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new 48702b5a33a [INLONG-1091][Doc] Unify the title and introduction (#1092)
48702b5a33a is described below
commit 48702b5a33a0be6637936a61e2e4011b00a4a6a3
Author: Zkplo <[email protected]>
AuthorDate: Mon Dec 9 10:57:25 2024 +0800
[INLONG-1091][Doc] Unify the title and introduction (#1092)
---
..._pulsar_mysql_example.md => airflow_example.md} | 68 ++++++++++++---------
.../offline_data_sync/dolphinscheduler_example.md | 49 ++++++++++++---
...r_labels.png => airflow_create_cluster_tag.png} | Bin
.../ds_create_cluster_tag.png} | Bin
.../dolphinscheduler/ds_create_data_target.png | Bin 0 -> 74200 bytes
.../dolphinscheduler/ds_create_pulsar_cluster.png | Bin 0 -> 104084 bytes
.../ds_create_synchronization_task.png | Bin 0 -> 58901 bytes
.../offline_data_sync/quartz_example.md | 4 +-
..._pulsar_mysql_example.md => airflow_example.md} | 56 +++++++++--------
.../offline_data_sync/dolphinscheduler_example.md | 47 ++++++++++++--
...r_labels.png => airflow_create_cluster_tag.png} | Bin
...png => airflow_create_synchronization_task.png} | Bin
.../ds_create_cluster_tag.png} | Bin
.../dolphinscheduler/ds_create_data_target.png | Bin 0 -> 75244 bytes
.../dolphinscheduler/ds_create_pulsar_cluster.png | Bin 0 -> 108551 bytes
.../ds_create_synchronization_task.png} | Bin
.../offline_data_sync/quartz_example.md | 4 +-
17 files changed, 155 insertions(+), 73 deletions(-)
diff --git a/docs/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
b/docs/quick_start/offline_data_sync/airflow_example.md
similarity index 61%
rename from docs/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
rename to docs/quick_start/offline_data_sync/airflow_example.md
index 27142ca8587..7be4d8aba79 100644
--- a/docs/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
+++ b/docs/quick_start/offline_data_sync/airflow_example.md
@@ -1,8 +1,9 @@
---
-title: Example of Airflow Offline Synchronization
+title: Airflow Scheduling Engine Example
sidebar_position: 3
---
-In the following content, a complete example will be used to introduce how to
create Airflow scheduling tasks using Apache InLong and complete offline data
synchronization from Pulsar to MySQL.
+
+In the following sections, we will walk through a complete example to
demonstrate how to integrate the third-party scheduling engine Airflow into
Apache InLong to create an offline data synchronization from Pulsar to MySQL.
## Deployment
### Install InLong
@@ -17,17 +18,22 @@ Download the
[connectors](https://inlong.apache.org/downloads/) corresponding to
> Currently, Apache InLong's offline data synchronization capability only
> supports Flink-1.18, so please download the 1.18 version of connectors.
## Create Clusters And Data Target
+When all containers are successfully started, you can access the InLong
dashboard address `http://localhost`, and use the following default account to
log in.
+```
+User: admin
+Password: inlong
+```
-### Create Cluster Label
-
+### Create Cluster Tag
+
### Register Pulsar Cluster
-
+
### Create Data Target
-
+
Execute the following SQL statement:
@@ -39,71 +45,73 @@ CREATE TABLE sink_table (
);
```
-## Airflow Initialization
+## Airflow Initialize
-### Get Initial DAG
+### Get Original DAG
-They can be obtained from [Inlong](https://github.com/apache/inlong).
+They can be obtained from [InLong](https://github.com/apache/inlong).
-
+
> Airflow does not provide an API for DAG creation, so two original DAGs are
> required. `dag_creator` is used to create offline tasks, and `dag_cleaner`
> is used to clean up offline tasks regularly.
-### Create Initial DAG
+### Create Original DAG
Place the DAG file in the Airflow default DAG directory and wait for a while.
The Airflow scheduler will scan the directory and load the DAG:
-
+
### Airflow REST API
By default, Airflow will reject all REST API requests. Please refer to the
[Airflow official
documentation](https://airflow.apache.org/docs/apache-airflow-providers-fab/stable/auth-manager/api-authentication.html)
for configuration.
-### Inlong Manager Configuration
+### Configure InLong Manager
-Modify the configuration file according to the configuration file requirements
and restart Inlong Manager.
+Modify the configuration file according to the configuration file requirements
and restart InLong Manager.
```properties
-# Inlong Manager URL accessible by the scheduler
+# InLong Manager URL accessible by the scheduler
schedule.engine.inlong.manager.url=http://inlongManagerIp:inlongManagerPort
# Management URL for Airflow
schedule.engine.airflow.baseUrl=http://airflowIP:airflowPort
# Username and password for Airflow REST API authentication
schedule.engine.airflow.username=airflow
schedule.engine.airflow.password=airflow
-# Connection used to save Inlong Manager authentication information
+# Connection used to save InLong Manager authentication information
schedule.engine.airflow.connection.id=inlong_connection
# The ids of the two original DAGs
schedule.engine.airflow.cleaner.id=dag_cleaner
schedule.engine.airflow.creator.id=dag_creator
```
-## Offline Synchronization Task Creation
+## Task Creation
### Create Synchronization Task
-
+
+
### Create Data Stream Group
-
+
-Please refer to the following steps: [Use Quartz built-in scheduling
engine](./quartz_example.md)
+Please refer to the following steps: [Quartz Scheduling Engine
Example](./quartz_example.md)
### Create Airflow Offline Task
-After approval and configuration, Inlong Manager will trigger `dag_creator`
through the Airflow API to create the offline task DAG:
+After approval and configuration, InLong Manager will trigger `dag_creator`
through the Airflow API to create the offline task DAG:
-
+
-
+
> Offline task DAG may not be scheduled immediately, because Airflow will scan
> DAG files regularly and add them to the schedule, so it may take some time.
The offline task execution results are as follows:
-
+
-> Airflow will periodically call the interface provided by Inlong Manager to
submit Flink tasks according to the configuration in the `Create Data Stream
Group` section. This is why the authentication information of Inlong Manager
needs to be saved in the `Inlong Manager Configuration` section.
+> Airflow will periodically call the interface provided by InLong Manager to
submit Flink tasks according to the configuration in the `Create Data Stream
Group` section. This is why the authentication information of InLong Manager
needs to be saved in the `Configure InLong Manager` section.
## Test Data
-### Send Data
+### Sending Data
+
+Use the Pulsar SDK to produce data into the Pulsar topic. An example is as
follows:
-The example of using Pulsar SDK to write production data to a Pulsar topic is
as follows:
```java
// Create pulsar client and producer
PulsarClient pulsarClient =
PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
@@ -118,8 +126,8 @@ for (int i = 0; i < 10000; i++) {
}
```
-### Data Verification
+### Data Validation
-Then enter Mysql and check the database table data. You can see that the data
has been synchronized to MySQL.
+Then enter MySQL to check the data in the table:
-
+
diff --git a/docs/quick_start/offline_data_sync/dolphinscheduler_example.md
b/docs/quick_start/offline_data_sync/dolphinscheduler_example.md
index fc50ab1c90a..40a04438936 100644
--- a/docs/quick_start/offline_data_sync/dolphinscheduler_example.md
+++ b/docs/quick_start/offline_data_sync/dolphinscheduler_example.md
@@ -1,9 +1,9 @@
---
-title: Use DolphinScheduler third-party scheduling engine
+title: DolphinScheduler Scheduling Engine Example
sidebar_position: 2
---
-In the following content, we will introduce how to use DolphinScheduler, a
third-party schedule engine in Apache InLong to create offline data
synchronization.
+In the following sections, we will walk through a complete example to
demonstrate how to integrate the third-party scheduling engine DolphinScheduler
into Apache InLong to create an offline data synchronization from Pulsar to
MySQL.
## Deployment
@@ -20,10 +20,40 @@ Download the
[connectors](https://inlong.apache.org/downloads/) corresponding to
> Currently, Apache InLong's offline data synchronization capability only
> supports Flink-1.18, so please download the 1.18 version of connectors.
-### Operations on DolphinScheduler
+## Create Clusters And Data Target
+When all containers are successfully started, you can access the InLong
dashboard address `http://localhost`, and use the following default account to
log in.
+```
+User: admin
+Password: inlong
+```
+
+### Create Cluster Tag
+
+
+### Register Pulsar Cluster
+
+
+
+### Create Data Target
+
+
+
+Execute the following SQL statement:
+
+```mysql
+CREATE TABLE sink_table (
+ id INT AUTO_INCREMENT PRIMARY KEY,
+ name VARCHAR(255) NOT NULL,
+ create_time TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+```
+
+## DolphinScheduler Initialize
+### Deploy DolphinScheduler
Before using DolphinScheduler as your scheduling engine, please make sure you
have a working DolphinScheduler on hand. If you need to deploy a
DolphinScheduler for yourself, please refer to the [DolphinScheduler Official
Document](https://dolphinscheduler.apache.org/zh-cn).
+### Get DolphinScheduler token
@@ -36,7 +66,7 @@ Set parameters for the token according to the steps in the
figure, include [Expi
-### Modify configuration in InLong Manager
+### Configure InLong Manager
For third-party scheduling engine, we need to modify configurations in manager.
@@ -50,13 +80,19 @@ For DolphinScheduler engine there are following
configurations need to be modifi
After doing this, restart the InLong Manager to ensure the configuration is
enabled.
-### Use DolphinScheduler in offline synchronization
+## Task Creation
+### Create Synchronization Task
+
+
+### Create Data Stream Group
During configure the offline synchronization task, choose DolphinScheduler
when selecting the scheduling engine, then configure other parameters.
-For details about how to manage clusters and configure data nodes, see [Use
Quartz built-in scheduling engine](quartz_example.md).
+For details about how to manage clusters and configure data nodes, see [Quartz
Scheduling Engine Example](quartz_example.md).
+
+### Create DolphinScheduler Offline Task
After approval data flow, return to the [Synchronization] page and wait for
the task configuration to succeed. Once configured successfully, the
DolphinScheduler will periodically calls back InLong to synchronize offline
data and the Manager will periodically submit Flink Batch Jobs to the Flink
cluster.
@@ -71,7 +107,6 @@ View the DolphinScheduler task instance logs. The following
logs indicate that t
## Test Data
-
### Sending Data
Use the Pulsar SDK to produce data into the Pulsar topic. An example is as
follows:
diff --git
a/docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_labels.png
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_tag.png
similarity index 100%
copy from
docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_labels.png
copy to
docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_tag.png
diff --git
a/docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_labels.png
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_cluster_tag.png
similarity index 100%
rename from
docs/quick_start/offline_data_sync/img/pulsar_mysql/airflow/airflow_create_cluster_labels.png
rename to
docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_cluster_tag.png
diff --git
a/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_data_target.png
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_data_target.png
new file mode 100644
index 00000000000..d0b5b0a4f10
Binary files /dev/null and
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_data_target.png
differ
diff --git
a/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_pulsar_cluster.png
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_pulsar_cluster.png
new file mode 100644
index 00000000000..16e9af7cfa7
Binary files /dev/null and
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_pulsar_cluster.png
differ
diff --git
a/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_synchronization_task.png
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_synchronization_task.png
new file mode 100644
index 00000000000..9efa01864bb
Binary files /dev/null and
b/docs/quick_start/offline_data_sync/img/pulsar_mysql/dolphinscheduler/ds_create_synchronization_task.png
differ
diff --git a/docs/quick_start/offline_data_sync/quartz_example.md
b/docs/quick_start/offline_data_sync/quartz_example.md
index 503d5cf2a86..0a392178270 100644
--- a/docs/quick_start/offline_data_sync/quartz_example.md
+++ b/docs/quick_start/offline_data_sync/quartz_example.md
@@ -1,9 +1,9 @@
---
-title: Use Quartz built-in scheduling engine
+title: Quartz Scheduling Engine Example
sidebar_position: 1
---
-In the following content, we will introduce how to use built-in schedule
engine in Apache InLong to create offline data synchronization from Pulsar to
MySQL through a complete example.
+In the following sections, we will walk through a complete example to
demonstrate how to use Apache InLong's built-in scheduling engine (Quartz) to
create an offline data synchronization from Pulsar to MySQL.
## Deployment
### Install InLong
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_example.md
similarity index 61%
rename from
i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
rename to
i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_example.md
index 27c0f34904d..5ecd4646343 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_pulsar_mysql_example.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_example.md
@@ -1,8 +1,9 @@
---
-title: Airflow 离线同步示例
+title: Airflow 调度引擎示例
sidebar_position: 3
---
-在下面的内容中，将通过一个完整的示例介绍如何使用 Apache InLong 创建 Airflow 调度任务，并完成 Pulsar -> MySQL
的离线数据同步。
+
+在下面的内容中，我们将通过一个完整的示例介绍如何在 Apache InLong 中集成第三方调度引擎 Airflow 来创建 Pulsar 到 MySQL
的离线数据同步。
## 环境部署
### 安装 InLong
@@ -13,21 +14,25 @@ sidebar_position: 3
### 添加 Connectors
-下载与 Flink 版本对应的 [connectors](https://inlong.apache.org/zh-CN/downloads) ，解压后将
`sort-connector-jdbc-[version]-SNAPSHOT.jar` 放在 `/inlong-sort/connectors/` 目录下。
+下载与 Flink 版本对应的 [connectors](https://inlong.apache.org/zh-CN/downloads)，解压后将
`sort-connector-jdbc-[version]-SNAPSHOT.jar` 放在 `/inlong-sort/connectors/` 目录下。
> 当前 Apache InLong 的离线数据同步能力只支持 Flink-1.18 版本，所以请下载 1.18 版本的 connectors。
## 创建集群和数据目标
-
+InLong 服务启动后，可以访问 InLong Dashboard 地址 `http://localhost`，并使用以下默认账号登录：
+```
+User: admin
+Password: inlong
+```
### 创建集群标签
-
+
### 注册 Pulsar 集群
-
+
### 创建数据目标
-
+
执行如下 Sql 语句：
@@ -43,67 +48,66 @@ CREATE TABLE sink_table (
### 获取初始 DAG
-`dag_creator` 和 `dag_cleaner` 可以在 [Inlong](https://github.com/apache/inlong)
获取。
+`dag_creator` 和 `dag_cleaner` 可以在 [InLong](https://github.com/apache/inlong)
获取。
-
+
> Airflow 没有提供 DAG 创建的提供 API ，因此需要两个原始 DAG。`dag_creator`
> 用于创建离线任务，`dag_cleaner` 用于定时去清理离线任务。
### 创建初始 DAG
-首先将 DAG 文件放到 Airflow 默认的 DAG 目录下面，等待一段时间，Airflow 调度器会去扫描该目录，并加载 DAG ：
+首先将 DAG 文件放到 Airflow 默认的 DAG 目录下面，等待一段时间，Airflow 调度器会去扫描该目录，并加载 DAG：
-
+
### Airflow REST API
默认情况下，Airflow 会拒绝所有 REST API 请求。请参考 [Airflow
官方文档](https://airflow.apache.org/docs/apache-airflow-providers-fab/stable/auth-manager/api-authentication.html)
进行配置。
-### Inlong Manager 配置
+### 配置 InLong Manager
-根据配置文件要求，对配置文件进行修改，并重启 Inlong Manager 。
+根据配置文件要求，对配置文件进行修改，并重启 InLong Manager。
```properties
-# Airflow 能够访问到的 Inlong Manager 的 url
+# Airflow 能够访问到的 InLong Manager 的 url
schedule.engine.inlong.manager.url=http://inlongManagerIp:inlongManagerPort
# Airflow 管理页面的 URL
schedule.engine.airflow.baseUrl=http://airflowIP:airflowPort
# 用于 Airflow 的 REST API 认证的用户名和密码
schedule.engine.airflow.username=airflow
schedule.engine.airflow.password=airflow
-# 用来保存 Inlong Manager 认证信息的 Connection
+# 用来保存 InLong Manager 认证信息的 Connection
schedule.engine.airflow.connection.id=inlong_connection
# 两个原始 DAG 的 id
schedule.engine.airflow.cleaner.id=dag_cleaner
schedule.engine.airflow.creator.id=dag_creator
```
-## 离线同步任务创建
-
+## 任务创建
### 创建同步任务
-
+
### 创建数据流组
-
+
-后续步骤请参照: [使用内置的 Quartz 调度引擎](./quartz_example.md)
+后续步骤请参照: [Quartz 调度引擎示例](./quartz_example.md)
### 创建 Airflow 离线任务
-审批并配置成功后，Inlong Manager 会去通过 Airflow API 触发 `dag_creator` 去创建离线任务 DAG ：
+审批并配置成功后，InLong Manager 会去通过 Airflow API 触发 `dag_creator` 去创建离线任务 DAG：
-
+
-
+
>离线任务 DAG 可能不会立即进行调度，因为 Airflow 会定期去扫描 DAG 文件，再将其加入调度中，所以可能需要等待一段时间。
离线任务执行结果如下：
-
+
-> Airflow 会根据`创建数据流组`小节中的配置，定期去调用 Inlong Manager 所提供的接口进行 Flink 任务的提交，这里也是为什么在
`Inlong Manager 配置` 小节中需要保存 Inlong Manager 的认证信息。
+> Airflow 会根据`创建数据流组`小节中的配置，定期去调用 InLong Manager 所提供的接口进行 Flink 任务的提交，这里也是为什么在
`InLong Manager 配置` 小节中需要保存 InLong Manager 的认证信息。
## 测试数据
### 发送数据
@@ -127,4 +131,4 @@ for (int i = 0; i < 10000; i++) {
然后进入 Mysql，查看库表数据，可以看到数据已经同步到 MySQL 中。
-
+
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/dolphinscheduler_example.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/dolphinscheduler_example.md
index 37a6afac039..2375d8dcf75 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/dolphinscheduler_example.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/dolphinscheduler_example.md
@@ -1,9 +1,9 @@
---
-title: 使用第三方 DolphinScheduler 调度引擎
+title: DolphinScheduler 调度引擎示例
sidebar_position: 2
---
-在接下来的内容中，我们将介绍如何在 Apache InLong 中集成第三方调度引擎 DolphinScheduler 来创建离线数据同步。
+在下面的内容中，我们将通过一个完整的示例介绍如何在 Apache InLong 中集成第三方调度引擎 DolphinScheduler 来创建 Pulsar
到 MySQL 的离线数据同步。
## 环境部署
@@ -19,10 +19,39 @@ sidebar_position: 2
下载与 Flink 版本对应的 [connectors](https://inlong.apache.org/zh-CN/downloads)，解压后将
`sort-connector-jdbc-[version]-SNAPSHOT.jar` 放在 `/inlong-sort/connectors/` 目录下。
> 当前 Apache InLong 的离线数据同步能力只支持 Flink-1.18 版本，所以请下载 1.18 版本的 connectors。
-### 在 DolphinScheduler 上的操作
+## 创建集群和数据目标
+InLong 服务启动后，可以访问 InLong Dashboard 地址 `http://localhost`，并使用以下默认账号登录：
+```
+User: admin
+Password: inlong
+```
+### 创建集群标签
+
+
+### 注册 Pulsar 集群
+
+
+
+### 创建数据目标
+
+
+
+执行如下 Sql 语句：
+
+```mysql
+CREATE TABLE sink_table (
+ id INT AUTO_INCREMENT PRIMARY KEY,
+ name VARCHAR(255) NOT NULL,
+ create_time TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+```
+
+## DolphinScheduler 初始化
+### 部署 DolphinScheduler
在使用 DolphinScheduler 作为调度引擎之前，请确保有可以提供服务的 DolphinScheduler 。如果您需要为自己部署一个
DolphinScheduler，请参考 [DolphinScheduler
官方文档](https://dolphinscheduler.apache.org/zh-cn)。
+### 获取 DolphinScheduler 令牌
@@ -35,7 +64,7 @@ sidebar_position: 2
-### 修改 InLong Manager 中的配置
+### 配置 InLong Manager
对于第三方调度引擎，我们需要在 InLong Manager 中修改配置。
@@ -49,13 +78,19 @@ sidebar_position: 2
完成这些操作后，重新启动 InLong Manager 以确保配置成功启用。
-### 在离线同步任务中使用 DolphinScheduler
+## 任务创建
+### 创建同步任务
+
+
+### 创建数据流组
在配置离线同步任务时，在选择调度引擎时选择 DolphinScheduler，然后配置其他参数。
-集群管理和相关数据节点的配置请参见[使用内置的 Quartz 调度引擎](quartz_example.md)。
+集群管理和相关数据节点的配置请参见 [Quartz 调度引擎示例](quartz_example.md)。
+
+### 创建 DolphinScheduler 离线任务
审批数据流后，返回【数据同步】页面，等待任务配置成功，配置成功后，DolphinScheduler 将定期回调 InLong Manager，并由
InLong Manager 周期提交 Flink Batch Job 到 Flink 集群。
diff --git
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---
-title: 使用内置的 Quartz 调度引擎
+title: Quartz 调度引擎示例
sidebar_position: 1
---
-在下面的内容中，我们将通过一个完整的示例介绍如何使用 Apache InLong 内置的调度引擎创建 Pulsar -> MySQL 的离线数据同步。
+在下面的内容中，我们将通过一个完整的示例介绍如何使用 Apache InLong 内置的调度引擎 (Quartz) 创建 Pulsar 到 MySQL
的离线数据同步。
## 环境部署
### 安装 InLong
