[Optimization-1043][md] Optimizate readme.md (#1044)

Co-authored-by: wenmo <32723967+wenmo@users.noreply.github.com>

README.md

@@ -9,137 +9,108 @@
 
 ## Introduction
 
-Real-time is the future. Dlink is born for Apache Flink, allowing Flink SQL to enjoy silky smoothness, and is committed to the construction of a real-time computing platform.
-
-Dinky implements Dlink based on Apache Flink, enhances the application and experience of Flink, and explores streaming data warehouses. That is to stand on the shoulders of giants to innovate and practice, Dinky has unlimited potential under the development trend of batch and flow integration in the future.
-
-In the end, Dinky's development is due to the guidance and results of other excellent open source projects such as Apache Flink.
-
-## Features
-
-A `out-of-the-box`, `easy to extend`, based on `Apache Flink`, a `one-stop` real-time computing platform connecting with many frameworks such as `OLAP` and `data lake`, dedicated to `stream-batch integration` The construction and practice of `Lake and Warehouse Integration`.
-
-Its main objectives are as follows:
-
-- Visual interactive FlinkSQL and SQL data development platform: automatic prompt completion, syntax highlighting, debugging execution, syntax verification, statement beautification, global variables, etc.
-
-- Supports comprehensive multi-version FlinkSQL job submission methods: Local, Standalone, Yarn Session, Yarn Per-Job, Yarn Application, Kubernetes Session, Kubernetes Application
-
-- Support all Connectors, UDFs, CDCs, etc. of Apache Flink
-
-- Support FlinkSQL syntax enhancement: compatible with Apache Flink SQL, table-valued aggregate functions, global variables, CDC multi-source merge, execution environment, statement merge, shared session, etc.
-
-- Supports easily extensible SQL job submission methods: ClickHouse, Doris, Hive, Mysql, Oracle, Phoenix, PostgreSql, SqlServer, etc.
-
-- Support FlinkCDC (Source merge) real-time warehousing into the lake
-
-- Support real-time debugging preview Table and ChangeLog data and graphics display
-
-- Support syntax logic check, job execution plan, field-level blood relationship analysis, etc.
-
-- Support Flink metadata, data source metadata query and management
-
-- Support real-time task operation and maintenance: job online and offline, job information, cluster information, job snapshot, exception information, job log, data map, ad hoc query, historical version, alarm record, etc.
-
-- Support as multi-version FlinkSQL Server capability as well as OpenApi
-
-- Support easy-to-expand real-time job alarms and alarm groups: DingTalk, WeChat Enterprise Account, etc.
-
-- Support for fully managed SavePoint launch mechanisms: most recent, earliest, once specified, etc.
-
-- Support multiple resource management: cluster instance, cluster configuration, Jar, data source, alarm group, alarm instance, document, user, system configuration, etc.
-
-- More hidden functions are waiting for friends to explore
+Dinky is an out of the box one-stop real-time computing platform dedicated to the construction and practice of Unified Streaming & Batch and Unified Data Lake & Data Warehouse. Based on Apache Flink, Dinky provides the ability to connect many big data frameworks including OLAP and Data Lake.
+
+## Feature
+
+Its main feature are as follows:
+
+- Immersive Flink SQL Data Development: Automatic prompt completion, syntax highlighting, statement beautification, online debugging, syntax verification, execution plan, MetaStore, lineage, version comparison, etc.
+- Support FlinkSQL multi-version development and execution modes: Local,Standalone,Yarn/Kubernetes  Session,Yarn Per-Job,Yarn/Kubernetes  Application.
+- Support Apache Flink ecology: Connector,FlinkCDC,Table Store,etc.
+- Support FlinkSQL syntax enhancement: Table-valued aggregate functions, global variables, execution environments, statement merging, database synchronization, shared sessions, etc.
+- Supports real-time warehousing and lake entry of the entire FlinkCDC database, multi-database output, and automatic table creation.
+- Support SQL job development: ClickHouse,Doris,Hive,Mysql,Oracle,Phoenix,PostgreSql,SqlServer,StarRocks,etc.
+- Support real-time online debugging preview Table, ChangeLog, statistical chart and UDF.
+- Support Flink Catalog, data source metadata online query and management.
+- Support real-time task operation and maintenance: Online and offline, job information, cluster information, job snapshot, exception information, data map, data exploration, historical version, alarm record, etc.
+- Support as multi-version FlinkSQL Server and OpenApi capability.
+- Support real-time job alarm and alarm group: DingTalk, WeChat, Feishu, E-mail, etc.
+- Support automatically managed SavePoint/CheckPoint recovery and triggering mechanisms: latest, earliest, specified, etc.
+- Support resource management: Cluster instance, cluster configuration, Jar, data source, alarm group, alarm instance, document, user, system configuration, etc.
+- More hidden features are waiting for friends to explore.
 
 ## Principle
 
 ![dinky_principle](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/main/dinky_principle.png)
 
-## Wonderful Moment
+## Run the Screenshot
 
 > FlinkSQL Studio
 
-![flinksqlstudio](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/flinksqlstudio.png)
-
-> Live debug preview
-
-![selectpreview](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/selectpreview.png)
-
-> Grammar and logic checking
-
-![checksql](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/checksql.png)
+![image-20220922101143441](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/datastudio.png)
 
-> JobPlan
+> Grammar Check
 
-![jobplan](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/jobplan.png)
+![image-20220922105912608](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/checksql.png)
 
-> Field-level bloodline analysis
+> Version Management
 
-![lineage](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/lineage.png)
+![image-20220922110933360](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/versiondiff.png)
 
-> BI showcase
+> lineage
 
-![charts](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/charts.png)
+![image-20220922102603221](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/lineage.png)
 
-> Metadata query
+> BI Charts
 
-![metadata](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/metadata.png)
+![image-20220922110356261](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/charts.png)
 
-> Real-time task monitoring
+> Metadata Query
 
-![monitor](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/monitor.png)
+![image-20220922104423674](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/metadata.png)
 
-> Real-time job information
+> Task Monitoring
 
-![jobinfo](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/jobinfo.png)
+![image-20220922101828034](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/monitor.png)
 
-> Data Map
+> Job Information
 
-![datamap](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/datamap.png)
+![image-20220922102034061](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/jobinfo.png)
 
-> Data source registration
+## Near-term Plans
 
-![datasource](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/datasource.png)
+- [ ] Multi-tenancy and Namespaces
+- [ ] Global lineage and influence analysis
+- [ ] Unified Metadata Management
+- [x] Flink Metadata Store
+- [x] Real-time warehouse entry into the lake
 
-## Function
+## Participate in Contributions
 
-See [Function](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/feature.md)
+Welcome to join the community, build a win-win situation, please refer to the contribution process： [How to contribute](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/developer_guide/contribution/how_contribute.md).
 
-## Near-Term Plans
-
-- Multi-tenancy and namespaces
-
-- Global bloodline and influence analysis
+## How to Deploy
 
-- Unified metadata management
+See [source code compilation](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/build_deploy/build.md) and [installation and deployment](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/build_deploy/deploy.md) for details.
 
-- Flink metadata persistence
+## How to Upgrade
 
-- Multi-version Flink-Client Server
+Due to many functions, there are many bugs and optimization points. It is strongly recommended to use or upgrade to the latest version.
 
-- Synchronization of thousands of watches in the whole library
+Upgrade steps:
 
-## How to Contribute
+(1) Upgrade the app: Replace all dependencies of latest Dinky.
 
-You are welcome to contribute your strength to the community and build a win-win situation. Please refer to the contribution process: [[How to Contribute](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/developer_guide/how_contribute.md)]
+(2) Upgrade the DDL: Execute some of the upgrade statements in dlink_history.sql in the sql directory. It is based on the version number and date to determine where to start the execution. Please do not execute all sql directly.
 
-## How to Deploy
+## Thanks
 
-See [Compile](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/quick_start/build.md) And [Install](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/quick_start/deploy.md) 。
+Standing on the shoulders of giants, Dinky was born. For this we express our heartfelt thanks to all the open source software used and its communities! We also hope that we are not only beneficiaries of open source, but also contributors to open source. We also hope that partners who have the same enthusiasm and belief in open source will join in and contribute to open source together.
 
-## How to Upgrade to the latest
+A partial list of acknowledgements follows:
 
-Due to more functions, there are more bugs and optimization points. It is strongly recommended that you use or upgrade to the latest version.
+[Apache Flink](https://github.com/apache/flink)
 
-Replace all dependent packages of the latest Dinky, and execute some upgrade statements in dlink_history.sql in the sql directory. It is based on the version number and date to determine where to start the execution. Please do not directly execute all sql.
+[FlinkCDC](https://github.com/ververica/flink-cdc-connectors)
 
-## Thanks
+[Apache Flink Table Store](https://github.com/apache/flink-table-store)
 
-Standing on the shoulders of giants, Dinky was born. For this we express our heartfelt thanks to all the open source software used and its communities! We also hope that we are not only beneficiaries of open source, but also contributors to open source. We also hope that partners who have the same enthusiasm and belief in open source will join in and contribute to open source together! Acknowledgments are listed below:
+[Apache Dolphinscheduler](https://github.com/apache/dolphinscheduler)
 
-[Apache Flink](https://github.com/apache/flink)
+[Apache Doris](https://github.com/apache/doris)
 
-[Apache Dolphinscheduler](https://github.com/apache/dolphinscheduler)
+[Druid](https://github.com/alibaba/druid)
 
 [Ant-Design-Pro](https://github.com/ant-design/ant-design-pro)
 
@@ -147,24 +118,31 @@ Standing on the shoulders of giants, Dinky was born. For this we express our hea
 
 [Monaco Editor](https://github.com/Microsoft/monaco-editor)
 
+[Sa Token](https://github.com/dromara/Sa-Token)
+
 [SpringBoot]()
 
 Thanks to [JetBrains](https://www.jetbrains.com/?from=dlink) for sponsoring a free open source license.
 
-[![JetBrains](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/main/jetbrains.svg)](https://www.jetbrains.com/?from=dlink)
+[![JetBrains](https://raw.githubusercontent.com/DataLinkDC/dlink/dev/dlink-doc/images/main/jetbrains.svg)](https://www.jetbrains.com/?from=dlink)
 
 ## Get Help
 
-1. Submit an issue
+1.Submit an issue.
+
+2.Visit the [official website](http://www.dlink.top/#/) website to read the latest documentation manual.
+
+3.It is recommended to scan the code to enter the DingTalk group.
+
+<img src="https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/main/dinkydingding.jpg" alt="dinkydingding" style="zoom:30%;" />
 
-2. Enter the WeChat user community group (recommended, add WeChat `wenmo_ai` to invite into the group) and QQ user community group (**543709668**) to communicate, apply for the remark "Dinky + company name + position", do not write or approve
+4.Enter the WeChat user community group (recommended, add WeChat `wenmo_ai` to invite into the group) and QQ user community group (**543709668**) to communicate, and apply for the remarks "Dinky + company name + position".
 
-3. Follow the WeChat public account to get relevant articles (recommended to follow the latest news): [DataLink Data Center](https://mmbiz.qpic.cn/mmbiz_jpg/dyicwnSlTFTp6w4PuJruFaLV6uShCJDkzqwtnbQJrQ90yKDuuIC8tyMU5DK69XZibibx7EPPBRQ3ic81se5UQYs21g/0?wx_fmt=jpeg)
+5.Follow the WeChat public account to get the latest official articles: [Dinky Open Source](https://mmbiz.qpic.cn/mmbiz_jpg/dyicwnSlTFTp6w4PuJruFaLV6uShCJDkzqwtnbQJrQ90yKDuuIC8tyMU5DK69XZibibx7EPPBRQ3ic81se5UQYs21g/0?wx_fmt=jpeg).
 
-4. Follow the bilibili UP master (at the end of the article) to get the latest video teaching
+6.Follow bilibili UP master (Shi Wen Mo A) to get the latest video teaching.
 
-5. Visit [GithubPages](https://datalinkdc.github.io/dlink/#/) or [Official Website](http://www.dlink.top/#/) to read the latest documentation manual
+## Copyright
 
-## LICENSE
+Please refer to the [LICENSE](https://github.com/DataLinkDC/dlink/blob/dev/LICENSE) document.
 
-Please refer to the [LICENSE](https://github.com/DataLinkDC/dlink/blob/main/LICENSE) document.

README_zh_CN.md

@@ -9,31 +9,24 @@
 
 ## 简介
 
-实时即未来，Dlink 为 Apache Flink 而生，让 Flink SQL 纵享丝滑，并致力于实时计算平台建设。
+Dinky 是一个 `开箱即用` 、`易扩展` ，以 `Apache Flink` 为基础，连接 `OLAP` 和 `数据湖` 等众多框架的 `一站式` 实时计算平台，致力于 `流批一体` 和 `湖仓一体` 的探索与实践。
 
-Dinky 基于 Apache Flink 实现 Dlink ，增强 Flink 的应用与体验，探索流式数仓。即站在巨人肩膀上创新与实践，Dinky 在未来批流一体的发展趋势下潜力无限。
-
-最后，Dinky 的发展皆归功于 Apache Flink 等其他优秀的开源项目的指导与成果。
-
-## 特点
-
-一个 `开箱即用` 、`易扩展` ，以 `Apache Flink` 为基础，连接 `OLAP` 和 `数据湖` 等众多框架的 `一站式` 实时计算平台，致力于 `流批一体` 和 `湖仓一体` 的建设与实践。
-
-其主要目标如下：
+## 功能
 
-- 可视化交互式 FlinkSQL 和 SQL 的数据开发平台：自动提示补全、语法高亮、调试执行、语法校验、语句美化、全局变量等
-- 支持全面的多版本的 FlinkSQL 作业提交方式：Local、Standalone、Yarn Session、Yarn Per-Job、Yarn Application、Kubernetes Session、Kubernetes Application
-- 支持 Apache Flink 所有的 Connector、UDF、CDC等
-- 支持 FlinkSQL 语法增强：兼容 Apache Flink SQL、表值聚合函数、全局变量、CDC多源合并、执行环境、语句合并、共享会话等
-- 支持易扩展的 SQL 作业提交方式：ClickHouse、Doris、Hive、Mysql、Oracle、Phoenix、PostgreSql、SqlServer 等
-- 支持 FlinkCDC （Source 合并）整库实时入仓入湖
-- 支持实时调试预览 Table 和 ChangeLog 数据及图形展示
-- 支持语法逻辑检查、作业执行计划、字段级血缘分析等
-- 支持 Flink 元数据、数据源元数据查询及管理
-- 支持实时任务运维：作业上线下线、作业信息、集群信息、作业快照、异常信息、作业日志、数据地图、即席查询、历史版本、报警记录等
-- 支持作为多版本 FlinkSQL Server 的能力以及 OpenApi
-- 支持易扩展的实时作业报警及报警组：钉钉、微信企业号等
-- 支持完全托管的 SavePoint 启动机制：最近一次、最早一次、指定一次等
+其主要功能如下：
+
+- 沉浸式 FlinkSQL 数据开发：自动提示补全、语法高亮、语句美化、在线调试、语法校验、执行计划、MetaStore、血缘分析、版本对比等
+- 支持 FlinkSQL 多版本开发及多种执行模式：Local、Standalone、Yarn/Kubernetes  Session、Yarn Per-Job、Yarn/Kubernetes  Application
+- 支持 Apache Flink 生态：Connector、FlinkCDC、Table Store 等
+- 支持 FlinkSQL 语法增强：表值聚合函数、全局变量、执行环境、语句合并、整库同步、共享会话等
+- 支持 FlinkCDC 整库实时入仓入湖、多库输出、自动建表
+- 支持 SQL 作业开发：ClickHouse、Doris、Hive、Mysql、Oracle、Phoenix、PostgreSql、SqlServer、StarRocks 等
+- 支持实时在线调试预览 Table、 ChangeLog、统计图和 UDF
+- 支持 Flink Catalog、数据源元数据在线查询及管理
+- 支持实时任务运维：上线下线、作业信息、集群信息、作业快照、异常信息、数据地图、数据探查、历史版本、报警记录等
+- 支持作为多版本 FlinkSQL Server 以及 OpenApi 的能力
+- 支持实时作业报警及报警组：钉钉、微信企业号、飞书、邮箱等
+- 支持自动托管的 SavePoint/CheckPoint 恢复及触发机制：最近一次、最早一次、指定一次等
 - 支持多种资源管理：集群实例、集群配置、Jar、数据源、报警组、报警实例、文档、用户、系统配置等
 - 更多隐藏功能等待小伙伴们探索
 
@@ -41,92 +34,92 @@ Dinky 基于 Apache Flink 实现 Dlink ，增强 Flink 的应用与体验，探
 
 ![dinky_principle](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/main/dinky_principle.png)
 
-## 精彩瞬间
+## 运行效果
 
 > FlinkSQL Studio
 
-![flinksqlstudio](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/flinksqlstudio.png)
-
-> 实时调试预览
-
-![selectpreview](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/selectpreview.png)
+![image-20220922101143441](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/datastudio.png)
 
-> 语法和逻辑检查
+> 语法检查
 
-![checksql](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/checksql.png)
+![image-20220922105912608](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/checksql.png)
 
-> JobPlan
+> 版本管理
 
-![jobplan](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/jobplan.png)
+![image-20220922110933360](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/versiondiff.png)
 
-> 字段级血缘分析
+> 血缘分析
 
-![lineage](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/lineage.png)
+![image-20220922102603221](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/lineage.png)
 
-> BI 展示
+> BI 图表
 
-![charts](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/charts.png)
+![image-20220922110356261](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/charts.png)
 
 > 元数据查询
 
-![metadata](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/metadata.png)
+![image-20220922104423674](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/metadata.png)
 
-> 实时任务监控
+> 任务监控
 
-![monitor](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/monitor.png)
+![image-20220922101828034](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/monitor.png)
 
-> 实时作业信息
+> 作业信息
 
-![jobinfo](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/jobinfo.png)
-
-> 数据地图
-
-![datamap](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/datamap.png)
-
-> 数据源注册
-
-![datasource](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/060/datasource.png)
-
-## 功能
-
-详见 [功能](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/feature.md)
+![image-20220922102034061](https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/070/jobinfo.png)
 
 ## 近期计划
 
 - [ ] 多租户及命名空间
 - [ ] 全局血缘与影响分析
 - [ ] 统一元数据管理
-- [ ]  Flink 元数据持久化
-- [ ]  多版本 Flink-Client Server
-- [ ]  整库千表同步
+- [x] Flink 元数据持久化
+- [x] 整库实时入仓入湖
 
 ## 参与贡献
 
-欢迎您为社区贡献自己的力量，共建共赢，贡献流程请参考： [[参与贡献](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/developer_guide/how_contribute.md)]
+欢迎加入社区，共建共赢，贡献流程请参考： [参与贡献](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/developer_guide/contribution/how_contribute.md)
 
 ## 如何部署
 
-详见 [编译](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/quick_start/build.md) 和 [安装](https://github.com/DataLinkDC/dlink/blob/dev/docs/zh-CN/quick_start/deploy.md) 。
+详见 [源码编译](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/build_deploy/build.md) 和 [安装部署](https://github.com/DataLinkDC/dlink/blob/dev/docs/docs/build_deploy/deploy.md) 。
+
+## 如何升级
+
+由于功能较多，所以 bug 及优化点较多，强烈建议使用或升级到最新版本。
 
-## 如何升级到最新
+升级步骤：
 
-由于功能较多，所以 bug 及优化点较多，强烈建议你使用或升级到最新版本。
-替换最新 Dinky 所有依赖包 ，执行 sql 目录下的 dlink_history.sql 中的部分升级语句，依据是通过版本号与日期来判断从何处开始执行，请不要直接执行全部 sql。
+（1）升级应用：替换最新 Dinky 所有依赖包；
+
+（2）升级 DDL：执行 sql 目录下的 dlink_history.sql 中的部分升级语句，依据是通过版本号与日期来判断从何处开始执行，请不要直接执行全部 sql。
 
 ## 感谢
 
-站在巨人的肩膀上，Dinky 才得以诞生。对此我们对使用的所有开源软件及其社区表示衷心的感谢！我们也希望自己不仅是开源的受益者，也能成为开源的贡献者，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！致谢列表如下：
+站在巨人的肩膀上，Dinky 才得以诞生。对此我们对使用的所有开源软件及其社区表示衷心的感谢！我们也希望自己不仅是开源的受益者，也能成为开源的贡献者，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！
+
+部分致谢列表如下：
 
 [Apache Flink](https://github.com/apache/flink)
 
+[FlinkCDC](https://github.com/ververica/flink-cdc-connectors)
+
+[Apache Flink Table Store](https://github.com/apache/flink-table-store)
+
 [Apache Dolphinscheduler](https://github.com/apache/dolphinscheduler)
 
+[Apache Doris](https://github.com/apache/doris)
+
+[Druid](https://github.com/alibaba/druid)
+
 [Ant-Design-Pro](https://github.com/ant-design/ant-design-pro)
 
 [Mybatis Plus](https://github.com/baomidou/mybatis-plus)
 
 [Monaco Editor](https://github.com/Microsoft/monaco-editor)
 
+[Sa Token](https://github.com/dromara/Sa-Token)
+
 [SpringBoot]()
 
 感谢 [JetBrains](https://www.jetbrains.com/?from=dlink) 提供的免费开源 License 赞助。
@@ -137,13 +130,17 @@ Dinky 基于 Apache Flink 实现 Dlink ，增强 Flink 的应用与体验，探
 
 1.提交 issue
 
-2.进入微信用户社区群（推荐，添加微信号 `wenmo_ai` 邀请进群）和QQ用户社区群（**543709668**）交流，申请备注 “ Dinky + 企业名 + 职位”，不写不批
+2.访问 [官网](http://www.dlink.top/#/) 网址，阅读最新文档手册
+
+3.推荐扫码进入钉钉群
+
+<img src="https://raw.githubusercontent.com/DataLinkDC/dlink/main/dlink-doc/images/main/dinkydingding.jpg" alt="dinkydingding" style="zoom:30%;" />
 
-3.关注微信公众号获取相关内容的文章（最新消息获取建议关注）：[DataLink数据中台](https://mmbiz.qpic.cn/mmbiz_jpg/dyicwnSlTFTp6w4PuJruFaLV6uShCJDkzqwtnbQJrQ90yKDuuIC8tyMU5DK69XZibibx7EPPBRQ3ic81se5UQYs21g/0?wx_fmt=jpeg)
+4.进入微信用户社区群（推荐，添加微信号 `wenmo_ai` 邀请进群）和QQ用户社区群（**543709668**）交流，申请备注 “ Dinky + 企业名 + 职位”
 
-4.关注 bilibili UP 主（是文末呀）获取最新视频教学
+5.关注微信公众号获取官方最新文章：[Dinky 开源](https://mmbiz.qpic.cn/mmbiz_jpg/dyicwnSlTFTp6w4PuJruFaLV6uShCJDkzqwtnbQJrQ90yKDuuIC8tyMU5DK69XZibibx7EPPBRQ3ic81se5UQYs21g/0?wx_fmt=jpeg)
 
-5.访问 [GithubPages](https://datalinkdc.github.io/dlink/#/) 或 [官网](http://www.dlink.top/#/) 网址，阅读最新文档手册
+6.关注 bilibili UP 主（是文末呀）获取最新视频教学
 
 ## 版权