Data Transmission Service:Synchronize data from a Db2 for LUW database to a PolarDB for MySQL cluster

Source database requirements

• The server hosting the source database must have enough outbound bandwidth. Insufficient bandwidth reduces synchronization speed.

• Tables to be synchronized must have PRIMARY KEY or UNIQUE constraints with all fields unique. Without these constraints, the destination database may contain duplicate records.

• When synchronizing individual tables with column or table renaming on the destination side, a single task supports up to 5,000 tables. If your selection exceeds 5,000 tables, split the work across multiple tasks, or synchronize at the database level instead.

• Log archiving must be enabled on the source database. If it is not enabled, the precheck fails and the task cannot start.

Log retention requirements by synchronization type:

Logs retained for shorter periods than required invalidate the DTS service level agreement (SLA).

CDC-specific limitations

These limitations apply only when incremental data synchronization is enabled.

• DTS uses Db2 for LUW's CDC replication technology. For constraints inherent to that technology, see General data restrictions for SQL Replication.

• MySQL column names are case-insensitive. If the source has multiple columns whose names differ only in capitalization, they are written to the same column in the destination, causing unexpected results.

• The source Db2 for LUW database is a self-managed database. A primary/secondary switchover on the source database while a task is running causes the task to fail.

• DTS calculates synchronization latency using the timestamp of the latest record in the destination against the current timestamp in the source. With no DML activity on the source for an extended period, the reported latency may be inaccurate. Perform a DML operation on the source to refresh the latency value. If you synchronize an entire database, you can create a heartbeat table that receives a write every second to keep latency accurate.

General synchronization behavior

• Run the synchronization task during off-peak hours. Initial full data synchronization consumes read and write resources on both the source and destination databases.

• After initial full data synchronization, the destination tablespace may be larger than the source due to table fragmentation from concurrent INSERT operations.

• During synchronization, write data to the destination exclusively through DTS to prevent data inconsistency. After synchronization completes, use Data Management (DMS) to run DDL statements online. See Perform lock-free DDL operations.

• If a DDL statement fails on the destination, the task continues running. View failed DDL statements in the task logs. See View task logs.

• After the task Status changes to Completed, run analyze table <table_name> to confirm data was written to disk in the destination table. In a high-availability (HA) switchover scenario, data may exist only in memory and can be lost.

Schema synchronization behavior

• DTS synchronizes foreign keys from the source to the destination during schema synchronization.

• During full and incremental data synchronization, DTS temporarily disables foreign key constraint checks and cascade operations at the session level. Cascade update or delete operations on the source during this period may cause data inconsistency.

Step 1: Go to the Data Synchronization Tasks page

1. Log on to the Data Management (DMS) console.

2. In the top navigation bar, click Data + AI.

3. In the left-side navigation pane, choose DTS (DTS) > Data Synchronization.

Operations may vary based on the DMS console mode. See Simple mode and Customize the layout and style of the DMS console. You can also go directly to the Data Synchronization Tasks page in the new DTS console.

Step 2: Select the region

On the right side of Data Synchronization Tasks, select the region where the data synchronization instance resides.

In the new DTS console, select the region in the top navigation bar.

Step 3: Configure the source and destination databases

Click Create Task. In the Create Data Synchronization Task wizard, configure the following parameters.

Source Database

Destination Database

Step 4: Test connectivity

Click Test Connectivity and Proceed at the bottom of the page.

DTS handles whitelist configuration automatically based on the database type:

• Alibaba Cloud database instances (such as ApsaraDB RDS or ApsaraDB for MongoDB): DTS adds its CIDR blocks to the instance whitelist automatically.

• Self-managed databases on Elastic Compute Service (ECS): DTS adds its CIDR blocks to the ECS security group rules automatically. Make sure the ECS instance can reach the database.

• Self-managed databases in data centers or third-party clouds: Manually add the DTS CIDR blocks to the database whitelist. See Add the CIDR blocks of DTS servers.

Step 5: Configure synchronization objects and advanced settings

Basic settings

Advanced settings

Step 6: Save settings and run the precheck

To preview the OpenAPI parameters for this task before saving, hover over Next: Save Task Settings and Precheck and click Preview OpenAPI parameters.

Click Next: Save Task Settings and Precheck.

The task cannot start until it passes the precheck. If the precheck fails, click View Details next to each failed item, fix the issues, and click Precheck Again. For alert items that can be safely ignored, click Confirm Alert Details > Ignore > OK > Precheck Again. Ignoring alerts may cause data inconsistency.

Step 7: Purchase a data synchronization instance

Wait until the Success Rate reaches 100%, then click Next: Purchase Instance.

On the purchase page, configure the following parameters.

Step 8: Start the task

Read and select Data Transmission Service (Pay-as-you-go) Service Terms, then click Buy and Start. In the confirmation dialog, click OK.

Track synchronization progress in the task list.