How to synchronize PolarDB-X 2.0 to Message Queue for Apache Kafka-Data Transmission Service(DTS)-阿里云帮助中心

Prerequisites

A source PolarDB-X 2.0 instance.
A destination Message Queue for Apache Kafka instance with more storage space than is used by the source PolarDB-X 2.0 instance.

Note
See Overview of data synchronization scenarios for the supported versions of source and destination databases.
A topic in the destination Message Queue for Apache Kafka instance to receive synchronized data. For more information, see Step 1: Create a topic.

Limits

Note

DTS does not synchronize foreign keys from the source database to the target database. Consequently, cascading deletes and updates on the source database do not affect the target database.

Type	Description
Source database limits	Tables to be synchronized must have a primary key or a unique constraint, and the fields must be unique. Otherwise, duplicate data may appear in the destination database. Read-only instances of PolarDB-X 2.0 Enterprise Edition are not supported as the source. If you synchronize data at the table level and need to edit objects, such as mapping column names, and the number of tables in a single sync task exceeds 5,000, split the tables into multiple tasks. You can also configure a task to synchronize the entire database. Otherwise, an error may be reported after you submit the task. Binary logs: Enable binary logging in the PolarDB-X 2.0 console. For more information, see Parameter settings. Also, set binlog_row_image to full. Otherwise, the precheck fails and the data synchronization task cannot start. For incremental synchronization tasks, DTS requires that binary logs be retained on the source database for more than 24 hours. For tasks that include both initial full data synchronization and incremental synchronization, DTS requires that binary logs be retained for at least 7 days. You can change the retention period to more than 24 hours after the initial full data synchronization is complete. If binary logs are not retained for the required period, the DTS task may fail because it cannot obtain the logs. In extreme cases, this can lead to data inconsistency or data loss. Issues caused by binary log retention periods shorter than the DTS requirement are not covered by the Service-Level Agreement (SLA). If a table name in the PolarDB-X 2.0 instance contains uppercase letters, only schema synchronization is supported for that table. Synchronization of table groups and databases or tables with the Locality property is not supported. Synchronization of tables whose names are reserved words, such as `select`, is not supported. In a PolarDB-X 2.0 instance, database partitions in DRDS mode cannot be synchronized. Do not run DDL operations that change database or table schemas during schema synchronization or full synchronization. Otherwise, the synchronization task fails. Note During full synchronization, DTS queries the source database. This creates metadata locks that may block DDL operations on the source database.
Other limits	Synchronization of INDEX, PARTITION, VIEW, PROCEDURE, FUNCTION, TRIGGER, and FK objects is not supported. Before you start data synchronization, evaluate the performance of the source and destination databases. We recommend that you perform data synchronization during off-peak hours. Initial full data synchronization consumes read and write resources on both the source and destination databases, which can increase database load. Initial full data synchronization runs concurrent INSERT operations, which causes fragmentation in the destination database tables. As a result, the tablespace of the destination instance is larger than that of the source instance after initial full data synchronization is complete. Do not use tools such as pt-online-schema-change to perform online DDL operations on the synchronization objects in the source database. Otherwise, the synchronization fails. During DTS synchronization, do not write data to the destination database from sources other than DTS. This can cause data inconsistency between the source and destination databases. For example, if you use DMS to perform online DDL operations while other data is being written to the destination database, data loss may occur in the destination database. Only data tables are supported as synchronization objects. Non-data table objects are not supported. Automatic adjustment of synchronization objects is not supported. If you rename a data table within a synchronization object and the new name is not included in the synchronization object, data from that table will no longer be synchronized to the target Kafka cluster. To continue data synchronization for the modified table to the target Kafka cluster, you need to perform the Modify Synchronization Object operation. For more information, see Add Synchronization Object. If the destination Kafka cluster is scaled out or scaled in during synchronization, you must restart the instance. If a task fails, DTS support staff will attempt to restore it within eight hours. During restoration, they may restart the task or adjust its parameters. Note Only DTS task parameters are modified—not database parameters. Parameters that may be adjusted include those listed in Modify instance parameters.
Other notes	DTS periodically updates the `dts_health_check`.`ha_health_check` table in the source database to advance the binary log offset.

Billing

Synchronization type	Pricing
Schema synchronization and full data synchronization	Free of charge.
Incremental data synchronization	Charged. For more information, see Billing overview.

Single-record size limit

The maximum size for a single record written to Kafka is 10 MB. If a row from the source exceeds this limit, DTS cannot write the record, and the synchronization task will be interrupted. To resolve this, exclude the table from the synchronization. If you must synchronize the table, configure the DTS task to include only a subset of its columns by filtering out columns with large fields. If a task is already running, first modify the synchronization objects to remove the table. Then, modify the synchronization objects again to add the table back, this time configuring it to filter out the columns with large fields.

Supported SQL operations

Type	SQL statement
DML	INSERT, UPDATE, and DELETE
DDL	CREATE TABLE, ALTER TABLE, DROP TABLE, RENAME TABLE, and TRUNCATE TABLE Important The RENAME TABLE operation may cause data inconsistency. For example, if the synchronization object is a single table and you rename it on the source instance during synchronization, the data of that table is not synchronized to the destination database. To avoid this issue, you can configure the task to synchronize the entire database that contains the table. Make sure that the database to which the table belongs both before and after the RENAME TABLE operation is included in the synchronization objects. CREATE FUNCTION, DROP FUNCTION, CREATE TRIGGER, and DROP TRIGGER CREATE INDEX and DROP INDEX Note If the source database is an Enterprise Edition PolarDB-X 2.0 instance, the CREATE FUNCTION and CREATE INDEX operations cannot be synchronized.

Procedure

Go to the data synchronization task list page in the destination region. You can do this in one of two ways.
DTS console
1. Log on to the DTS console.
2. In the navigation pane on the left, click Data Synchronization.
3. In the upper-left corner of the page, select the region where the synchronization instance is located.
DMS console
Note
The actual steps may vary depending on the mode and layout of the DMS console. For more information, see Simple mode console and Customize the layout and style of the DMS console.
1. Log on to the DMS console.
2. In the top menu bar, choose Data + AI > DTS (DTS) > Data Synchronization.
3. To the right of Data Synchronization Tasks, select the region of the synchronization instance.
Click Create Task to open the task configuration page.

Configure the source and destination databases.

Warning

After you select the source and destination instances, review the Limits at the top of the page. Otherwise, the task may fail or data inconsistency may occur.

Category	Parameter	Description
N/A	Task Name	DTS automatically generates a task name. We recommend that you specify a descriptive name for easy identification. The name does not need to be unique.
Source Database	Select Existing Connection	Select the registered database instance with DTS from the drop-down list. The database information below is automatically configured. Note In the DMS console, this configuration item is Select a DMS database instance. If you have not registered the database instance or do not need to use a registered instance, manually configure the database information below.
	Database Type	Select PolarDB-X 2.0.
	Connection Type	Select Alibaba Cloud Instance.
	Instance Region	Select the region where the source PolarDB-X 2.0 instance is located.
	Replicate Data Across Alibaba Cloud Accounts	For this example, data is synchronized within the same Alibaba Cloud account. Select No.
	Instance ID	Select the ID of the source PolarDB-X 2.0 instance.
	Database Account	Enter the database account for the source PolarDB-X 2.0 instance. The account must have the REPLICATION SLAVE, REPLICATION CLIENT, and SELECT permissions on the objects to be synchronized. Note For more information about how to grant permissions, see Account permission issues during data synchronization.
	Database Password	Enter the password for the specified database account.
Destination Database	Select Existing Connection	Select the registered database instance with DTS from the drop-down list. The database information below is automatically configured. Note In the DMS console, this configuration item is Select a DMS database instance. If you have not registered the database instance or do not need to use a registered instance, manually configure the database information below.
	Database Type	Select Kafka.
	Connection Type	Select Express Connect, VPN Gateway, or Smart Access Gateway. Note In this scenario, the synchronization task treats your Message Queue for Apache Kafka instance as a self-managed Kafka cluster.
	Instance Region	Select the region where the destination Kafka instance is located.
	Connected VPC	Select the ID of the Virtual Private Cloud (VPC) where the destination Kafka instance is located. You can find the VPC ID on the Basic Information page of the Kafka instance.
	Domain Name or IP	Enter any IP address from the Default Endpoint of the Kafka instance. Note You can obtain the IP address from the Default Endpoint on the Basic Information page of the Kafka instance.
	Port	The service port for the Kafka instance. Default: 9092.
	Database Account	Enter the database account for the destination Kafka instance. Note If the Kafka instance is a VPC Instance, you do not need to configure Database Account and Database Password.
	Database Password	Enter the password for the specified database account.
	Kafka Version	Select the version that corresponds to your Kafka instance.
	Connection method	Select Non-encrypted or SCRAM-SHA-256 based on your business and security requirements.
	Topic	From the drop-down list, select the topic to receive the data.
	Use Kafka Schema Registry	Kafka Schema Registry is a serving layer for your metadata. It provides a RESTful interface for storing and retrieving Avro schemas. No: Do not use Kafka Schema Registry. Yes: Use Kafka Schema Registry. You must enter the URL or IP address for the Kafka Schema Registry.

After completing the configuration, click Test Connectivity and Proceed at the bottom of the page.
Note
- Ensure that you add the CIDR blocks of the DTS servers (either automatically or manually) to the security settings of both the source and destination databases to allow access. For more information, see Add the IP address whitelist of DTS servers.
- If the source or destination is a self-managed database (i.e., the Access Method is not Alibaba Cloud Instance), you must also click Test Connectivity in the CIDR Blocks of DTS Servers dialog box.

Configure the task objects.

On the Configure Objects page, specify the objects to synchronize.

Parameter	Description
Synchronization Type	DTS always selects Incremental Data Synchronization. By default, you must also select Schema Synchronization and Full Data Synchronization. After the precheck, DTS initializes the destination cluster with the full data of the selected source objects, which serves as the baseline for subsequent incremental synchronization.
Processing Mode for Existing Destination Tables	Precheck and Report Errors: Checks for tables with the same names in the destination database. If any tables with the same names are found, an error is reported during the precheck and the data synchronization task does not start. Otherwise, the precheck is successful. Note If you cannot delete or rename the table with the same name in the destination database, you can map it to a different name in the destination. For more information, see Database Table Column Name Mapping. Ignore Errors and Proceed: Skips the check for tables with the same name in the destination database. Warning Selecting Ignore Errors and Proceed may cause data inconsistency and put your business at risk. For example: If the table schemas are consistent and a record in the destination database has the same primary key or unique key value as a record in the source database: During full data synchronization, DTS retains the destination record and skips the source record. During incremental synchronization, DTS overwrites the destination record with the source record. If the table schemas are inconsistent, data initialization may fail. This can result in only partial data synchronization or a complete synchronization failure. Use with caution.
Data Format in Kafka	Select the storage format for the data synchronized to the Kafka instance based on your requirements. If you select DTS Avro, you must parse the data according to the DTS Avro schema definition. For details, see DTS Avro schema definition and DTS Avro deserialization example. If you select Canal JSON, see Canal JSON format for parameter descriptions and examples.
Kafka Data Compression Format	Select the compression format for Kafka messages based on your requirements. LZ4 (Default): Lower compression ratio and higher compression speed. GZIP: Higher compression ratio and lower compression speed. Note This option is CPU-intensive. Snappy: Medium compression ratio and medium compression speed.
Policy for Shipping Data to Kafka Partitions	Select a strategy based on your business requirements. For more information, see Kafka partition routing strategy. Important This feature is not supported if the source database is a PolarDB-X 1.0 instance.
Message acknowledgement mechanism	Select a message acknowledgment mechanism based on your business requirements.
Topic That Stores DDL Information	From the drop-down list, select the topic to store DDL statements. Note If you do not select a topic, DDL statements are stored in the topic selected for receiving data by default.
Case Policy for Destination Object Names	Configure the case-sensitivity policy for database, table, and column names in the destination instance. By default, the DTS default policy is selected. You can also choose to use the default policy of the source or destination database. For more information, see Case policy for destination object names.
Source Objects	In the Source Objects box, click the objects, and then click to move them to the Selected Objects box. Note You can select objects at the database, table, or column level. If you select only tables or columns, DTS does not synchronize other object types (such as views, triggers, and stored procedures).
Selected Objects	No additional configuration is required for this example. You can use the mapping feature to set the topic name, number of topic partitions, and partition key for the source table in the destination Kafka instance. For more information, see Mapping information. Note If you use the object name mapping feature, other objects that depend on the mapped object may fail to synchronize. To select the SQL operations for incremental synchronization, right-click the desired object in the Selected Objects pane and select the SQL operations in the dialog box that appears.

Click Next: Advanced Settings.

Parameter	Description
Dedicated Cluster for Task Scheduling	By default, DTS uses a shared cluster for tasks, so you do not need to make a selection. For greater task stability, you can purchase a dedicated cluster to run the DTS synchronization task. For more information, see What is a DTS dedicated cluster?.
Retry Time for Failed Connections	If the connection to the source or destination database fails after the synchronization task starts, DTS reports an error and immediately begins to retry the connection. The default retry duration is 720 minutes. You can customize the retry time to a value from 10 to 1,440 minutes. We recommend a duration of 30 minutes or more. If the connection is restored within this period, the task resumes automatically. Otherwise, the task fails. Note If multiple DTS instances (e.g., Instance A and B) share a source or destination, DTS uses the shortest configured retry duration (e.g., 30 minutes for A, 60 for B, so 30 minutes is used) for all instances. DTS charges for task runtime during connection retries. Set a custom duration based on your business needs, or release the DTS instance promptly after you release the source/destination instances.
Retry Time for Other Issues	If a non-connection issue (e.g., a DDL or DML execution error) occurs, DTS reports an error and immediately retries the operation. The default retry duration is 10 minutes. You can also customize the retry time to a value from 1 to 1,440 minutes. We recommend a duration of 10 minutes or more. If the related operations succeed within the set retry time, the synchronization task automatically resumes. Otherwise, the task fails. Important The value of Retry Time for Other Issues must be less than that of Retry Time for Failed Connections.
Enable Throttling for Full Data Migration	During full data synchronization, DTS consumes read and write resources from the source and destination databases, which can increase their load. To mitigate pressure on the destination database, you can limit the migration rate by setting Queries per second (QPS) to the source database, RPS of Full Data Migration, and Data migration speed for full migration (MB/s). Note This parameter is available only if Synchronization Types is set to Full Data Synchronization. You can also adjust the rate of full data synchronization when the synchronization instance is running.
Enable Throttling for Incremental Data Synchronization	You can also limit the incremental synchronization rate to reduce pressure on the destination database by setting RPS of Incremental Data Synchronization and Data synchronization speed for incremental synchronization (MB/s).
Whether to delete SQL operations on heartbeat tables of forward and reverse tasks	Choose whether DTS writes heartbeat SQL information to the source database while the instance is running. Yes: Does not write heartbeat SQL information to the source database. The DTS instance may display latency. No: Writes heartbeat SQL information to the source database. This may interfere with source database operations like physical backups and cloning.
Environment Tag	You can select an environment tag to identify the instance based on your needs. No selection is required for this example.
Configure ETL	Choose whether to enable the extract, transform, and load (ETL) feature. For more information, see What is ETL? Valid values: Yes: Enables the ETL feature. Enter data processing statements in the code editor. For more information, see Configure ETL in a data migration or data synchronization task. No: Disables the ETL feature.
Monitoring and Alerting	Choose whether to set up alerts. If the synchronization fails or the latency exceeds the specified threshold, DTS sends a notification to the alert contacts. No: No alerts are configured. Yes: Configures alerts. You must also set the alert threshold and alert contact. For more information, see Configure monitoring and alerting during task configuration.

Save the task and perform a precheck.
- To view the parameters for configuring this instance via an API operation, hover over the Next: Save Task Settings and Precheck button and click Preview OpenAPI parameters in the tooltip.
- If you have finished viewing the API parameters, click Next: Save Task Settings and Precheck at the bottom of the page.
Note
- Before a synchronization task starts, DTS performs a precheck. You can start the task only if the precheck passes.
- If the precheck fails, click View Details next to the failed item, fix the issue as prompted, and then rerun the precheck.
- If the precheck generates warnings:
  For non-ignorable warning, click View Details next to the item, fix the issue as prompted, and run the precheck again.
  For ignorable warnings, you can bypass them by clicking Confirm Alert Details, then Ignore, and then OK. Finally, click Precheck Again to skip the warning and run the precheck again. Ignoring precheck warnings may lead to data inconsistencies and other business risks. Proceed with caution.

Purchase the instance.

When the Success Rate reaches 100%, click Next: Purchase Instance.

On the Purchase page, select the link specification for the data migration instance. For more information, see the following table.

Category	Parameter	Description
New Instance Class	Resource Group Settings	Select the resource group to which the instance belongs. The default value is default resource group. For more information, see What is Resource Management?
New Instance Class	Instance Class	DTS provides migration specifications with different performance levels. The link specification affects the migration speed. You can select a specification based on your business scenario. For more information, see Data migration link specifications.

After the configuration is complete, read and select Data Transmission Service (Pay-as-you-go) Service Terms.
Click Buy and Start. In the OK dialog box that appears, click OK.

You can view the progress of the migration task on the Data Migration Tasks list page.
Note
- If the migration task does not include incremental migration, it stops automatically after the full migration is complete. After the task stops, its Status changes to Completed.
- If the migration task includes incremental migration, it does not stop automatically. The incremental migration task continues to run. While the incremental migration task is running, the Status of the task is Running.

Mapping information

In the Selected Objects area, hover over the destination topic name.
Click Edit next to the destination topic name.

In the Edit Table dialog box, configure the mapping information.

Note

The dialog box is named Edit Schema at the database level and Edit Table at the table level. The Edit Schema dialog box supports fewer parameters.
If you are not synchronizing an entire database, you cannot modify the Name of target Topic and Number of Partitions parameters in the Edit Schema dialog box.

Parameter	Description
Name of target Topic	The name of the destination topic that receives data from the source table. By default, this is the Topic selected in the Destination Database section of the Configurations for Source and Destination Databases step. Important If the destination database is a Message Queue for Apache Kafka instance, the topic name you enter must already exist in the destination Kafka instance. Otherwise, the data synchronization will fail. If the destination database is a self-managed Kafka database and the synchronization task includes database and table structure, Data Transmission Service (DTS) attempts to create the specified topic in the destination database. If you modify the Name of target Topic, the system writes data to the newly specified topic.
Filter Conditions	For details, see Set filter conditions.
Number of Partitions	The number of partitions for the destination topic.
Partition Key	You can configure this parameter when Policy for Shipping Data to Kafka Partitions is set to Ship Data to Separate Partitions Based on Hash Values of Primary Keys. You can specify one or more columns as the partition key. Data Transmission Service (DTS) calculates a hash value based on the specified key and uses this value to distribute rows across the partitions of the destination topic. Note You can configure the Partition Key only in the Edit Table dialog box.

Click OK.

FAQ

Can I change the Kafka Data Compression Format or Message acknowledgement mechanism after the task is created?

Yes. Modify these settings through the object modification feature. See Modify the objects to be synchronized.