[INLONG-1119][Doc] Fix Quick Start Chapter

docs/quick_start/data_ingestion/file_pulsar_clickhouse_example.md

@@ -19,7 +19,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -76,12 +76,12 @@ Back to [Ingestion] page, wait for [configuration success].
 
 ## Test Data
 ### Enter Agent Container
-```
+```shell
 docker exec -it agent /bin/bash
 ```
 
 ### Send Data
-```
+```shell
 # collect file /data/collect-data/test.log data source configuration path and total of 10000 data packets are sent.
 for i in {1..10000};do echo "name_$i | $i" >> /data/collect-data/test.log;done
 ```

docs/quick_start/data_ingestion/mysql_kafka_clickhouse_example.md

@@ -27,7 +27,7 @@ docker run -d --name kafka -p 9092:9092 -e KAFKA_BROKER_ID=0 -e KAFKA_ZOOKEEPER_
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```

docs/quick_start/offline_data_sync/airflow_example.md

@@ -19,7 +19,7 @@ Download the [connectors](https://inlong.apache.org/downloads/) corresponding to
 
 ## 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.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -37,7 +37,7 @@ Password: inlong
 
 Execute the following SQL statement:
 
-```mysql
+```sql
 CREATE TABLE sink_table (
     id INT AUTO_INCREMENT PRIMARY KEY,
     name VARCHAR(255) NOT NULL,

docs/quick_start/offline_data_sync/dolphinscheduler_example.md

@@ -22,7 +22,7 @@ Download the [connectors](https://inlong.apache.org/downloads/) corresponding to
 
 ## 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.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -40,7 +40,7 @@ Password: inlong
 
 Execute the following SQL statement:
 
-```mysql
+```sql
 CREATE TABLE sink_table (
     id INT AUTO_INCREMENT PRIMARY KEY,
     name VARCHAR(255) NOT NULL,
@@ -112,17 +112,17 @@ View the DolphinScheduler task instance logs. The following logs indicate that t
 Use the Pulsar SDK to produce data into the Pulsar topic. An example is as follows:
 
 ```java
-        // Create Pulsar client and producer
-        PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
-        Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
-
-        // Send messages
-        for (int i = 0; i < 10000; i++) {
-            // Field separator is |
-            String msgStr = i + "|msg-" + i;
-            MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
-            System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
-        }
+// Create Pulsar client and producer
+PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
+Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
+
+// Send messages
+for (int i = 0; i < 10000; i++) {
+    // Field separator is |
+    String msgStr = i + "|msg-" + i;
+    MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
+    System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
+}
 ```
 
 ### Data Validation

docs/quick_start/offline_data_sync/quartz_example.md

@@ -19,7 +19,7 @@ Download the [connectors](https://inlong.apache.org/downloads/) corresponding to
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address `http://localhost`, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -29,13 +29,17 @@ Click [Clusters] -> [ClusterTags] -> [Create] on the page to specify the cluster
 
 ![Create Cluster Tag](img/pulsar_mysql/quartz/cluster_tag.png)
 
-**caution: `default_cluster` is the default ClusterTags for each component. If you decide to use a different name, make sure to update the corresponding tag configuration accordingly.**
+:::caution
+`default_cluster` is the default ClusterTags for each component. If you decide to use a different name, make sure to update the corresponding tag configuration accordingly.
+:::
 
 ### Register Pulsar Cluster
 
 ![Create Pulsar](img/pulsar_mysql/quartz/create_pulsar_cluster.png)
 
-**You can refer to the screenshot information to fill in details such as cluster name, associated tag, and Pulsar cluster address.**
+:::info
+You can refer to the screenshot information to fill in details such as cluster name, associated tag, and Pulsar cluster address.
+:::
 
 ## Task Creation
 ### Create Data Stream Group
@@ -115,17 +119,17 @@ Return to the [Synchronization] page and wait for the task configuration to succ
 
 Use the Pulsar SDK to produce data into the Pulsar topic. An example is as follows:
 ```java
-        // Create Pulsar client and producer
-        PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
-        Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
-
-        // Send messages
-        for (int i = 0; i < 10000; i++) {
-            // Field separator is |
-            String msgStr = i + "|msg-" + i;
-            MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
-            System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
-        }
+// Create Pulsar client and producer
+PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
+Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
+
+// Send messages
+for (int i = 0; i < 10000; i++) {
+    // Field separator is |
+    String msgStr = i + "|msg-" + i;
+    MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
+    System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
+}
 ```
 
 ### Data Validation

docs/quick_start/realtime_data_sync/mysql_clickhouse_example.md

@@ -23,7 +23,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```

docs/quick_start/realtime_data_sync/mysql_iceberg_example.md

@@ -20,7 +20,7 @@ Please refer to the [Installation Tutorial](https://iceberg.apache.org/hive-quic
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -67,7 +67,7 @@ Back to [Synchronization] page, wait for [success].
 
 ## Test Data
 ### Send Data
-```
+```bash
 #!/bin/bash
 
 # MySQL info

docs/quick_start/realtime_data_sync/mysql_starrocks_example.md

@@ -21,7 +21,7 @@ Please refer to the [Installation Tutorial](https://docs.starrocks.io/docs/quick
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -64,7 +64,7 @@ Back to [Synchronization] page, wait for [success].
 
 ## Test Data
 ### Send Data
-```
+```bash
 #!/bin/bash
 
 # MySQL info

docs/quick_start/realtime_data_sync/pulsar_clickhouse_example.md

@@ -23,7 +23,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## Cluster Initialize
 When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.
-```
+```properties
 User: admin
 Password: inlong
 ```

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/data_ingestion/file_pulsar_clickhouse_example.md

@@ -18,7 +18,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## 集群初始化
 容器启动成功后，访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录：
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -73,12 +73,12 @@ Service URL 为 `pulsar://pulsar:6650`，Admin URL 为 `http://pulsar:8080`。
 
 ## 测试数据
 ### 进入 Agent 容器
-```
+```shell
 docker exec -it agent /bin/bash
 ```
 
 ### 发送数据
-```
+```shell
 # 采集文件 /data/collect-data/test.log 数据源配置路径，总共发送 10000 条
 for i in {1..10000};do echo "name_$i | $i" >> /data/collect-data/test.log;done
 ```

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/data_ingestion/mysql_kafka_clickhouse_example.md

@@ -26,7 +26,7 @@ docker run -d --name kafka -p 9092:9092 -e KAFKA_BROKER_ID=0 -e KAFKA_ZOOKEEPER_
 
 ## 集群初始化
 容器启动成功后，访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录：
-```
+```properties
 User: admin
 Password: inlong
 ```

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/airflow_example.md

@@ -19,7 +19,7 @@ sidebar_position:  3
 
 ## 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：
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -36,7 +36,7 @@ Password: inlong
 
 执行如下 Sql 语句：
 
-```mysql
+```sql
 CREATE TABLE sink_table (
     id INT AUTO_INCREMENT PRIMARY KEY,
     name VARCHAR(255) NOT NULL,

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/dolphinscheduler_example.md

@@ -21,7 +21,7 @@ sidebar_position: 2
 
 ## 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：
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -38,7 +38,7 @@ Password: inlong
 
 执行如下 Sql 语句：
 
-```mysql
+```sql
 CREATE TABLE sink_table (
     id INT AUTO_INCREMENT PRIMARY KEY,
     name VARCHAR(255) NOT NULL,
@@ -111,17 +111,17 @@ CREATE TABLE sink_table (
 通过 Pulsar SDK 生产数据写入的 Pulsar topic 中，示例如下：
 
 ```java
-        // Create Pulsar client and producer
-        PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
-        Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
-
-        // Send messages
-        for (int i = 0; i < 10000; i++) {
-            // Field separator is |
-            String msgStr = i + "|msg-" + i;
-            MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
-            System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
-        }
+// 创建 pulsar client 和 producer
+PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
+Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
+
+// 发送消息
+for (int i = 0; i < 10000; i++) {
+    // 字段分隔符为 |
+    String msgStr = i + "|msg-" + i;
+    MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
+    System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
+}
 ```
 
 ### 数据验证

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/offline_data_sync/quartz_example.md

@@ -19,7 +19,7 @@ sidebar_position: 1
 
 ## 集群初始化
 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:
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -113,17 +113,17 @@ CREATE TABLE sink_table (
 
 通过 Pulsar SDK 生产数据写入的 Pulsar topic 中，示例如下：
 ```java
-        // 创建 pulsar client 和 producer
-        PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
-        Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
-
-        // 发送消息
-        for (int i = 0; i < 10000; i++) {
-            // 字段分隔符为 |
-            String msgStr = i + "|msg-" + i;
-            MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
-            System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
-        }
+// 创建 pulsar client 和 producer
+PulsarClient pulsarClient = PulsarClient.builder().serviceUrl("pulsar://localhost:6650").build();
+Producer<byte[]> producer = pulsarClient.newProducer().topic("public/default/test").create();
+
+// 发送消息
+for (int i = 0; i < 10000; i++) {
+    // 字段分隔符为 |
+    String msgStr = i + "|msg-" + i;
+    MessageId msgId = producer.send(msgStr.getBytes(StandardCharsets.UTF_8));
+    System.out.println("Send msg : " + msgStr + " with msgId: " + msgId);
+}
 ```
 
 ### 数据验证

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/realtime_data_sync/mysql_clickhouse_example.md

@@ -23,7 +23,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## 集群初始化
 当所有容器都成功启动后，可以访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录:
-```
+```properties
 User: admin
 Password: inlong
 ```

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/realtime_data_sync/mysql_iceberg_example.md

@@ -20,7 +20,7 @@ sidebar_position: 3
 
 ## 集群初始化
 容器启动成功后，访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录：
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -67,7 +67,7 @@ Password: inlong
 
 ## 测试数据
 ### 发送数据
-```
+```bash
 #!/bin/bash
 
 # MySQL info

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/realtime_data_sync/mysql_starrocks_example.md

@@ -21,7 +21,7 @@ sidebar_position: 2
 
 ## 集群初始化
 容器启动成功后，访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录：
-```
+```properties
 User: admin
 Password: inlong
 ```
@@ -61,7 +61,7 @@ Password: inlong
 
 ## 测试数据
 ### 发送数据
-```
+```shell
 #!/bin/bash
 
 # MySQL info

i18n/zh-CN/docusaurus-plugin-content-docs/current/quick_start/realtime_data_sync/pulsar_clickhouse_example.md

@@ -23,7 +23,7 @@ docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLIC
 
 ## 集群初始化
 当所有容器都成功启动后，可以访问 InLong Dashboard 地址 http://localhost，并使用以下默认账号登录:
-```
+```properties
 User: admin
 Password: inlong
 ```