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new 46b330f421c [INLONG-956][Doc] Update the user manual for Dashboard
(#1125)
46b330f421c is described below
commit 46b330f421cc49d202e64a2fdfc42665ad15ef72
Author: James Zow <james...@163.com>
AuthorDate: Tue Feb 25 19:02:52 2025 +0800
[INLONG-956][Doc] Update the user manual for Dashboard (#1125)
* [Improve][Doc] improve dashboard guide
* Add Create Data Stream Group
* [Improve][Doc] Remove image resources that are not used by the dashboard
guide.
* [Improve][Doc] Rename image resources
* [Improve][Doc] Add the image resources needed for the dashboard guide
* [Improve][Doc] Improve Dashboard Guide
---
docs/user_guide/dashboard_usage.md | 319 +++++++++++----------
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.../current/user_guide/dashboard_usage.md | 269 ++++++++++++-----
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51 files changed, 369 insertions(+), 219 deletions(-)
diff --git a/docs/user_guide/dashboard_usage.md
b/docs/user_guide/dashboard_usage.md
index 854dace0e26..40dcd918112 100644
--- a/docs/user_guide/dashboard_usage.md
+++ b/docs/user_guide/dashboard_usage.md
@@ -1,247 +1,270 @@
---
-title: Dashboard Guide
+title: Dashboard
sidebar_position: 1
---
-## User Login
-
-Requires the user to enter the account name and password of the system,
default account is `admin inlong`.
-
-
-
-## Data Access
+## Overview
+The guide in this section will show you how to manage data flows through the
`Inlong` dashboard and introduce some management configurations.
+Through this guide, you will learn to perform operations such as data access,
data consumption, data synchronization, and cluster management.
-The data access module displays a list of all tasks connected to the system
within the current user authority, and can
-view, edit, update and delete the details of these tasks.
+## Getting started
+To start using the `InLong` dashboard, please deploy it first. Here are
several ways to do it:
-Click [Create], there are two steps to fill in data access information: Group
information, data stream.
+- [Standalone](/deployment/standalone.md)
+- [Docker](/deployment/docker.md)
+- [Kubernetes](/deployment/k8s.md)
+- [Bare Metal](/deployment/bare_metal.md)
-
+:::tip
+We recommend using `docker` for deployment.
+:::
-### Data Stream Group Information
+## User Login
-
+Requires the user to enter the system account name and password. The default
account name is `admin` and the password is `inlong`.
+It is recommended that you change the password in time after logging in.
-#### Access Requirements
+
-Access requirements require users to choose message middleware: high
throughput (TUBE) or High reliability (PULSAR):
+## Data Access
-- high throughput (Inlong TubeMQ): high-throughput message transmission
component, suitable for log message transmission.
-- high reliability (Apache PULSAR): high-reliability message transmission
component, suitable for billing transmission.
+The data access module is responsible for aggregating data from various data
sources into a unified storage service, enabling further data queries and
analysis.
-#### Group Information
+### Create Data Stream Group
-You are required to fill in basic data stream group information for access
tasks.
+Click on [Create] button, this step requires you to fill in the basic
information of the data flow group.
-- Group Name: Unified lowercase English name, please try to include the
product name and concise
- specifications, such as pay_base
-- Group Label: the label of the group, easy to use and retrieve, up to 128
characters
-- Group responsible person: at least 1 people, the group responsible person
can view and modify group
- information, add and modify all access configuration items
-- Group introduction: Cut SMS to introduce the group background and
application of this access task:
+
-#### Access Scale
+- **InLong group id**: Unified lowercase English name, please try to include
the product name and concise
+ specifications, such as pay_base.
+- **InLong group name**: Custom data group name.
+- **InLong group owners**: The data stream group owner can view and modify
group information,
+ add and modify all access configuration items.
+- **Description**: Simple text introduction to data stream group
+- **MQ type**: Choose message middleware of MQ.
-The scale of access requires users to judge the scale of access data in
advance, to allocate computing and storage
-resources later.
+Currently, supports three message middleware of MQ. we use TubeMQ as an
example.
+you can also check
[Kafka](/quick_start/data_ingestion/mysql_kafka_clickhouse_example.md) data
access example
+and [Pulsar](/quick_start/data_ingestion/file_pulsar_clickhouse_example.md)
data access example.
-### Data Stream
+:::info MQ Type
+- Apache Kafka: high throughput and low latency, and can handle large-scale
data streams.
+- Apache Pulsar: high-reliability message transmission component, suitable for
billing transmission.
+- InLong TubeMQ: high-throughput message transmission component, suitable for
log message transmission.
+:::
-Click [Next] to enter the data stream information filling step. There are four
modules for data stream information filling:
-basic information, data source, data information, and data stream.
+
-In the data stream process, you can click [Create] to create a new data stream:
+Click on [Next] button, to enter the data stream information filling step.
-
+### Create Data Stream
-#### Basic Information
+Data stream has a specific data source, data format and data sink. Click
[Create] button to create a new data stream:
-You are required to fill in the basic information of the data stream in the
access task:
+
-- Data stream id: The prefix is automatically generated according to the
product/project, which is unique in a
- specific group and is consistent with the stream id in the data source and
the storage table
-- Data stream name: interface information description, the length is limited
to 64 characters (32 Chinese characters)
-- Data stream owner: The data stream owner can view and modify data stream
information, add and modify all access
- configuration items
-- Introduction to data stream: simple text introduction to data stream
+#### Step 1: Create Data Stream Information
-#### Data Sources
+- **Stream id**: The prefix is automatically generated according to the
product/project, which is unique in a
+ specific group and is consistent with the stream id in the data source and
the storage table.
+- **Stream name**: Custom name for a data stream, used to visually identify
the purpose or type of the data stream.
+- **Description**: Simple text introduction to data stream.
+- **Data type**: The data format type transmitted in the data stream.
Supported types: `CSV`, `Key-Value`, `Avro`, `JSON`
+- **Ignore parse error**: Whether to ignore data parsing errors.
+ - `Yes`: skip the invalid data and continue processing.
+ - `No`: stop processing when an error is encountered.
+- **Data encoding**: Character encoding of data, such as `UTF-8`, `GBK`.
+- **Source data separator**: The field separator of the source data.
+- **Source fields**: Schema of the source data fields. Applicable to
structured data formats.
+- **Advanced options**: Additional configuration for data processing.
-You are required to select the source of the data stream.
+
-Currently, two methods of file and independent push are supported, and the
detailed information of the data source can
-be supplemented in the advanced options.
+Click on [Ok] button, to save the data stream information.
-- File: The business data is in the file, and the business machine deploys
InLong Agent, which is read according to
- customized policy rules
-- Autonomous push: Push data to the messaging middleware through the SDK
+#### Step 2: Create Data Source And Data Target
-#### Data Information
+The left side is the data source, and the right side is the data target.
+You can find more examples of create data source and data target in the
**[Data Ingestion]** section under **[Quick Start]**.
-You are required to fill in the data-related information in the data stream.
+
-
+The types supported by the data source are as:
-- Data Format
-- Data encoding
-- Source field separator
-- Source data field
+
-#### Data Storage
+The types supported by the data target are as:
-You are required to select the final flow direction of this data stream, this
part is not currently supports both hive storage
-and autonomous push.
+
-Add HIVE storage:
+After create the data source and data target, click the [Submit] button to
enter the [approval management](#approval-management).
-
+## Data Synchronization
-- Target database: hive database name (prepared to create in advance)
-- Target table: hive table name
-- First-level partition: the field name of the first-level subdirectory of
hdfs data divided by hive data
-- Secondary partition: the field name of the first-level subdirectory of hdfs
data divided by hive data
-- Username: hive server connection account name
-- User password: hive server connection account password
-- HDFS url: Hive bottom HDFS connection
-- JDBC url: jdbc url of hive server
-- Field related information: source field name, source field type, HIVE field
name, HIVE field type, field description,
- and support deletion and addition
+Data synchronization is the process of establishing consistency between source
and target data stores, and the continuous harmonization of the data over time.
+Click the [Create] button to create a data synchronization group.
-## My Application
+
-The approval management function module currently includes my application and
my approval, and all tasks of data access
-and consumption application approval in the management system.
+`InLong` has two data synchronization modes, one is real-time data
synchronization and the other is offline data synchronization.
-
+### Realtime Data Synchronization
-Display the current task list submitted by the applicant for data access and
consumption in the system, click [Details]
-to view the current basic information and approval process of the task.
+Suitable for low-latency scenarios such as real-time monitoring and
transaction flow synchronization
-#### Application Data Access Details
+#### Step 1: Create Realtime Synchronization Data Stream Group
-
+Select the synchronization type of [RealTime]
-Data access task detailed display The current basic information of the
application task includes: applicant-related
-information, basic information about application access, and current approval
process nodes.
+
-## Data Consumption
+- **Group ID**: Unified lowercase English name, please try to include the
product name and concise specifications, such as pay_base.
+- **Group owners**: The data stream group owner can view and modify group
information,
+ add and modify all access configuration items.
+- **Full database migration**: Whether to migrate the entire database.
+- **Sync Type**: Real-time or offline.
+- **Description**: Simple text introduction to data stream group.
-Data consumption currently does not support direct consumption access to data,
and data can be consumed normally after
-the approval process.
+Click the [Next] button to create data stream.
-Click [Create] to enter the data consumption process, and you need to fill in
information related to
-consumption.
+#### Step 2: Create Realtime Synchronization Data Stream
-### Consumer Information
+
-Applicants need to gradually fill in the basic consumer data stream group
information related to data consumption applications in
-the information filling module
+Here are a few examples of creating real-time data synchronization:
-
+- [MySQL to ClickHouse
Example](/quick_start/realtime_data_sync/mysql_clickhouse_example.md)
+- [MySQL to StarRocks
Example](/quick_start/realtime_data_sync/mysql_starrocks_example.md)
+- [MySQL to Iceberg
Example](/quick_start/realtime_data_sync/mysql_iceberg_example.md)
+- [Pulsar to ClickHouse
Example](/quick_start/realtime_data_sync/pulsar_clickhouse_example.md)
-- Consumer group name: The brief name of the
- consumer must be composed of lowercase letters, numbers, and underscores.
The final approval will assign the consumer
- name based on the abbreviation splicing
-- Consumer Responsible Person: At least 2 persons are required to choose the
responsible person; the responsible person
- can view and modify the consumption information
-- Consumer target data stream group id: you need to select the group id of the
consumer data, you can click [Query] and
- select the appropriate group id in the pop-up window
-- Data usage: select data usage usage
-- Data usage description: The applicant needs to briefly explain the items
used and the purpose of the data according to
- their own consumption scenarios After completing the information, click
[Submit], and the data consumption process
- will be formally submitted to the approver before it will take effect.
+### Offline Data Synchronization
-## Synchronization
+Applicable to scenarios such as data warehouse construction and historical
migration.
-The data synchronization module displays a list of all tasks in the
synchronization system within the current user permissions. You can view, edit,
update and delete the details of these tasks.
-Click [New Data Synchronization] to enter the data synchronization process.
You need to fill in the relevant information about the synchronization
information. You can choose two synchronization types: real-time or offline.
+#### Step 1: Create Offline Synchronization Data Stream Group
-
+Select the synchronization type of [Offline], In addition to filling in the
basic data stream group information, you also need to
+fill in offline synchronization related information, such as scheduling rules
and dependency configuration.
-### Base Information
+
-#### Realtime Synchronization
+**Scheduling Rules**:
-After filling in the relevant basic information, you can proceed to the next
step.
+- **Schedule Engine**: Choose `quartz` or `airflow` or `dolphinScheduler`
engine.
+- **Schedule Type**: Choose regular or `Crontab` type.
+- **Schedule Unit**: Select minutes, hours, days, years, etc.
+- **Schedule Interval**: Fill in the schedule unit time.
+- **Delay Time**: Fill in the required delay time.
+- **Valid Time**: Configure the validity time of offline rules.
+- **Self Dependence**: Choose dependency type.
-
+#### Step 2: Create Offline Synchronization Data Stream
-- Data flow group ID: The brief name of the synchronization task, which must
be composed of lowercase letters, numbers, and underscores.
-- Responsible person: The responsible person can view and modify synchronized
information.
-- Entire database migration: Choose whether you need to migrate the entire
database according to your own needs.
+
-#### Offline Synchronization
+Here are a few examples of creating offline data synchronization:
-After filling in the relevant basic information, you also need to fill in the
offline synchronization related information, such as: scheduling rules and
dependency configuration.
+- [Quartz Scheduling Engine
Example](/quick_start/offline_data_sync/quartz_example.md)
+- [DolphinScheduler Scheduling Engine
Example](/quick_start/offline_data_sync/dolphinscheduler_example.md)
+- [Airflow Scheduling Engine
Example](/quick_start/offline_data_sync/airflow_example.md)
-
+## Data Subscription
-Scheduling type: Choose regular or Crontab type according to your own needs.
+Data Subscription provides subscribers bulk data feeds of the data they are
entitled to access.
-##### Regular Type
+
-- Scheduling unit: select minutes, hours, days, weeks, etc. according to your
own needs.
-- Scheduling cycle: Select the cycle according to your own needs, and its unit
is determined by the selection of the scheduling unit.
-- Delay time: fill in the required delay time.
-- Validity time: Configure the validity time of offline rules.
+Click [New subscribe] button to create a new data subscription.
-##### Crontab Type
+
-- Valid time: The time interval can be filled in, the format is: 2021-01-01
00:00-2021-12-31 23:59
-- Crontab expression: Fill in the Crontab expression according to your own
needs.
+- **Consumer group name**: The brief name of the
+ consumer must be composed of lowercase letters, numbers, and underscores.
The final approval will assign the consumer
+ name based on the abbreviation splicing.
+- **Subscription owners**: Owner can view and modify consumption information
+- **Target inLong group id**: Need to Select the target stream group in the
drop-down box.
-## Data Node
+## Data Nodes
The data node module displays the list of data nodes within the current user
permissions. You can view, edit, update and delete the details of these nodes.
-Click [New] to pop up a dialog box for creating a new node. You can choose
different node types, such as: Redis, Kafka, MySQL, etc.
-
+Click [Create] button to pop up a dialog box for create a new node. You can
choose different node types, such as: `Redis`, `Kafka`, `MySQL`, etc.
+
+
-
+
-- Node name: The brief name of the node, which must be composed of lowercase
letters, numbers, and underscores.
-- Node type: Select the type of node.
-- Responsible person: The node responsible person can view and modify node
information.
+- **Name**: The brief name of the node, which must be composed of lowercase
letters, numbers, and underscores.
+- **Type**: Select the type of node.
+- **Owners**: The node responsible person can view and modify node information.
+- **Description**: Simple text introduction to data node.
## Cluster Management
-The cluster management module is divided into two modules: cluster label
management and cluster management. Cluster label management is used to manage
cluster labels, and cluster management is used to manage clusters.
+The cluster management module is divided into two modules: cluster label
management and cluster management. Cluster label
+management is used to manage cluster labels, and cluster management is used to
manage clusters.
### Cluster Tag Management
Cluster label management can add, delete, modify cluster labels, view the
cluster list, bind clusters, etc.
-
+
#### Add New Cluster Label
-
+
-- Cluster label: The brief name of the label, which must be composed of
lowercase letters, numbers, and underscores. Modifying the cluster label name
will also modify the label names in all clusters bound to this label. Make sure
that this label is not used by InlongGroup. .
-- Person in charge: The person in charge can view and modify cluster label
information.
-- Tenant: Select the tenant to be bound.
+- **Cluster tag**: The brief name of the label, which must be composed of
lowercase letters, numbers, and underscores.
+ Modifying the cluster label name will also modify the label names in all
clusters bound to this label.
+ Make sure that this label is not used by InLong Group.
+- **Owners**: The person in charge can view and modify cluster label
information.
+- **Tenant**: Select the tenant to be bound.
+- **Description**: Simple text introduction to cluster label.
#### Bind Cluster
-
+Click [Bind cluster] button to open the Bind cluster information box and
select the cluster you want to bind.
-
+
-- Cluster name: When the cluster list is empty, you need to go to the cluster
management page to create the required cluster so that the cluster label can be
bound to the cluster.
+- **Cluster name**: When the cluster list is empty, you need to go to the
cluster management page to create the required
+ cluster so that the cluster label can be bound to the cluster.
### Cluster Management
Cluster management can add, delete, modify clusters, view the cluster list,
view cluster details, view cluster nodes, etc.
-#### Create New Cluster
+#### Create New Cluster
+
+Click [Create] button to open dialog box for creating a new cluster will pop
up.
+
+
+
+
+
+- **Cluster Name**: The brief name of the cluster, which must be composed of
lowercase letters, numbers, and underscores.
+- **Type**: Select the type of cluster. you can choose different cluster
types, such as `Agent`, `Kafka`, etc.
+- **Owners**: The person in charge of the cluster can view and modify the
cluster information.
+- **Cluster label**: Select the label to be bound.
+- **Description**: Simple text introduction to cluster.
+
+## Approval Management
+
+The approval management function module currently includes my application and
my approval, and all tasks of data access
+and consumption application approval in the management system.
+
+
+
+Click [Detail] to view the current basic information and approval process of
the task,
+display the current task list submitted by the applicant for data access and
consumption in the system.
-Click [New Cluster] and a dialog box for creating a new cluster will pop up.
You can choose different cluster types, such as Agent, Kafka, etc.
+
-
+## FAQ
-
+### Data Stream configuration error
-- Cluster name: The brief name of the cluster, which must be composed of
lowercase letters, numbers, and underscores.
-- Cluster type: Select the type of cluster.
-- Person in charge: The person in charge of the cluster can view and modify
the cluster information.
-- Cluster label: Select the label to be bound.
+Generally, the `MQ` or `Flink` cluster configuration. You can view the error
information on the page, or enter the `Manager`
+container to view detailed logs.
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a/i18n/zh-CN/docusaurus-plugin-content-docs/current/user_guide/dashboard_usage.md
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index 7eb7e9ee1aa..7c2459ee8c5 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/user_guide/dashboard_usage.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/user_guide/dashboard_usage.md
@@ -1,127 +1,254 @@
---
-title: Dashboard 指引
+title: Dashboard
sidebar_position: 1
---
+## 概述
+本节的指南将向您展示如何通过 `Inlong` 仪表板管理数据流，并介绍一些管理配置。
+通过本指南，您将学习执行数据访问、数据消费、数据同步和集群管理等操作。
+
+## 入门
+要开始使用 `InLong` 仪表板，请先部署。以下是几种部署方法：
+
+- [Standalone](/deployment/standalone.md)
+- [Docker](/deployment/docker.md)
+- [Kubernetes](/deployment/k8s.md)
+- [Bare Metal](/deployment/bare_metal.md)
+
+:::tip
+我们建议使用 `docker` 进行部署。
+:::
+
## 用户登录
-需系统使用用户输入账号名称和密码，默认账号是`admin inlong`。
+使用系统需要用户输入系统账号和密码，默认账户为 `admin`，默认密码为 `inlong`。
## 数据接入
-数据接入模块展示目前用户权限内接入系统所有任务列表，可以对这些任务详情查看、编辑更新和删除操作。
+数据访问模块负责将来自各种数据源的数据聚合到统一的存储服务中，以实现进一步的数据查询和分析。
+
+### 创建数据流组
+
+点击【新建接入】按钮，此步骤需要您填写数据流组的基本信息。
+
+
+
+- **数据流组 ID**：统一小写英文名称，请尽量包含产品名称且简洁规范，例如pay_base。
+- **数据流组名称**：自定义数据组名称。
+- **责任人**：数据流群组拥有者可以查看、修改群组信息，添加、修改所有访问配置项。
+- **描述**：数据流组简单介绍
+- **MQ 类型**：选择MQ消息中间件。
+
+目前支持三种MQ消息中间件，这里以TubeMQ为例。你也可以查看
[Kafka](/quick_start/data_ingestion/mysql_kafka_clickhouse_example.md) 数据接入示例
+和 [Pulsar](/quick_start/data_ingestion/file_pulsar_clickhouse_example.md)
数据接入示例。
+
+:::info MQ 类型
+- Apache Kafka: 高吞吐量、低延迟，可以处理大规模数据流。
+- Apache Pulsar: 高可靠性消息传输组件，适用于计费传输场景。
+- InLong TubeMQ: 高吞吐量消息传输组件，适用于日志消息传输场景。
+:::
+
+
+
+点击【下一步】按钮，进入数据流信息填写步骤。
+
+### 创建数据流
+
+数据流有特定的数据源、数据格式和数据接收器。点击【新建数据流】按钮可以创建新的数据流：
+
+
+
+#### 步骤 1: 创建数据流信息
+
+- **数据流 ID**： 前缀根据产品/项目自动生成，这在某个具体的接入中是唯一的，与数据源和入库的表中的数据流ID保持一致。
+- **数据流名称**： 数据流的自定义名称，用于直观地识别数据流的用途或类型。
+- **介绍**: 简单的介绍数据流。
+- **数据格式**： 数据流中传输的数据格式类型。支持的类型有： `CSV`, `Key-Value`, `Avro`, `JSON`
+- **忽略数据解析错误**：是否忽略数据解析错误。
+ - `是`： 跳过无效数据并继续处理。
+ - `否`： 遇到错误时停止处理。
+- **数据编码**： 数据的字符编码，例如：`UTF-8`, `GBK`。
+- **源数据字段分割符**： 源数据的字段分隔符。
+- **源数据字段**： 源数据字段的映射。适用于结构化数据格式。
+- **高级选项**： 用于数据处理的高级设置。
+
+
+
+点击【确定】按钮，保存数据流信息。
+
+#### 步骤 2: 创建数据源和数据目标
+
+左侧是数据源，右侧是数据目标。您可以在**快速开始**下的**数据接入**部分中找到更多创建数据源和数据目标的示例。
+
+
+
+数据源支持的类型如下图：
+
+
+
+数据目标支持的类型如下图：
+
+
+
+创建完数据源和数据目标后，点击【提交审批】按钮进入[审批管理](#审批管理)。
+
+## 数据同步
+
+数据同步是建立数据源和目标数据存储之间一致性的过程，可随着时间持续协调数据。
+点击【新建数据同步】按钮创建数据同步组。
+
+
+
+`InLong` 有两种数据同步模式，一种是实时数据同步，一种是离线数据同步。
+
+### 实时数据同步
+
+适用于实时监控、交易流同步等低延迟场景。
+
+#### 步骤 1: 创建实时同步数据流组
+
+选择【实时】同步类型
+
+
+
+- **数据流组 ID**：统一小写英文名称，请尽量包含产品名称且简洁规范，例如pay_base。
+- **责任人**：数据流群组拥有者可以查看、修改群组信息，添加、修改所有访问配置项。
+- **整库迁移**：是否迁移整个数据库。
+- **同步类型**： 实时或离线。
+- **描述**：对数据流组进行简单的介绍。
+
+点击【下一步】按钮，创建数据流。
+
+#### 步骤 2: 创建实时同步数据流
+
+
+
+以下是创建实时数据同步的几个示例：
+
+- [MySQL 到 ClickHouse
示例](/quick_start/realtime_data_sync/mysql_clickhouse_example.md)
+- [MySQL 到 StarRocks
示例](/quick_start/realtime_data_sync/mysql_starrocks_example.md)
+- [MySQL 到 Iceberg
示例](/quick_start/realtime_data_sync/mysql_iceberg_example.md)
+- [Pulsar 到 ClickHouse
示例](/quick_start/realtime_data_sync/pulsar_clickhouse_example.md)
+
+### 离线数据同步
+
+适用于数据仓库构建，历史迁移等场景。
+
+#### 步骤 1: 创建离线同步数据流组
+
+选择同步类型为【离线】，除了填写基本的数据流组信息外，还需要填写离线同步相关信息，如调度规则、依赖配置等。
+
+
-点击【新建接入】接入流程，数据接入信息填写有两个步骤：Group 信息、数据流。
+**调度规则**:
-
+- **调度引擎**：选择 `quartz` 或 `airflow` 或 `dolphinScheduler` 调度引擎。
+- **调度类型**：选择常规或 `Crontab` 类型.
+- **调度单位**：选择分钟、小时、天、月等。
+- **调度周期**：填写调度单位时间。
+- **延迟时间**：填写所需的延迟时间。
+- **有效时间**：配置离线规则的有效时间。
+- **自身依赖**：选择依赖类型。
-### 数据流 Group 信息
+#### Step 2: 创建离线同步数据流
-
+
-#### 接入要求
+以下是创建离线数据同步的几个示例：
-接入要求需要用户进行选择消息中间件：高吞吐（TUBE）或者高可靠（PULSAR）：
+- [Quartz 调度引擎示例](/quick_start/offline_data_sync/quartz_example.md)
+- [DolphinScheduler
调度引擎示例](/quick_start/offline_data_sync/dolphinscheduler_example.md)
+- [Airflow 调度引擎示例](/quick_start/offline_data_sync/airflow_example.md)
-- 高吞吐（InLong TubeMQ）：高吞吐消息传输组件，适用于日志类的消息传递。
-- 高可靠（Apache Pulsar）：高可靠消息传输组件，适用于计费等场景。
+## 数据订阅
-#### Group 信息
+数据订阅为订阅者提供他们有权访问的数据的批量数据源。
-需要用户对接入任务填写基础数据流 Group 信息。
+
-- Group 英文名称：统一小写英文名称，请尽量包含产品名和简洁规范，如pay_base
-- Group 中文名称：Group 的中文描述，便于使用与检索，最多128个字
-- Group 责任人：至少1人，Group 责任人可查看、修改Group 信息，新增和修改所有接入配置项
-- Group 介绍：简短对此次接入任务Group 背景和应用进行介绍：
+点击【新建订阅】按钮创建一个新的数据订阅。
-#### 接入规模
+
-接入规模需要用户预先针对接入数据进行规模判断，以便后续分配计算和存储资源。
+- **消费组名称**：消费者简称必须由小写字母、数字、下划线组成，最终审批将按照缩写拼接的方式分配消费者名称。
+- **订阅责任人**：责任人可以查看、修改消费信息。
+- **所属的数据流组 ID**：需要在下拉框中选择目标群体。
-### 数据流
+## 数据节点
-点击【下一步】进入到数据流信息填写步骤，数据流信息填写有四个模块：基础信息、数据来源、数据信息、数据流向。
+数据节点模块展示当前用户权限范围内的数据节点列表，可以查看、编辑、更新、删除这些节点的详细信息。
-在数据流流程中可以点击【新建】，创建一个新的数据流信息填写页面：
+点击【新建】按钮弹出创建新节点的弹框，可以选择不同的节点类型，如：`Redis`、`Kafka`、`MySQL` 等。
-
+
-#### 基础信息
+
-需用户对该接入任务中数据流的基础信息进行填写：
+- **节点名称**：节点的简称，必须由小写字母、数字和下划线组成。
+- **类型**：选择节点的类型。
+- **责任人**：节点负责人可以查看、修改节点信息。
+- **描述**：数据节点进行简单的介绍。
-- 数据流ID：前缀根据产品/项目自动生成，这在某个具体的接入中是唯一的，与数据源和入库的表中的数据流ID保持一致
-- 数据流名称：接口信息说明，长度限制为64个英文字符（对应32个中文字符）
-- 数据流责任人：数据流责任人可查看、修改数据流信息，新增和修改所有接入配置项
-- 数据流介绍：数据流简单文本介绍
+## 集群管理
-#### 数据来源
+集群管理模块分为集群标签管理和集群管理两个模块，集群标签管理用于管理集群标签，集群管理用于管理集群。
-需用户选择该数据流的消息来源，目前支持文件、自主推送两种方式，并且可以在高级选项中补充该数据来源详细信息：
+### 集群标签管理
-- 文件：采集数据以文件形式存放，采集机器部署 InLong Agent，根据定制的策略规则进行读取
-- 自主推送：通过 SDK 向消息中间件推送数据
+集群标签管理可以添加、删除、修改集群标签，查看集群列表，绑定集群等。
-#### 数据信息
+
-需用户填写该数据流中数据相关信息：
+#### 创建新的集群标签
-
+
-- 数据格式：数据来源格式，是普通文本类型，或者KV键值对数据
-- 数据编码
-- 源字段分隔符
-- 源数据字段
+- **集群标签**：标签的简称，必须由小写字母、数字和下划线组成。修改集群标签名称会同时修改与该标签绑定的所有集群中的标签名称。
+ 请确保该标签未被InLong Group使用。
+- **负责人**：T负责人可以查看、修改集群标签信息。
+- **租户**：选择需要绑定的租户。
+- **标签描述**：集群标签的文字介绍。
-#### 数据流向
+#### 绑定集群
-需用户对此任务的流向终流向进行选择，此部分为非必填项，目前支持Hive和自主推送两种：
+点击【绑定集群】按钮，打开绑定集群信息框，选择需要绑定的集群。
-HIVE流向：
+
-
+- **集群名称**：当集群列表为空时，需要前往集群管理页面创建集群，这样才能将集群标签绑定到集群上。
-- 目标库：hive数据库名（需要提前准备创建好）
-- 目标表：hive表名
-- 一级分区：hive数据划分hdfs数据一级子目录的字段名
-- 二级分区：hive数据划分hdfs数据一级子目录的字段名
-- 用户名：hiveserver连接账户名
-- 用户密码：hiveserver连接账密码
-- HDFS url：hive底层hdfs连接
-- JDBC url：hiveserver 的jdbcurl
-- 字段相关信息： 源字段名、源字段类型、HIVE字段名、HIVE字段类型、字段描述，并支持删除和新增字段
+### 集群管理
-## 我的申请
+集群管理可以添加、删除、修改集群，查看集群列表，查看集群详细信息，查看集群节点等。
-审批管理功能模块目前包含了我的申请和我的审批，管理系统中数据接入和数据消费申请审批全部任务。
+#### 创建新集群
-
+点击【新建集群】按钮，将弹出创建新集群的弹框。
-展示目前申请人在系统中数据接入、消费提交的任务列表，点击【详情】可以查看目前该任务基础信和审批进程：
+
-#### 申请数据接入详情
+
-
+- **集群名称**：集群的简称，必须由小写字母、数字和下划线组成。
+- **类型**：选择集群类型。您可以选择不同的集群类型，例如 `Agent`，`Kafka` 等。
+- **责任人**：集群责任人可以查看、修改集群信息。
+- **集群标签**：选择需要绑定的集群标签。
+- **集群描述**：集群简单的文字介绍。
-数据接入任务详细展示目前该申请任务基础信息包括：申请人相关信息、申请接入基础信息，以及目前审批进程节点：
+## 审批管理
-## 数据消费
+审批管理功能模块目前包括我的申请和我的审批，以及管理系统中的所有数据访问、消费申请审批等任务。
-数据消费目前不支持直接消费接入数据，需走数据审批流程后方可正常消费数据； 点击【新建消费】，进入数据消费流程，需要对消费信息相关信息进行填写：
+
-### 消费信息
+点击【详情】可以查看该任务当前的基本信息及审批进度，显示申请人当前在系统中提交数据存取和消费的任务列表。
-申请人需在该信息填写模块中逐步填写数据消费申请相关基础消费数据流 Group 信息：
+
-
+## 常见问题
-- 消费组名称：消费者的简要名称，必须是小写字母、数字、下划线组成，最后审批会根据简称拼接分配出消费者名称
-- 消费责任人：自行选择责任人，必须至少2人；责任人可查看、修改消费信息
-- 消费目标数据流Group ID：需要选择消费数据的数据流Group ID，可以点击【查询】后，在弹窗页面中选择合适的数据流Group ID，如下图所示：
-- 数据用途：选择数据使用用途
-- 数据用途说明：需申请人根据自身消费场景，简要说明使用的项目和数据的用途
+### 数据流配置错误
-信息填完完成后，点击【提交】后，会将次数据消费流程正式提交待审批人审批后方可生效。
\ No newline at end of file
+一般是 `MQ` 或者 `Flink` 集群配置错误导致，可以在页面查看错误信息，或者进入 `Manager` 容器查看详细日志。
\ No newline at end of file
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