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Posted to commits@inlong.apache.org by do...@apache.org on 2022/10/14 07:45:39 UTC
[inlong-website] branch master updated: [INLONG-566][Doc] Update the Introduction (#567)
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new 05def02bfa [INLONG-566][Doc] Update the Introduction (#567)
05def02bfa is described below
commit 05def02bfad0e235a76ad2f9bc3f33f4eaa6fe09
Author: Charles Zhang <do...@apache.org>
AuthorDate: Fri Oct 14 15:45:34 2022 +0800
[INLONG-566][Doc] Update the Introduction (#567)
---
docs/introduction.md | 8 ++++----
.../current/design_and_concept/basic_concept.md | 2 +-
.../docusaurus-plugin-content-docs/current/introduction.md | 10 +++++-----
3 files changed, 10 insertions(+), 10 deletions(-)
diff --git a/docs/introduction.md b/docs/introduction.md
index 2d62bbecb5..685e1ef1a9 100644
--- a/docs/introduction.md
+++ b/docs/introduction.md
@@ -56,7 +56,7 @@ values={[
## Modules
Apache InLong serves the entire life cycle from data collection to landing, and provides different processing modules according to different stages of data, including the next modules:
-- **inlong-agent**, data collection agent, supports reading regular logs from specified directories or files and reporting data one by one. In the future, DB collection capabilities will also be expanded.
+- **inlong-agent**, data collection services, including file collection, DB collection, etc.
- **inlong-dataproxy**, a Proxy component based on Flume-ng, supports data transmission blocking, placing retransmission, and has the ability to forward received data to different MQ (message queues).
- **inlong-tubemq**, Tencent's self-developed message queuing service, focuses on high-performance storage and transmission of massive data in big data scenarios and has a relatively good core advantage in mass practice and low cost.
- **inlong-sort**, after consuming data from different MQ services, perform ETL processing, and then aggregate and write the data into Apache Hive, ClickHouse, Hbase, IceBerg, etc.
@@ -71,11 +71,11 @@ Apache InLong serves the entire life cycle from data collection to landing, and
| | File | None | Standard |
| | Kafka | 2.x | Lightweight, Standard |
| | MySQL | 5.6, 5.7, 8.0.x | Lightweight, Standard |
-| | MongoDB | >= 3.6 | Lightweight |
+| | MongoDB | >= 3.6 | Lightweight, Standard |
| | Oracle | 11,12,19 | Lightweight |
-| | PostgreSQL | 9.6, 10, 11, 12 | Lightweight |
+| | PostgreSQL | 9.6, 10, 11, 12 | Lightweight, Standard |
| | Pulsar | 2.8.x | Lightweight |
-| | SQLServer | 2012, 2014, 2016, 2017, 2019 | Lightweight |
+| | SQLServer | 2012, 2014, 2016, 2017, 2019 | Lightweight, Standard |
| Load Node | Auto Consumption | None | Standard |
| | Hive | 1.x, 2.x, 3.x | Lightweight, Standard |
| | Iceberg | 0.12.x | Lightweight, Standard |
diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/design_and_concept/basic_concept.md b/i18n/zh-CN/docusaurus-plugin-content-docs/current/design_and_concept/basic_concept.md
index 5eac266221..3195b2850a 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/design_and_concept/basic_concept.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/design_and_concept/basic_concept.md
@@ -10,7 +10,7 @@ sidebar_position: 1
| Group | 数据流组，包含多个数据流，一个Group 代表一个数据接入 | Group 有ID、Name 等属性 |
| Stream | 数据流，一个数据流有具体的流向 | Stream 有ID、Name、数据字段等属性 |
| Node | 数据节点，包括`Extract Node` 和 `Load Node`，分别代表数据源类型和数据流向目标类型 | |
-| InLongMsg | InLong 数据格式，如果从消息队列中直接消费，需要先进行`InLongMsg` 解析 | |
+| InLongMsg | InLong 数据格式，如果从消息队列中直接消费，需要先进行 `InLongMsg` 解析 | |
| Agent | 标准架构使用 Agent 进行数据采集，Agent 代表不同类型的采集能力 | 包含文件 Agent、SQL Agent、Binlog Agent 等 |
| DataProxy | 将接收到的数据转发到不同的消息队列 | 支持数据发送阻塞和落盘重发 |
| Sort | 数据流分拣 | 主要有基于 Flink 的 sort-flink，sort-standalone 本地分拣 |
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 2011ee02c6..2db4d30874 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/introduction.md
@@ -53,13 +53,13 @@ values={[
## 模块
Apache InLong 服务于数据采集到落地的整个生命周期，按数据的不同阶段提供不同的处理模块，主要包括：
-- **inlong-agent**，数据采集 Agent，支持从指定目录或文件读取常规日志、逐条上报。后续也将扩展 DB 采集等能力。
+- **inlong-agent**，数据采集服务，包括文件采集、DB采集等。
- **inlong-dataproxy**，一个基于 Flume-ng 的 Proxy 组件，支持数据发送阻塞和落盘重发，拥有将接收到的数据转发到不同 MQ（消息队列）的能力。
- **inlong-tubemq**，腾讯自研的消息队列服务，专注于大数据场景下海量数据的高性能存储和传输，在海量实践和低成本方面有着良好的核心优势。
- **inlong-sort**，对从不同的 MQ 消费到的数据进行 ETL 处理，然后汇聚并写入 Hive、ClickHouse、Hbase、Iceberg 等存储系统。
- **inlong-manager**，提供完整的数据服务管控能力，包括元数据、任务流、权限，OpenAPI 等。
- **inlong-dashboard**，用于管理数据接入的前端页面，简化整个 InLong 管控平台的使用。
-- **inlong-audit**，对InLong系统的Agent、DataProxy、Sort模块的入流量、出流量进行实时审计对账。
+- **inlong-audit**，对 InLong 系统的 Agent、DataProxy、Sort 模块的入流量、出流量进行实时审计对账。
## 已支持数据节点（更新中）
| Type | Name | Version | Architecture |
@@ -68,11 +68,11 @@ Apache InLong 服务于数据采集到落地的整个生命周期，按数据的
| | File | None | Standard |
| | Kafka | 2.x | Lightweight, Standard |
| | MySQL | 5.6, 5.7, 8.0.x | Lightweight, Standard |
-| | MongoDB | >= 3.6 | Lightweight |
+| | MongoDB | >= 3.6 | Lightweight, Standard |
| | Oracle | 11,12,19 | Lightweight |
-| | PostgreSQL | 9.6, 10, 11, 12 | Lightweight |
+| | PostgreSQL | 9.6, 10, 11, 12 | Lightweight, Standard |
| | Pulsar | 2.8.x | Lightweight |
-| | SQLServer | 2012, 2014, 2016, 2017, 2019 | Lightweight |
+| | SQLServer | 2012, 2014, 2016, 2017, 2019 | Lightweight, Standard |
| Load Node | Auto Consumption | None | Standard |
| | Hive | 1.x, 2.x, 3.x | Lightweight, Standard |
| | Iceberg | 0.12.x | Lightweight, Standard |