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Posted to commits@inlong.apache.org by do...@apache.org on 2022/06/26 10:12:26 UTC
[inlong-website] branch fix-455 created (now eca6624a2)
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at eca6624a2 [INLONG-455][Doc] Update the Introduction for InLong
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[inlong-website] 01/01: [INLONG-455][Doc] Update the Introduction for InLong
Posted by do...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
dockerzhang pushed a commit to branch fix-455
in repository https://gitbox.apache.org/repos/asf/inlong-website.git
commit eca6624a2d7634e2fe1d5c4b32a9a0d541ce437e
Author: dockerzhang <do...@apache.org>
AuthorDate: Sun Jun 26 18:12:18 2022 +0800
[INLONG-455][Doc] Update the Introduction for InLong
---
docs/introduction.md | 9 ++++++---
.../zh-CN/docusaurus-plugin-content-docs/current/introduction.md | 7 ++++---
.../docusaurus-plugin-content-docs/version-1.2.0/introduction.md | 7 ++++---
versioned_docs/version-1.2.0/introduction.md | 9 ++++++---
4 files changed, 20 insertions(+), 12 deletions(-)
diff --git a/docs/introduction.md b/docs/introduction.md
index f6e7e87a6..60afad975 100644
--- a/docs/introduction.md
+++ b/docs/introduction.md
@@ -7,9 +7,12 @@ sidebar_position: 1
> and it is regarded as a metaphor of the InLong system for reporting data streams.
## About InLong
-[Apache InLong](https://inlong.apache.org) is a one-stop integration framework for massive data donated by Tencent to the Apache community. It provides automatic, safe, reliable, and high-performance data transmission capabilities to facilitate the construction of streaming-based data analysis, modeling, and applications.
-The Apache InLong project was originally called TubeMQ, focusing on high-performance, low-cost message queuing services. To further release the surrounding ecological capabilities of TubeMQ, the community upgraded the project to InLong, focusing on creating a one-stop integration framework for massive data.
-Apache InLong relies on trillion-level data ingestion and processing capabilities to integrate the entire process of data collection, aggregation, storage, and sorting data processing. It is simple, flexible, stable, and reliable.
+[Apache InLong](https://inlong.apache.org) is a one-stop integration framework for massive data ,it provides automatic, safe, reliable, and high-performance data transmission capabilities to
+facilitate the construction of streaming-based data analysis, modeling, and applications. The Apache InLong project was originally called TubeMQ, focusing on high-performance,
+low-cost message queuing services. To further release the surrounding ecological capabilities of TubeMQ, the community upgraded the project to InLong, focusing on creating a one-stop integration framework for massive data.
+Apache InLong relies on 10 trillion-level data ingestion and processing capabilities to integrate the entire process of data collection, aggregation, storage, and sorting data processing. It is simple, flexible, stable, and reliable.
+The project was initially donated to the Apache incubator by the Tencent Big Data team in November 2019 and officially graduated as an Apache top-level project in June 2022. Currently, InLong is widely used in various industries such as advertising,
+payment, social networking, games, artificial intelligence, etc., to provide efficient and convenient customer services in multiple fields.
## Features
- Ease of Use
diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md b/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md
index 8f5cfbbe6..aadfc62e4 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md
@@ -3,12 +3,13 @@ title: InLong 简介
sidebar_position: 1
---
-> InLong(应龙)，中国神话故事里的神兽，引流入海，借喻 InLong 系统提供数据接入能力。
+> InLong(应龙)，中国神话故事里的神兽，引流入海，借喻 InLong 系统提供数据集成能力。
## 关于 InLong
-[Apache InLong（应龙）](https://inlong.apache.org)是腾讯捐献给 Apache 社区的一站式海量数据集成框架，提供自动、安全、可靠和高性能的数据传输能力，方便业务构建基于流式的数据分析、建模和应用。
+[Apache InLong（应龙）](https://inlong.apache.org)是一站式的海量数据集成框架，提供自动、安全、可靠和高性能的数据传输能力，方便业务构建基于流式的数据分析、建模和应用。
InLong 项目原名 TubeMQ ，专注于高性能、低成本的消息队列服务。为了进一步释放 TubeMQ 周边的生态能力，我们将项目升级为 InLong，专注打造一站式海量数据集成框架。
-Apache InLong 依托万亿级别的数据接入和处理能力，整合了数据采集、汇聚、存储、分拣数据处理全流程，拥有简单易用、灵活扩展、稳定可靠等特性。
+Apache InLong 依托 10 万亿级别的数据接入和处理能力，整合了数据采集、汇聚、存储、分拣数据处理全流程，拥有简单易用、灵活扩展、稳定可靠等特性。
+该项目最初于 2019 年 11 月由腾讯大数据团队捐献到 Apache 孵化器，2022 年 6 月正式毕业成为 Apache 顶级项目。目前 InLong 正广泛应用于广告、支付、社交、游戏、人工智能等各个行业领域，为多领域客户提供高效化便捷化服务。
## 特性
- 简单易用
diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/version-1.2.0/introduction.md b/i18n/zh-CN/docusaurus-plugin-content-docs/version-1.2.0/introduction.md
index 8f5cfbbe6..aadfc62e4 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/version-1.2.0/introduction.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/version-1.2.0/introduction.md
@@ -3,12 +3,13 @@ title: InLong 简介
sidebar_position: 1
---
-> InLong(应龙)，中国神话故事里的神兽，引流入海，借喻 InLong 系统提供数据接入能力。
+> InLong(应龙)，中国神话故事里的神兽，引流入海，借喻 InLong 系统提供数据集成能力。
## 关于 InLong
-[Apache InLong（应龙）](https://inlong.apache.org)是腾讯捐献给 Apache 社区的一站式海量数据集成框架，提供自动、安全、可靠和高性能的数据传输能力，方便业务构建基于流式的数据分析、建模和应用。
+[Apache InLong（应龙）](https://inlong.apache.org)是一站式的海量数据集成框架，提供自动、安全、可靠和高性能的数据传输能力，方便业务构建基于流式的数据分析、建模和应用。
InLong 项目原名 TubeMQ ，专注于高性能、低成本的消息队列服务。为了进一步释放 TubeMQ 周边的生态能力，我们将项目升级为 InLong，专注打造一站式海量数据集成框架。
-Apache InLong 依托万亿级别的数据接入和处理能力，整合了数据采集、汇聚、存储、分拣数据处理全流程，拥有简单易用、灵活扩展、稳定可靠等特性。
+Apache InLong 依托 10 万亿级别的数据接入和处理能力，整合了数据采集、汇聚、存储、分拣数据处理全流程，拥有简单易用、灵活扩展、稳定可靠等特性。
+该项目最初于 2019 年 11 月由腾讯大数据团队捐献到 Apache 孵化器，2022 年 6 月正式毕业成为 Apache 顶级项目。目前 InLong 正广泛应用于广告、支付、社交、游戏、人工智能等各个行业领域，为多领域客户提供高效化便捷化服务。
## 特性
- 简单易用
diff --git a/versioned_docs/version-1.2.0/introduction.md b/versioned_docs/version-1.2.0/introduction.md
index f6e7e87a6..ef63ee320 100644
--- a/versioned_docs/version-1.2.0/introduction.md
+++ b/versioned_docs/version-1.2.0/introduction.md
@@ -7,9 +7,12 @@ sidebar_position: 1
> and it is regarded as a metaphor of the InLong system for reporting data streams.
## About InLong
-[Apache InLong](https://inlong.apache.org) is a one-stop integration framework for massive data donated by Tencent to the Apache community. It provides automatic, safe, reliable, and high-performance data transmission capabilities to facilitate the construction of streaming-based data analysis, modeling, and applications.
-The Apache InLong project was originally called TubeMQ, focusing on high-performance, low-cost message queuing services. To further release the surrounding ecological capabilities of TubeMQ, the community upgraded the project to InLong, focusing on creating a one-stop integration framework for massive data.
-Apache InLong relies on trillion-level data ingestion and processing capabilities to integrate the entire process of data collection, aggregation, storage, and sorting data processing. It is simple, flexible, stable, and reliable.
+[Apache InLong](https://inlong.apache.org) is a one-stop integration framework for massive data ,it provides automatic, safe, reliable, and high-performance data transmission capabilities to
+facilitate the construction of streaming-based data analysis, modeling, and applications. The Apache InLong project was originally called TubeMQ, focusing on high-performance,
+low-cost message queuing services. To further release the surrounding ecological capabilities of TubeMQ, the community upgraded the project to InLong, focusing on creating a one-stop integration framework for massive data.
+Apache InLong relies on 10 trillion-level data ingestion and processing capabilities to integrate the entire process of data collection, aggregation, storage, and sorting data processing. It is simple, flexible, stable, and reliable.
+The project was initially donated to the Apache incubator by the Tencent Big Data team in November 2019 and officially graduated as an Apache top-level project in June 2022. Currently, InLong is widely used in various industries such as advertising,
+payment, social networking, games, artificial intelligence, etc., to provide efficient and convenient customer services in multiple fields.
## Features
- Ease of Use