Kafka is a distributed message queue service that features high throughput and high scalability. Kafka is widely used for big data analytics such as log collection, data aggregation, streaming processing, and online and offline analysis. It is indispensable for the big data ecosystem. This topic describes how to synchronize data from an Apsara PolarDB for MySQL cluster to a user-created Kafka cluster by using Data Transmission Service (DTS). The data synchronization feature allows you to extend message processing capabilities.
Prerequisites
- The version of the user-created Kafka cluster is 0.10 or 1.0.
- A topic is created in the Kafka cluster to receive the synchronized data.
- The binary logging feature is enabled for the Apsara PolarDB for MySQL cluster. For more information, see Enable binary logging.
Precautions
The source database must have PRIMARY KEY or UNIQUE constraints and all fields must be unique. Otherwise, the destination database may contain duplicate data records.
Limits
- You can select only tables as the objects to be synchronized.
- DTS does not automatically update the objects to be synchronized based on their names.
Note DTS does not synchronize the data in a renamed table to the destination Kafka cluster. This applies if the new table name is not included in the objects to be synchronized. To synchronize the data in a renamed table to the destination Kafka cluster, you must modify the objects to be synchronized. For more information, see Add an object to a data synchronization task.
Data format
The data that is synchronized to the Kafka cluster is stored in the Avro format. For more information, see DTS Avro schema.
After the data is synchronized to the Kafka cluster, you must parse the data based on the Avro schema.
Procedure
- At the top of the Synchronization Tasks page, select the region where the destination instance resides.
- Configure the source and destination instances.
Section Parameter Description N/A Synchronization Task Name DTS automatically generates a task name. We recommend that you specify an informative name for easy identification. You do not need to use a unique task name. Source Instance Details Instance Type The value of this parameter is set to PolarDB Instance and cannot be changed. Instance Region The region of the source instance. The region is the same as the source region that you selected when you purchased the data synchronization instance. You cannot change the value of this parameter. PolarDB Instance ID Select the ID of the source PolarDB cluster. Database Account Enter the database account of the source PolarDB cluster. The account must have the REPLICATION SLAVE permission, the REPLICATION CLIENT permission, and the permission to perform SELECT operations on the required objects. Database Password Enter the password of the source database account. Destination Instance Details Instance Type - If the Kafka cluster is deployed on an ECS instance, select User-Created Database in ECS Instance
- If the Kafka cluster is deployed on a local server, select User-Created Database Connected over Express Connect, VPN Gateway, or Smart Access
Gateway.
Note If you select User-Created Database Connected over Express Connect, VPN Gateway, or Smart Access Gateway, you must specify the VPC ID, IP address, and port number.
Instance Region The region of the destination instance. The region is the same as the destination region that you selected when you purchased the data synchronization instance. You cannot change the value of this parameter. ECS Instance ID Select the ID of the ECS instance on which the Kafka cluster is deployed. Database Type Select Kafka. Port Number Enter the service port number of the Kafka cluster. The default port number is 9092. Database Account Enter the username that is used to log on to the Kafka cluster. If the authentication is disabled for the Kafka cluster, you do not need to enter the username. Database Password Enter the password of the username. If the authentication is disabled for the Kafka cluster, you do not need to enter the password. Topic - Click Get Topic List.
- Select a topic name from the drop-down list.
Kafka Version Select the version of the destination Kafka cluster. Encryption Select Non-encrypted or SCRAM-SHA-256 based on your business and security requirements. - Configure the processing mode in existing destination tables and the objects to be
synchronized.
Parameter Description Objects to be synchronized Select tables from the Available section and click the
icon to move the tables to the Selected section.
Note- You can select only tables as the objects to be synchronized.
- After an object is synchronized to the destination database, the name of the object remains unchanged. You can change the names of the objects that are synchronized to the destination database by using the object name mapping feature. For more information about how to use this feature, see Specify the name of an object in the destination instance.
- Configure initial synchronization.
Parameter Description Initial Synchronization Select both Initial Schema Synchronization and Initial Full Data Synchronization. Before synchronizing incremental data, DTS synchronizes the schemas and historical data of the required objects from the source database to the destination database. Filter options Ignore DDL in incremental synchronization phase is selected by default. In this case, DTS does not synchronize DDL operations that are performed on the source database during incremental data synchronization. - In the lower-right corner of the page, click Precheck.
Note
- Before you can start the data synchronization task, a precheck is performed. You can start the data synchronization task only after the task passes the precheck.
- If the task fails to pass the precheck, click the
icon next to each failed item to view details. Troubleshoot the issues based on the
causes and run the precheck again.
- Wait until the initial synchronization is complete and the data synchronization task
is in the Synchronizing state.
On the Synchronization Tasks page, view the status of the data synchronization task.
