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Wanted: Who is using DolphinScheduler #57

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boandai opened this issue Apr 15, 2019 · 138 comments
Open

Wanted: Who is using DolphinScheduler #57

boandai opened this issue Apr 15, 2019 · 138 comments

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@boandai
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boandai commented Apr 15, 2019

Who is using DolphinScheduler

Sincerely thank everyone who constantly keeps on using and supporting DolphinScheduler. We will try our best to make DolphinScheduler better and make the DolphinScheduler community and ecology more prosperous.

The original intention of this issue

  1. We’d like to listen to the community to make DolphinScheduler better.
  2. We want to attract more partners to contribute to DolphinScheduler.
  3. Learn more about the practical use scenarios of DolphinScheduler to facilitate the next step of planning.

What we expect from you

Please submit a comment in this issue to include the following infomation:

your company, school or organization, and homepage
your city and country.
your contact info: blog, email, twitter (at least one).
for what business scenario do you use DolphinScheduler.

You can refer to the following sample answer:

* Organization: xueqiu
* Location: Beijing, China
* Contact: bianyulong@163.com
* Scenario: Data task and ETL scheduling platform
* WeChat/Slack:
* Logo Url:

Thanks again for your participation ! Your support is the motivation for us to move forward.
DolphinScheduler Community

@sancong
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sancong commented Apr 15, 2019

  • Organization: IdeaWin
  • Location: Xi'an, China
  • Contact: 619019206@qq.com
  • Scenario: used for cloud computing platform, process scheduling and scheduling of tasks

  • 组织:IdeaWin
  • 地点:中国西安
  • 联系方式:619019206@qq.com
  • 场景:用于云计算平台,进行任务的流程编排和调度

@ocean-zhc
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ocean-zhc commented Apr 15, 2019

  • Organization: Aisino
  • Location: Hefei, China
  • Contact: zhanghc0532@gmail.com
  • Scenario: Visual management and scheduling for various tasks of the big data platform

  • 组织:Aisino
  • 地点:中国合肥
  • 联系方式:zhanghc0532@gmail.com
  • 场景:用于大数据平台各类任务的可视化管理与调度

@yangqinlong
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yangqinlong commented Apr 16, 2019

Organization: DataBuring
Location: Beijing, China
Contact: yqlong000@163.com
Scenario: for big data platform ETL processing


组织:DataBuring
地点:中国北京
联系方式:yqlong000@163.com
场景:用于大数据平台ETL处理

@allantaylor81
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allantaylor81 commented Apr 18, 2019

Visual management and scheduling for various tasks of big data platform


用于大数据平台各类任务的可视化管理与调度

@livionlj
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livionlj commented Apr 18, 2019

Organization: chinasoft
Location: Beijing, China
Contact: 631709547@qq.com
Scenario: Visual scheduling and task processing for high-concurrency environments in big data platforms


组织:chinasoft
地点:中国北京
联系方式:631709547@qq.com
场景:用于大数据平台高并发环境的可视化调度及任务处理

@apache apache deleted a comment from davidzollo Apr 18, 2019
@boandai
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boandai commented Apr 18, 2019

Visual Management and Scheduling for Various Tasks of Big Data Platform
  Brother company is a school?


@chyun
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chyun commented Apr 19, 2019

  • Organization: shulidata
  • Location: Hangzhou, China
  • Contact: liqun.w054@shulidata.com
  • Scenario: for big data platform ETL processing

  • 组织:shulidata
  • 地点:中国杭州
  • 联系方式:liqun.w054@shulidata.com
  • 场景:用于大数据平台ETL处理

@XyJan
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XyJan commented Apr 19, 2019

  • Organization: Shenzhen Carbon Atom
  • Location: Shenzhen, China
  • Contact: jan@seeapp.com
  • Scenario: Distributed ETL development for big data platforms, hope to support components such as hive, spark, and support DAG management.

  • 组织:深圳碳原子
  • 地点:中国深圳
  • 联系方式:jan@seeapp.com
  • 场景:用于大数据平台的分布式ETL开发,希望支持hive,spark等组件,支持DAG管理。

@yangning83
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yangning83 commented Apr 19, 2019

Organization: No
Location: Dalian, Liaoning, China
Contact: 123424930@qq.com
Scenario: Visual management and scheduling for tasks.


组织:暂无
地点:中国辽宁大连
联系方式:123424930@qq.com
场景:用于任务的可视化管理与调度。

@roy110
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roy110 commented Apr 22, 2019

Organization: Zhongda University
Location: Guangzhou, China
Contact: 190178867@qq.com
Scenario: Visual management and scheduling of tasks for the operation and maintenance platform.


组织:中大
地点:中国广州
联系方式:190178867@qq.com
场景:用于运维平台的任务的可视化管理与调度。

@boandai boandai pinned this issue Apr 22, 2019
@qiaozhanwei qiaozhanwei unpinned this issue Apr 22, 2019
@pczhouhua
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pczhouhua commented Apr 22, 2019

Organization: geton
Location: Shanghai, China
Contact: 46526682@qq.com
Scenario: Visual management and scheduling for various tasks


组织:geton
地点:中国上海
联系方式:46526682@qq.com
场景:用于各类任务的可视化管理与调度

@kevin5210
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kevin5210 commented Apr 23, 2019

Organization: cttc
Location: Harbin, China
Contact: binda5210@163.com
Scenario: Visual management and scheduling for various tasks


组织:cttc
地点:中国哈尔滨
联系方式:bida5210@163.com
场景:用于各类任务的可视化管理与调度

@linzhaoyang6688
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linzhaoyang6688 commented Apr 23, 2019

Organization: qutke
Location: Xiamen, China
Contact: 1556295727@qq.com
Scenario: Task scheduling and visual management for the data platform.


组织:qutke
地点:中国厦门
联系方式:1556295727@qq.com
场景:用于数据平台的任务调度和可视化管理。

@wuliyong225
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wuliyong225 commented Apr 24, 2019

Organization: giantstone
Location: Changsha, China
Contact: wuliyong225@163.com
Scenario: for big data platform ETL processing


组织:giantstone
地点:中国长沙
联系方式:wuliyong225@163.com
场景:用于大数据平台ETL处理

@wefuture-icon
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wefuture-icon commented Apr 25, 2019

Organization: Micro Technology
Location: Nanjing, Jiangsu, China
Contact: 3947615@qq.com
Scenario: Visual management and scheduling for tasks


组织:微未科技
地点:中国江苏南京
联系方式:3947615@qq.com
场景:用于任务的可视化管理与调度

@boandai boandai pinned this issue Apr 25, 2019
@Huangxy2018
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Huangxy2018 commented Apr 26, 2019

Organization: Chinsoft
Location: Beijing
Contact: hxy7577326@163.com
Scenario: Distributed ETL development for big data platforms, hope to support components such as hive, spark, and support DAG management.


组织:Chinsoft
地点:北京
联系方式:hxy7577326@163.com
场景:用于大数据平台的分布式ETL开发,希望支持hive,spark等组件,支持DAG管理。

@bobzhangfw
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bobzhangfw commented Apr 28, 2019

Organization: Jiangsu Tianchuang
Location: Suzhou, Jiangsu
Contact: 110055885@qq.com
Scenario: ETL development and management for large-scale video stream processing.


组织:江苏天创
地点:江苏苏州
联系方式:110055885@qq.com
场景:用于大规模视频流处理的ETL开发,管理。

@vblvbl
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vblvbl commented Apr 29, 2019

Organization: Individual
Location: Beijing
Contact: 67011332@qq.com
Scenario: Distributed etl scheduling system research


组织:个人
地点:北京
联系方式:67011332@qq.com
场景:分布式etl调度系统调研

@wangfann
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wangfann commented Apr 30, 2019

Organization: Individual
Location: Beijing
Contact: wangfan15@126.com
Scenario: Distributed etl scheduling system research


组织:个人
地点:北京
联系方式:wangfan15@126.com
场景:分布式etl调度系统调研

@y1170328179s
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y1170328179s commented Apr 30, 2019

Organization: Individual
Location: Beijing
Contact: 1225833493@qq.com
Scenario: Personal research distributed big data scheduling


组织:个人
地点:北京
联系方式:1225833493@qq.com
场景:个人研究分布式大数据调度组建

@zhangpeng1990618
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zhangpeng1990618 commented Apr 30, 2019

Organization: 哗啦啦
Location: Beijing
Contact: 17071400190@163.com
Scenario: Big Data Platform Task Scheduling Tool


组织:哗啦啦
地点:北京
联系方式:17071400190@163.com
场景:大数据平台任务调度工具

@ylgkger
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ylgkger commented Apr 30, 2019

Organization: Individual
Location: Hangzhou
Contact: 594386080@qq.com
Scenario: Initial application for big data platform ETL


组织:个人
地点:杭州
联系方式:594386080@qq.com
场景:用于大数据平台ETL初步应用

@echmi
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echmi commented May 5, 2019

Organization: Individual
Location: Wuhan
Contact: hank.you@qq.com
Scenario: Used in the cloud computing platform to perform task scheduling and scheduling learning and research.


组织:个人
地点:武汉
联系方式:hank.you@qq.com
场景:用于云计算平台,进行任务的流程编排和调度学习和研究。

@zhangshun0530
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zhangshun0530 commented May 5, 2019

Organization: alpcontrol
Location: Qingdao, China
Contact: zhangshun0530@gmail.com
Scenario: used by common ETL scheduling platforms


组织:alpcontrol
地点:中国青岛
联系方式: zhangshun0530@gmail.com
场景:用于常见ETL调度平台使用

@ethqunzhong
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ethqunzhong commented May 6, 2019

Organization: Individual
Location: Beijing, China
Contact: zyqbit@163.com
Scenario: User AI platform back-end task scheduling


组织:个人
地点:中国北京
联系方式: zyqbit@163.com
场景:用户AI平台后端任务调度

@free-souls
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free-souls commented May 6, 2019

Organization: xueqiu
Location: Beijing, China
Contact: bianyulong@163.com
Scenario: Data task and ETL scheduling platform use


组织:雪球
地点:中国北京
联系方式: bianyulong@163.com
场景:数据任务和ETL调度平台使用

@mgduoduo
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mgduoduo commented Dec 15, 2021

Organization: Bus Steward (https://www.chebada.com/)
Location: Suzhou, China
Contact: openzerol@163.com
Scenario: Data task and ETL scheduling management

组织:巴士管家
地点:中国苏州
联系方式:openzerol@163.com
场景:数据任务及ETL任务调度管理

@yhhmo
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yhhmo commented Jan 5, 2022

Organization: ZcKj
Location: HaiKou, China
Contact: 942313673@qq.com
Scenario: Data task and ETL scheduling platform

组织:众澄科技
地点:中国海口
联系方式:942313673@qq.com
场景:数据任务及ETL任务调度管理

@Jasong321
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Organization: Yunda
Location: Shanghai, China
Contact: jasong321@163.com
Scenario: ETL scheduling platform

组织:韵达
地点:中国上海
联系方式:jasong321@163.com
场景:ETL调度管理平台

@chenshuai1995
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Organization: 2345
Location: ShangHai, China
Contact: 785659165@qq.com
Scenario: used for data middle platform and algorithm middle platform, process scheduling of tasks

组织:上海二三四五网络科技有限公司
地点:中国上海
联系方式:827311945@qq.com
场景:用于数据中台和算法中台的任务调度

@wushanru
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wushanru commented Jan 7, 2022

组织:卓繁信息
地点:上海
联系方式:251483206@qq.com
场景:用于政务领域任务调度、任务汇总统计

@Aaronoooooo
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Organization: Aurora
Location: Shenzheng, Guangdong, China
Contact: pro1024k@163.com
Scenario: Data task and ETL scheduling platform

@luketalent
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Organization: Access
Location: HangZhou, China
Contact: luketalent@qq.com
Scenario: Data task and ETL scheduling platform

组织:杭州艾柯塞斯品牌管理有限公司
地点:中国杭州
联系方式:luketalent@qq.com
场景:用于数据中台任务调度

@1811A
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1811A commented Jan 17, 2022

组织:百诚慧通
地点:中国合肥
联系方式:303097291@qq.com
场景:用于智慧交通模型任务

@lovingfeel
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lovingfeel commented Jan 17, 2022

Organization: Chongqing Power Network
Location: ChongQing, China
Contact: 354911379@qq.com
Scenario: Visual management and scheduling for various tasks of the big data platform

组织:重庆电网
地点:中国重庆
联系方式:354911379@qq.com
场景:用于大数据平台各类任务的可视化管理与调度

@darrkz
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darrkz commented Jan 20, 2022

Organization: Electronic Soul
Location: Hangzhou, China
Contact: 171910226@qq.com
Scenario: management and scheduling for various tasks of the big data platform

组织:杭州电魂网络
地点:中国浙江杭州
联系方式:171910226@qq.com
场景:用于大数据平任务的可视化管理与调度

@davidzollo davidzollo unpinned this issue Feb 7, 2022
@SbloodyS SbloodyS pinned this issue May 9, 2022
@zhongjiajie zhongjiajie unpinned this issue Jun 17, 2022
@zhuxt2015
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Organization: YILI
Location: BeiJing China
Contact: zhuxt20152015@163.com
Scenario: ETL scheduling platform

组织:伊利集团
地点:中国北京
联系方式:zhuxt20152015@163.com
场景:ETL调度管理平台

@xiaojiu504
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组织:好好住
地点:中国北京
联系方式:sunxu01731@163.com
场景:数据任务调度

@zhumengdetianshi
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Organization: mirrorego
Location: Shenzhen China
Contact: 734736109@qq.com
Scenario: Task scheduling platform,for bigdata offline tasks and AI tasks

组织:镜象科技
地点:中国深圳
联系方式:734736109@qq.com
场景:任务调度平台,主要用于大数据离线任务和AI相关任务

@764276020
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Organization: Netease
Location: GuangZhou, China
Contact: 764276020@qq.com
Scenario: Visual management and scheduling for various tasks of the big data platform

组织:网易
地点:中国广东广州
联系方式:764276020@qq.com
场景:用于大数据平台各类任务的可视化管理与调度

@davidzollo davidzollo pinned this issue Mar 6, 2023
@liangziqiang
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Organization: longi
Location: XiAn, China
Contact: 591635247@qq.com
Scenario: Visual management and scheduling for various tasks of the big data platform

组织:隆基l绿能
地点:中国西安
联系方式:591635247@qq.com
场景:用于大数据平台各类任务的可视化管理与调度

@baratamavinash225
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Organization: Tesco
Location: India
Contact: baratamavinash225@gmail.com
Scenario: Using for the Scheduling the Spark jobs, buildign auto deployment of workflows through our CLI commands

@ediconss
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Organization: Chongqing HJ Fruit
Location: ChongQing, China
Contact: sunkang@hjfruit.com
Scenario: Visual management and scheduling for various tasks of the big data platform

组织:洪九果品
地点:中国重庆
联系方式:sunkang@hjfruit.com
场景:用于大数据平台各类任务的可视化管理与调度

@daymickcorr
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daymickcorr commented May 3, 2024

Organization: home user
Location: Canada, Montreal
Contact: mickeycorriveau@hotmail.com
Scenario: System Operations

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This issue has been automatically marked as stale because it has not had recent activity for 30 days. It will be closed in next 7 days if no further activity occurs.

@github-actions github-actions bot added the Stale label Jul 26, 2024
@fuchanghai fuchanghai unpinned this issue Aug 9, 2024
@SbloodyS SbloodyS pinned this issue Aug 12, 2024
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