658 lines
23 KiB
Java
658 lines
23 KiB
Java
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Easyscheduler简介
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准备工作
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系统使用手册
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系统架构设计
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开发环境搭建
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项目目录结构
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系统功能模块
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路由和状态管理
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规范
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接口
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扩展开发
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后端开发文档
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<ul class="articles">
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开发环境搭建
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</a>
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<li class="chapter " data-level="1.7.2" data-path="任务插件开发.html">
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<a href="任务插件开发.html#任务插件开发">
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自定义任务插件文档
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</a>
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<li class="chapter " data-level="1.8" >
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<span>
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系统版本升级文档
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版本升级
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<li class="chapter " data-level="1.9" >
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<span>
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历次版本发布内容
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<ul class="articles">
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1.0.2 release
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<li class="chapter " data-level="1.9.2" data-path="1.0.1-release.html">
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1.0.1 release
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[1.0.0 release 正式开源]
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本书使用 GitBook 发布
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<!-- Title -->
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<h1>
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<i class="fa fa-circle-o-notch fa-spin"></i>
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<a href="." >Easyscheduler简介</a>
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</h1>
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<section class="normal markdown-section">
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<h1 id="easy-scheduler">Easy Scheduler</h1>
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<p><a href="https://www.apache.org/licenses/LICENSE-2.0.html" target="_blank"><img src="https://img.shields.io/badge/license-Apache%202-4EB1BA.svg" alt="License"></a></p>
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<blockquote>
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<p>Easy Scheduler for Big Data</p>
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</blockquote>
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<p><strong>设计特点：</strong> 一个分布式易扩展的可视化DAG工作流任务调度系统。致力于解决数据处理流程中错综复杂的依赖关系，使调度系统在数据处理流程中<code>开箱即用</code>。
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其主要目标如下：</p>
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<ul>
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<li>以DAG图的方式将Task按照任务的依赖关系关联起来，可实时可视化监控任务的运行状态</li>
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<li>支持丰富的任务类型：Shell、MR、Spark、SQL(mysql、postgresql、hive、sparksql),Python,Sub_Process、Procedure等</li>
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<li>支持工作流定时调度、依赖调度、手动调度、手动暂停/停止/恢复，同时支持失败重试/告警、从指定节点恢复失败、Kill任务等操作</li>
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<li>支持工作流优先级、任务优先级及任务的故障转移及任务超时告警/失败</li>
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<li>支持工作流全局参数及节点自定义参数设置</li>
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<li>支持资源文件的在线上传/下载，管理等，支持在线文件创建、编辑</li>
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<li>支持任务日志在线查看及滚动、在线下载日志等</li>
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<li>实现集群HA，通过Zookeeper实现Master集群和Worker集群去中心化</li>
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<li>支持对<code>Master/Worker</code> cpu load，memory，cpu在线查看</li>
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<li>支持工作流运行历史树形/甘特图展示、支持任务状态统计、流程状态统计</li>
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<li>支持补数</li>
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<li>支持多租户</li>
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<li>支持国际化</li>
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<li>还有更多等待伙伴们探索</li>
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</ul>
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<h3 id="与同类调度系统的对比">与同类调度系统的对比</h3>
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<p><img src="http://geek.analysys.cn/static/upload/47/2019-03-01/9609ca82-cf8b-4d91-8dc0-0e2805194747.jpeg" alt="调度系统对比"></p>
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<h3 id="系统部分截图">系统部分截图</h3>
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<p><img src="http://geek.analysys.cn/static/upload/221/2019-03-29/0a9dea80-fb02-4fa5-a812-633b67035ffc.jpeg" alt=""></p>
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<p><img src="http://geek.analysys.cn/static/upload/221/2019-04-01/83686def-a54f-4169-8cae-77b1f8300cc1.png" alt=""></p>
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<p><img src="http://geek.analysys.cn/static/upload/221/2019-03-29/83c937c7-1793-4d7a-aa28-b98460329fe0.jpeg" alt=""></p>
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<h3 id="文档">文档</h3>
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<ul>
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<li><p><a href="https://analysys.github.io/easyscheduler_docs_cn/后端部署文档.html" target="_blank">后端部署文档</a></p>
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</li>
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<li><p><a href="https://analysys.github.io/easyscheduler_docs_cn/前端部署文档.html" target="_blank">前端部署文档</a></p>
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</li>
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<li><p><a href="https://analysys.github.io/easyscheduler_docs_cn/系统使用手册.html?_blank" title="系统使用手册" target="_blank"><strong>使用手册</strong></a> </p>
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</li>
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<li><p><a href="https://analysys.github.io/easyscheduler_docs_cn/升级文档.html?_blank" title="升级文档" target="_blank"><strong>升级文档</strong></a> </p>
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</li>
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<li><p><a href="http://52.82.13.76:8888" target="_blank">我要体验</a> 普通用户登录：demo/demo123</p>
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</li>
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</ul>
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<p>更多文档请参考 <a href="https://analysys.github.io/easyscheduler_docs_cn/" target="_blank">easyscheduler中文在线文档</a></p>
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<h3 id="感谢">感谢</h3>
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<ul>
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<li>Easy Scheduler使用了很多优秀的开源项目，比如google的guava、guice、grpc，netty，ali的bonecp，quartz，以及apache的众多开源项目等等，
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正是由于站在这些开源项目的肩膀上，才有Easy Scheduler的诞生的可能。对此我们对使用的所有开源软件表示非常的感谢！我们也希望自己不仅是开源的受益者，也能成为开源的
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贡献者，于是我们决定把易调度贡献出来，并承诺长期维护。也希望对开源有同样热情和信念的伙伴加入进来，一起为开源献出一份力！</li>
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</ul>
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<h3 id="帮助">帮助</h3>
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<p>The fastest way to get response from our developers is to submit issues, or add our wechat : 510570367</p>
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</section>
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