EasyScheduler

Introduction: Easy Scheduler is a distributed workflow task scheduling system, which mainly resolve the problem of "complicated task dependencies but cannot directly monitor the health status of tasks". Easy Scheduler assembles tasks in a DAG diagram and can monitor the running status of tasks in real time. Meanwhile, It supports operations such as retry, recovery failure from the specified node, pause and kill tasks.中文描述:Easy Scheduler 是一个分布式工作流任务调度系统,主要解决"错综复杂的任务依赖关系,而不能直观监控任务健康状态等问题"。Easy Scheduler 以 DAG 流式的方式将 Task 组装起来,并可实时监控任务的运行状态,同时支持重试、从指定节点恢复失败、暂停及 Kill 任务等操作。EasyScheduler 由在工作流调度方面工作多年的多位小伙伴研发而成,致力于成为大数据平台的中流砥柱,使调度变得更加容易,更可以从其中文名“易调度”看出我们的初衷,如果你对目前市面上的调度不够满意,非常欢迎使用易调度,欢迎大家加入进来,提出需求,也欢迎贡献代码
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Easy Scheduler for Big Data

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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. " Supports traditional shell tasks, while supporting large data platform task scheduling: MR, Spark, SQL (mysql, postgresql, hive, sparksql), Python, Procedure, Sub_Process 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

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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.

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