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README.md
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README.md
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# 简介
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### 产品介绍
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**OhMyScheduler是基于Akka架构的一款分布式调度与计算框架（对标 Alibaba SchedulerX2.0），其主要功能特性如下**：
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 [](https://github.com/KFCFans/OhMyScheduler/blob/master/LICENSE)
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* 使用简单：提供前端Web界面，允许开发者可视化地完成调度任务的管理（增、删、改、查）、任务运行状态监控和运行日志查看等功能。
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* 定时策略完善：支持CRON表达式、固定频率、固定延迟和API四种定时调度策略。
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* 执行模式丰富：支持单机、广播、Map、MapReduce四种执行模式，其中Map/MapReduce处理器能使开发者寥寥数行代码便获得集群分布式计算的能力。
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* 执行器支持广泛：支持Spring Bean、内置/外置Java类、Shell、Python等处理器，应用范围广。
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* 运维便捷：支持在线日志功能，执行器产生的日志可以在前端控制台页面实时显示，降低debug成本，极大地提高开发效率。
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* 依赖精简：最小仅依赖关系型数据库（MySQL/Oracle/MS SQLServer...），扩展依赖为MongoDB（用于存储庞大的在线日志）。
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* 高可用&高性能：调度服务器经过精心设计，一改其他调度框架基于数据库锁的策略，实现了无锁化调度。部署多个调度服务器可以同时实现高可用和性能的提升（支持无限的水平扩展）。
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* 故障转移与恢复：任务执行失败后，可根据配置的重试策略完成重试，只要执行器集群有足够的计算节点，任务就能顺利完成。
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OhMyScheduler is a powerful distributed scheduling platform and distributed computing framework based on Akka architecture.It provides you a chance to schedule job and distributed computing easily.
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### 适用场景
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* 有定时执行需求的业务场景：如每天凌晨全量同步数据、生成业务报表等。
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* 有需要全部机器一同执行的业务场景：如使用广播执行模式清理集群日志。
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* 有需要分布式处理的业务场景：比如需要更新一大批数据，单机执行耗时非常长，可以使用Map/MapReduce处理器完成任务的分发，调动整个集群加速计算。
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# Introduction
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### 同类产品对比
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| | QuartZ | xxl-job | SchedulerX 2.0 | OhMyScheduler |
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| -------------- | ------------------------ | ---------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------ |
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| 定时类型 | CRON | CRON | CRON、固定频率、固定延迟、OpenAPI | **CRON、固定频率、固定延迟、OpenAPI** |
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| 任务类型 | 内置Java | 内置Java、GLUE Java、Shell、Python等脚本 | 内置Java、外置Java（FatJar）、Shell、Python等脚本 | **内置Java、外置Java（容器）、Shell、Python等脚本** |
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| 分布式任务 | 无 | 静态分片 | MapReduce动态分片 | **MapReduce动态分片** |
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| 在线任务治理 | 不支持 | 支持 | 支持 | **支持** |
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| 日志白屏化 | 不支持 | 支持 | 不支持 | **支持** |
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| 调度方式及性能 | 基于数据库锁，有性能瓶颈 | 基于数据库锁，有性能瓶颈 | 不详 | **无锁化设计，性能强劲无上限** |
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| 报警监控 | 无 | 邮件 | 短信 | **邮件，提供接口允许开发者扩展** |
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| 系统依赖 | MySQL | MySQL | 人民币（公测期间免费，哎，帮打个广告吧） | **任意Spring Data Jpa支持的关系型数据库（MySQL、Oracle...）** |
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| DAG工作流 | 不支持 | 不支持 | 支持 | 暂不支持，有明确开发计划 |
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### Features
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- Simple to use: Provides a front-end Web interface that allows developers to visually complete the management of scheduled tasks (create, delete, update, and query), task operation status monitoring, and operation logs viewing.
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- Complete timing strategy: Support four timing scheduling strategies of CRON expression, fixed frequency, fixed delay and API.
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- Extensive execution modes: It supports four execution modes: stand-alone, broadcast, Map, and MapReduce. Among them, the Map / MapReduce processor enables developers to obtain cluster distributed computing capabilities with only a few lines of code.
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- Workflow(DAG) support: support online configuration of task dependencies, visually arrange tasks, as well as support for data transfer between upstream and downstream tasks
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- Extensive executor support: supports processors such as Spring Bean, ordinary Java objects, Shell, Python, and a wide range of applications (such as broadcast execution + Shell script to clear logs)
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- Convenient operation and maintenance: support online log function, the log generated by the actuator can be displayed on the front-end console page in real time, reduce the debugging cost, and greatly improve the development efficiency.
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- Dependency simplification: The smallest dependency-only database (MySQL / Oracle / MS SQLServer ...), the extended dependency is MongoDB (used to store huge online logs).
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- High availability & high performance: The scheduling server has been carefully designed to change the strategy of other scheduling frameworks based on database locks to achieve lock-free scheduling. Deploying multiple scheduling servers can achieve high availability and performance improvement at the same time (support unlimited horizontal expansion).
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- Failover and recovery: After the task fails to execute, the retry can be completed according to the configured retry strategy. As long as the executor cluster has enough computing nodes, the task can be successfully completed.
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### Applicable scene
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# 文档
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**[主地址](https://kfcfans.github.io/)** OR **[备用地址](https://kfcfans.gitee.io/ohmyscheduler/)**
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- Business scenarios with regular execution requirements: such as synchronizing data in full volume every morning and generating business reports.
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- There are business scenarios that require all machines to perform together: such as log cleanup.
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- There are business scenarios that require distributed processing: for example, a large amount of data needs to be updated, and the stand-alone execution takes a long time. You can use the Map / MapReduce processors to complete the task distribution and mobilize the entire cluster to speed up the calculation.
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# 参考
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>Alibaba SchedulerX 2.0
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### Comparison of similar products
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* [Akka 框架](https://yq.aliyun.com/articles/709946?spm=a2c4e.11153959.teamhomeleft.67.6a0560c9bZEnZq)：不得不说，akka-remote简化了相当大一部分的网络通讯代码。
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* [执行器架构设计](https://yq.aliyun.com/articles/704121?spm=a2c4e.11153959.teamhomeleft.97.371960c9qhB1mB)：这篇文章反而不太认同，感觉我个人的设计更符合Yarn的“架构”。
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* [MapReduce模型](https://yq.aliyun.com/articles/706820?spm=a2c4e.11153959.teamhomeleft.83.6a0560c9bZEnZq)：想法很Cool，大数据处理框架都是处理器向数据移动，但对于传统Java应用来说，数据向处理器移动也未尝不可，这样还能使框架的实现变得简单很多。
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* [广播执行](https://yq.aliyun.com/articles/716203?spm=a2c4e.11153959.teamhomeleft.40.371960c9qhB1mB)：运行清理日志脚本什么的，也太实用了8～
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| | QuartZ | xxl-job | SchedulerX 2.0 | OhMyScheduler |
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| ---------------------------------- | --------------------------------------------------------- | --------------------------------------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| Timing type | CRON | CRON | CRON, fixed frequency, fixed delay, OpenAPI | **CRON, fixed frequency, fixed delay, OpenAPI** |
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| Task type | Built-in Java | Built-in Java, GLUE Java, Shell, Python and other scripts | Built-in Java, external Java (FatJar), Shell, Python and other scripts | **Built-in Java, external Java (container), Shell, Python and other scripts** |
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| Distributed task | no | Static sharding | MapReduce dynamic sharding | **MapReduce dynamic sharding** |
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| Online task governance | not support | support | support | **support** |
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| Log blanking | not support | support | not support | **support** |
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| Scheduling methods and performance | Based on database lock, there is a performance bottleneck | Based on database lock, there is a performance bottleneck | Unknown | **Lock-free design, powerful performance without upper limit** |
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| Alarm monitoring | no | mail | SMS | **Email, providing an interface to allow developers to customize development** |
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| System dependence | MySQL | MySQL | Renminbi (free during public beta, hey, help to advertise) | **Any relational database (MySQL, Oracle ...) supported by Spring Data Jpa** |
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| DAG workflow | not support | not support | support | **support** |
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# 后记
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* 产品永久开源（Apache License, Version 2.0），免费使用，且目前开发者@KFCFans有充足的时间进行项目维护和提供无偿技术支持（All In 了解一下），欢迎各位试用！
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* 欢迎共同参与本项目的贡献，PR和Issue都大大滴欢迎（求求了）～
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* 觉得还不错的话，可以点个Star支持一下哦～ =￣ω￣=
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* 联系方式@KFCFans -> `tengjiqi@gmail.com`
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# Document
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**[GitHub Wiki](https://github.com/KFCFans/OhMyScheduler/wiki)**
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**[中文文档](https://www.yuque.com/ohmyscheduler/product)**
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# Others
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- The product is permanently open source (Apache License, Version 2.0), free to use, and the current developer @KFCFans has sufficient time to maintain the project and provide free technical support (All of my time), welcome to try!
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- Welcome to participate in the contribution of this project, PR and Issue are greatly welcome (please) ~
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- If you feel pretty good, you can give it a star to support it ~ = ￣ω￣ =
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- Need some help or have some advice? Welcome to contact Developer @KFCFans-> `tengjiqi@gmail.com`
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54
README_zhCN.md
Normal file
54
README_zhCN.md
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@ -0,0 +1,54 @@
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 [](https://github.com/KFCFans/OhMyScheduler/blob/master/LICENSE)
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OhMyScheduler是基于Akka架构的一款分布式调度与计算框架（对标 Alibaba SchedulerX2.0）。OhMyScheduler能让您轻松完成作业的调度与繁杂任务的分布式计算。
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# 简介
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### 主要特性
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* 使用简单：提供前端Web界面，允许开发者可视化地完成调度任务的管理（增、删、改、查）、任务运行状态监控和运行日志查看等功能。
|
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* 定时策略完善：支持CRON表达式、固定频率、固定延迟和API四种定时调度策略。
|
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* 执行模式丰富：支持单机、广播、Map、MapReduce四种执行模式，其中Map/MapReduce处理器能使开发者寥寥数行代码便获得集群分布式计算的能力。
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* DAG工作流支持：支持在线配置任务依赖关系，可视化得对任务进行编排，同时还支持上下游任务间的数据传递
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* 执行器支持广泛：支持Spring Bean、内置/外置Java类、Shell、Python等处理器，应用范围广。
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* 运维便捷：支持在线日志功能，执行器产生的日志可以在前端控制台页面实时显示，降低debug成本，极大地提高开发效率。
|
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* 依赖精简：最小仅依赖关系型数据库（MySQL/Oracle/MS SQLServer...），扩展依赖为MongoDB（用于存储庞大的在线日志）。
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* 高可用&高性能：调度服务器经过精心设计，一改其他调度框架基于数据库锁的策略，实现了无锁化调度。部署多个调度服务器可以同时实现高可用和性能的提升（支持无限的水平扩展）。
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* 故障转移与恢复：任务执行失败后，可根据配置的重试策略完成重试，只要执行器集群有足够的计算节点，任务就能顺利完成。
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### 适用场景
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* 有定时执行需求的业务场景：如每天凌晨全量同步数据、生成业务报表等。
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* 有需要全部机器一同执行的业务场景：如使用广播执行模式清理集群日志。
|
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* 有需要分布式处理的业务场景：比如需要更新一大批数据，单机执行耗时非常长，可以使用Map/MapReduce处理器完成任务的分发，调动整个集群加速计算。
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### 同类产品对比
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| | QuartZ | xxl-job | SchedulerX 2.0 | OhMyScheduler |
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| -------------- | ------------------------ | ---------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------ |
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| 定时类型 | CRON | CRON | CRON、固定频率、固定延迟、OpenAPI | **CRON、固定频率、固定延迟、OpenAPI** |
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| 任务类型 | 内置Java | 内置Java、GLUE Java、Shell、Python等脚本 | 内置Java、外置Java（FatJar）、Shell、Python等脚本 | **内置Java、外置Java（容器）、Shell、Python等脚本** |
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| 分布式任务 | 无 | 静态分片 | MapReduce动态分片 | **MapReduce动态分片** |
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| 在线任务治理 | 不支持 | 支持 | 支持 | **支持** |
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| 日志白屏化 | 不支持 | 支持 | 不支持 | **支持** |
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| 调度方式及性能 | 基于数据库锁，有性能瓶颈 | 基于数据库锁，有性能瓶颈 | 不详 | **无锁化设计，性能强劲无上限** |
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| 报警监控 | 无 | 邮件 | 短信 | **邮件，提供接口允许开发者扩展** |
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| 系统依赖 | MySQL | MySQL | 人民币（公测期间免费，哎，帮打个广告吧） | **任意Spring Data Jpa支持的关系型数据库（MySQL、Oracle...）** |
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| DAG工作流 | 不支持 | 不支持 | 支持 | **支持** |
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# 文档
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**[中文文档](https://www.yuque.com/ohmyscheduler/product)** OR **[备用地址，内容可能更新不及时](https://kfcfans.gitee.io/ohmyscheduler/)**
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PS：感谢文档翻译平台[breword](https://www.breword.com/)对本项目英文文档翻译做出的巨大贡献！
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# 参考
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>Alibaba SchedulerX 2.0
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* [Akka 框架](https://yq.aliyun.com/articles/709946?spm=a2c4e.11153959.teamhomeleft.67.6a0560c9bZEnZq)：不得不说，akka-remote简化了相当大一部分的网络通讯代码。
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* [执行器架构设计](https://yq.aliyun.com/articles/704121?spm=a2c4e.11153959.teamhomeleft.97.371960c9qhB1mB)：这篇文章反而不太认同，感觉我个人的设计更符合Yarn的“架构”。
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* [MapReduce模型](https://yq.aliyun.com/articles/706820?spm=a2c4e.11153959.teamhomeleft.83.6a0560c9bZEnZq)：想法很Cool，大数据处理框架都是处理器向数据移动，但对于传统Java应用来说，数据向处理器移动也未尝不可，这样还能使框架的实现变得简单很多。
|
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* [广播执行](https://yq.aliyun.com/articles/716203?spm=a2c4e.11153959.teamhomeleft.40.371960c9qhB1mB)：运行清理日志脚本什么的，也太实用了8～
|
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# 后记
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* 产品永久开源（Apache License, Version 2.0），免费使用，且目前开发者@KFCFans有充足的时间进行项目维护和提供无偿技术支持（All In 了解一下），欢迎各位试用！
|
||||
* 欢迎共同参与本项目的贡献，PR和Issue都大大滴欢迎（求求了）～
|
||||
* 觉得还不错的话，可以点个Star支持一下哦～ =￣ω￣=
|
||||
* 联系方式@KFCFans -> `tengjiqi@gmail.com`
|
||||
@ -69,4 +69,13 @@ public class TestWorkflow {
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System.out.println(ohMyClient.runWorkflow(1L));
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}
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@Test
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public void testStopWorkflowInstance() throws Exception {
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System.out.println(ohMyClient.stopWorkflowInstance(148003202598436928L));
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}
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@Test
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public void testFetchWfInstanceInfo() throws Exception {
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System.out.println(ohMyClient.fetchWorkflowInstanceInfo(148003202598436928L));
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}
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}
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@ -147,8 +147,8 @@ public class OpenAPIController {
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/* ************* Workflow Instance 区 ************* */
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@PostMapping(OpenAPIConstant.STOP_WORKFLOW_INSTANCE)
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public ResultDTO<Void> stopWorkflowInstance(Long wfInstance, Long appId) {
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workflowInstanceService.stopWorkflowInstance(wfInstance, appId);
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public ResultDTO<Void> stopWorkflowInstance(Long wfInstanceId, Long appId) {
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workflowInstanceService.stopWorkflowInstance(wfInstanceId, appId);
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return ResultDTO.success(null);
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}
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@PostMapping(OpenAPIConstant.FETCH_WORKFLOW_INSTANCE_INFO)
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BIN
others/images/oms-logo.png
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BIN
others/images/oms-logo.png
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