分布式调度框架。
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 
samz406 701495116f misspell words (#817) 5 years ago
..
images update documents (#740) 5 years ago
1.0.1-release.md update documents (#740) 5 years ago
1.0.2-release.md refactor zkClient; update documents (#683) 5 years ago
1.0.3-release.md refactor zkClient; update documents (#683) 5 years ago
1.0.4-release.md update documents (#740) 5 years ago
1.0.5-release.md update documents (#740) 5 years ago
1.1.0-release.md refactor zkClient; update documents (#683) 5 years ago
EasyScheduler Proposal.md misspell words (#817) 5 years ago
EasyScheduler-FAQ.md update documents (#740) 5 years ago
README.md update documents (#740) 5 years ago
SUMMARY.md update documents (#740) 5 years ago
architecture-design.md update markdown docs which can not display images normally (#806) 5 years ago
backend-deployment.md scripts name standardization (#813) 5 years ago
backend-development.md update documents (#740) 5 years ago
book.json update documents (#740) 5 years ago
frontend-deployment.md update documents (#740) 5 years ago
frontend-development.md update documents (#740) 5 years ago
quick-start.md update documents (#740) 5 years ago
system-manual.md update documents (#740) 5 years ago
upgrade.md scripts name standardization (#813) 5 years ago

README.md

Easy Scheduler

License Total Lines

Easy Scheduler for Big Data

Stargazers over time

EN doc CN doc

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/Worker cpu 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

image

image

image

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

The fastest way to get response from our developers is to submit issues, or add our wechat : 510570367

License

Please refer to LICENSE file.