Data Transmission Service:Use a Kafka client to consume tracked data

Usage notes

• If you enable auto commit when you use the change tracking feature, some data may be committed before it is consumed. This results in data loss. We recommend that you manually commit data.
  Note If data fails to be committed, you can restart the client to continue consuming data from the last recorded consumer offset. However, duplicate data may be generated during this period. You must manually filter out the duplicate data.
• Data is serialized and stored in the Avro format. For more information, see Record.avsc.
  Warning If you are not using the Kafka client that is described in this topic, you must parse the tracked data based on the Avro schema.
• The search unit is second when Data Transmission Service (DTS) calls the offsetForTimes operation. The search unit is millisecond when a native Kafka client calls this operation.

Run the Kafka client

Download the demo code of the Kafka client. For more information about how to use the demo code, see Readme.

Procedure

The following steps show how to run the Kafka client to consume tracked data. In this example, IntelliJ IDEA (Community Edition 2018.1.4 Windows) is used.

1. Create a change tracking task. For more information, see Track data changes from an ApsaraDB RDS for MySQL instance, Track data changes from a PolarDB for MySQL cluster, or Track data changes from a self-managed Oracle database.
2. Create one or more consumer groups. For more information, see Create consumer groups.
3. Download the demo code of the Kafka client and decompress the package.
   Note Click and select Download ZIP to download the package.
4. Open IntelliJ IDEA. In the window that appears, click Open.
   
5. In the dialog box that appears, go to the directory in which the downloaded demo code resides. Find the pom.xml file.
   
6. In the dialog box that appears, select Open as Project.
7. In the Project tool window of IntelliJ IDEA, expand folders to find the demo file of the Kafka client, and double-click the file. The file name is NotifyDemoDB.java.
8. Set the parameters in the NotifyDemoDB.java file.
   

   Parameter	Description	Method to obtain
   USER_NAME	The username of the consumer group. Warning If you are not using the SDK client that is used in this topic, you must specify this parameter in the following format: <Username>-<Consumer group ID>. Example: dtstest-dtsae******bpv. Otherwise, the connection fails.	In the DTS console, click the instance ID. In the left-side navigation pane, click Consume Data. You can obtain the consumer group ID and the corresponding username. Note The password of the consumer group account is automatically specified when you create the consumer group.
   PASSWORD_NAME	The password of the account.
   SID_NAME	The ID of the consumer group.
   GROUP_NAME	The name of the consumer group. Set this parameter to the consumer group ID.
   KAFKA_TOPIC	The topic of the change tracking instance.	In the DTS console, click the instance ID. On the Task Management page, you can obtain the tracked Topic and the network information.
   KAFKA_BROKER_URL_NAME	The endpoint of the change tracking instance. Note If you track data changes over internal networks, the network latency is minimal. This is applicable if the Elastic Compute Service (ECS) instance where you deploy the Kafka client belongs to the classic network or the same virtual private cloud (VPC) as the change tracking instance.
   INITIAL_CHECKPOINT_NAME	The consumer offset of consumed data. The value is a UNIX timestamp. Example: 1592269238. Note You must save the consumer offset. If the consumption process is interrupted, you can specify the consumer offset on the change tracking client to resume data consumption. This prevents data loss. When you start the change tracking client, you can specify the consumer offset to consume data on demand.	The consumer offset of consumed data must be within the data range of the change tracking instance, as shown in the following figure. The consumer offset must be converted into a UNIX timestamp. Note For more information about how to view the data range, see View tracked data changes. You can use a search engine to obtain a UNIX timestamp converter.
   USE_CONFIG_CHECKPOINT_NAME	Specifies whether the client is forced to consume data from the specified consumer offset. Default value: true. The default value retains the data that is received but not processed.	N/A
   SUBSCRIBE_MODE_NAME	Specifies whether to run two or more Kafka clients for a consumer group. If you want to use this feature, set this parameter to subscribe for these Kafka clients. Default value: assign. The default value indicates that only one Kafka client is deployed.	N/A

9. In the top menu bar of IntelliJ IDEA, choose Run > Run to run the client.
   Note The first time you run IntelliJ IDEA, a specific time period is required to load and install the relevant dependency.

Execution result on the Kafka client

The following figure shows that the Kafka client can track data changes from the source database.

You can delete the // characters from the //log.info(ret); string in line 25 of the NotifyDemoDB.java file. Then, run the client again to view the data change information.

FAQ

• Q: Why do I need to record the consumer offset of the Kafka client?

  A: The consumer offset recorded by DTS is the time when DTS receives a commit operation from the Kafka client. The recorded consumer offset may be different from the actual consumption time. If a business application or the Kafka client is unexpectedly interrupted, you can specify an accurate consumer offset to continue data consumption. This prevents data loss or duplicate data consumption.

Mappings between MySQL data types and dataTypeNumber values

Mappings between Oracle data types and dataTypeNumber values

Mappings between PostgreSQL data types and dataTypeNumber values