backfilling data
- Support multi-tenant
- Support internationalization
- There are more waiting partners to explore
What's in Easy Scheduler
| 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 easyscheduler 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: Task queue mechanism, the number of schedulable tasks on a single machine can be flexibly configured, when too many tasks will be cached in the task queue, will not cause machine jam. | One-click deployment | Supports traditional shell tasks, and also support big data platform task scheduling: MR, Spark, SQL (mysql, postgresql, hive, sparksql), Python, Procedure, Sub_Process |
System partial screenshot
Document
More documentation please refer to [EasyScheduler online documentation]
Recent R&D plan
Work plan of Easy Scheduler: R&D plan, where In Develop card is the features of 1.1.0 version , TODO card is to be done (including feature ideas)
How to contribute code
Welcome to participate in contributing code, please refer to the process of submitting the code: [How to contribute code]
Thanks
Easy Scheduler uses a lot of excellent open source projects, such as google guava, guice, grpc, netty, ali bonecp, quartz, and many open source projects of apache, etc. It is because of the shoulders of these open source projects that the birth of the Easy Scheduler is possible. We are very grateful for all the open source software used! We also hope that we will not only be the beneficiaries of open source, but also be open source contributors, so we decided to contribute to easy scheduling and promised long-term updates. We also hope that partners who have the same passion and conviction for open source will join in and contribute to open source!
Get Help
- Submit an issue
- Mail list: dev@dolphinscheduler.apache.org. Mail to dev-subscribe@dolphinscheduler.apache.org, follow the reply to subscribe the mail list.
- Contact WeChat group manager, ID 510570367. This is for Mandarin(CN) discussion.
License
Please refer to LICENSE file.