This topic describes how to migrate data from a PolarDB for MySQL cluster to an AnalyticDB for MySQL V3.0 cluster by using Data Transmission Service (DTS). After you migrate data, you can use AnalyticDB for MySQL to build internal business intelligence (BI) systems, interactive query systems, and real-time report systems.

Prerequisites

  • An ApsaraDB RDS for MySQL instance is created. For more information, see Create an ApsaraDB RDS for MySQL instance.
  • The destination AnalyticDB for MySQL V3.0 cluster is created. For more information, see Create a cluster.
  • The available storage space of the destination AnalyticDB for MySQL cluster is larger than the total size of the data in the source PolarDB for MySQL cluster.

Limits

Category Description
Limits on the source database
  • The server to which the source database belongs must have sufficient outbound bandwidth. Otherwise, the data migration speed decreases.
  • The tables to be migrated must have PRIMARY KEY or UNIQUE constraints and all fields must be unique. Otherwise, the destination database may contain duplicate data records.
  • If you select tables as the objects to be migrated and you need to edit the tables, such as renaming tables or columns, in the destination database, you can migrate up to 1,000 tables in a single data migration task. If you run a task to migrate more than 1,000 tables, a request error occurs. In this case, we recommend that you configure multiple tasks to synchronize the tables in batches or configure a task to synchronize the entire database.
  • If you want to migrate incremental data, make sure that the following requirements are met:
    • The binary logging feature must be enabled. The value of the loose_polar_log_bin parameter must be set to on. Otherwise, error messages are returned during precheck and the data migration task cannot be started.
    • For an incremental data migration task, the binary logs of the source database are retained for at least 24 hours. For a full data and incremental data migration task, the binary logs of the source database are retained for at least seven days. Otherwise, Data Transmission Service (DTS) may fail to obtain the binary logs and the task may fail. In exceptional circumstances, data inconsistency or loss may occur. After full data migration is complete, you can set the retention period to more than 24 hours. Make sure that you set the retention period of binary logs based on the preceding requirements. Otherwise, the Service Level Agreement (SLA) of DTS does not ensure service reliability and performance.

  • Limits on operations that are performed on the source database:
    • During schema migration and full data migration, do not perform DDL operations to change the schemas of databases or tables. Otherwise, the data migration task fails.
    • During data migration, do not perform DDL operations to add comments. Otherwise, the data migration task fails. For example, do not execute the ALTER TABLE table_name COMMENT='Table comment'; statement.
    • If you perform only full data migration, do not write data to the source database during data migration. Otherwise, data inconsistency between the source and destination databases may occur. To ensure data consistency, we recommend that you select schema migration, full data migration, and incremental data migration as the migration types.
Usage notes
  • Prefix indexes cannot be migrated. If the source database contains prefix indexes, data may fail to be migrated.
  • Read-only nodes of the source PolarDB for MySQL cluster cannot be migrated.
  • Due to the limits of AnalyticDB for MySQL, if the disk space usage of the nodes in an AnalyticDB for MySQL cluster reaches 80%, the task is delayed and error messages are returned. We recommend that you estimate the required disk space based on the objects to be migrated. Make sure that the destination cluster has sufficient storage space.
  • Before you migrate data, evaluate the impact of data migration on the performance of the source and destination databases. We recommend that you migrate data during off-peak hours. During full data migration, DTS uses the read and write resources of the source and destination databases. This may increase the loads of the database servers.
  • During full data migration, concurrent INSERT operations cause fragmentation in the tables of the destination database. After full data migration is complete, the size of used tablespace of the destination database is larger than that of the source database.
  • Make sure that the precision settings for columns of the FLOAT or DOUBLE data type meet your business requirements. DTS uses the ROUND(COLUMN,PRECISION) function to retrieve values from columns of the FLOAT or DOUBLE data type. If you do not specify a precision, DTS sets the precision for the FLOAT data type to 38 digits and the precision for the DOUBLE data type to 308 digits.
  • DTS attempts to resume data migration tasks that failed within the last seven days. Before you switch workloads to the destination instance, stop or release the data migration task. You can also execute the REVOKE statement to revoke the write permissions from the accounts used by DTS to access the destination instance. Otherwise, the data in the source database will overwrite the data in the destination database after the task is resumed.
  • DTS executes the CREATE DATABASE IF NOT EXISTS `test` statement in the source database as scheduled to move forward the binary log file position.

Billing

Migration type Task configuration fee Internet traffic fee
Schema migration and full data migration Free of charge. Charged only when data is migrated from Alibaba Cloud over the Internet. For more information, see Billing overview.
Incremental data migration Charged. For more information, see Billing overview.

Migration types

  • Schema migration

    DTS migrates the schemas of the required objects from the source database to the destination database.

    Note ApsaraDB RDS for MySQL and AnalyticDB for MySQL are heterogeneous databases. DTS does not ensure that the schemas of the source and destination databases are consistent after schema migration. We recommend that you evaluate the impact of data type conversion on your business. For more information, see Data type mappings between heterogeneous databases.
  • Full data migration

    DTS migrates historical data of the required objects from the source database to the destination database.

  • Incremental data migration

    After full data migration is complete, DTS synchronizes incremental data from the source database to the destination database. Incremental data migration allows you to ensure service continuity when you migrate data between self-managed databases.

SQL operations that can be migrated

Operation type SQL statements
DML INSERT, UPDATE, and DELETE
DDL CREATE TABLE, DROP TABLE, RENAME TABLE, TRUNCATE TABLE, ADD COLUMN, and DROP COLUMN
Warning If the data type of a field in the source table is changed during data migration, an error message is generated and the data migration task is stopped. You can submit a ticket or perform the following steps to troubleshoot the issue.
  1. When DTS migrates data to the destination AnalyticDB for MySQL cluster, the data type of a field named customer in the source table is changed. As a result, the data migration task fails.
  2. In the destination AnalyticDB for MySQL V3.0 cluster, create a table named customer_new. The customer_new table has the same schema as the customer table.
  3. Run the INSERT INTO SELECT command to copy the data of the customer table and insert the data into the customer_new table. This ensures that the data of the two tables is consistent.
  4. Rename or delete the customer table. Then, change the name of the customer_new table to customer.
  5. Restart the data migration task in the DTS console.

Permissions required for database accounts

Database Required permissions
PolarDB for MySQL The read permissions on the objects to be migrated
AnalyticDB for MySQL V3.0 The read and write permissions
For more information about how to create and authorize a database account, see the following topics:

Procedure

  1. Go to the Data Synchronization page of the new DTS console.
    Note You can also log on to the Data Management console. In the top navigation bar, click DTS. Then, in the left-side navigation pane, choose DTS (DTS) > Data Synchronization.
  2. In the top navigation bar, select the region where the data synchronization instance resides.
    Region
  3. Click Create Task. On the page that appears, configure the source and destination databases.
    Warning After you select the source and destination instances, we recommend that you read the limits displayed at the top of the page. This helps you create and run the data synchronization task.
    Section Parameter Description
    N/A Task Name

    DTS automatically generates a task name. We recommend that you specify an informative name to identify the task. You do not need to use a unique task name.

    Source Database Database Type Select PolarDB for MySQL.
    Access Method Select Alibaba Cloud Instance.
    Instance Region Select the region where the source PolarDB for MySQL cluster resides.
    Replicate Data Across Alibaba Cloud Accounts

    In this example, select No because data is synchronized within the same Alibaba Cloud account.

    In this example, select Yes because data is synchronized across different Alibaba Cloud accounts. Before you set this parameter, you must make preparations for the task. For more information, see Synchronize or migrate data across Alibaba Cloud accounts.

    PolarDB Cluster ID Select the ID of the source PolarDB for MySQL cluster.
    Database Account Enter the database account of the source PolarDB for MySQL cluster. The account must have the read permissions on the objects to be synchronized.
    Database Password

    Enter the password of the database account.

    Destination Database Database Type Select AnalyticDB for MySQL 3.0.
    Access Method Select Alibaba Cloud Instance.
    Instance Region Select the region in which the destination AnalyticDB for MySQL V3.0 cluster resides.
    Instance ID Select the ID of the destination AnalyticDB for MySQL V3.0 cluster.
    Database Account Enter the database account of the destination AnalyticDB for MySQL V3.0 cluster. The account must have the read and write permissions on the destination database.
    Database Password

    Enter the password of the database account.

  4. In the lower part of the page, click Test Connectivity and Proceed.
    Note
    • You do not need to modify the security settings for ApsaraDB instances (such as ApsaraDB RDS for MySQL and ApsaraDB for MongoDB) and ECS-hosted databases. DTS automatically adds the CIDR blocks of DTS servers to the whitelists of ApsaraDB instances or the security group rules of Elastic Compute Service (ECS) instances. For more information, see Add the CIDR blocks of DTS servers to the security settings of on-premises databases.
    • After data synchronization is completed, we recommend that you remove the CIDR blocks of DTS servers from the whitelists or security groups.
  5. Select objects for the task and configure advanced settings.
    • Basic SettingsBasic Settings
      Parameter Description
      Task Stages

      Incremental Data Synchronization is selected by default. You must also select Schema Synchronization and Full Data Synchronization. After the precheck, DTS synchronizes the historical data of the selected objects from the source instance to the destination cluster. The historical data is the basis for subsequent incremental synchronization.

      Processing Mode of Conflicting Tables
      • Precheck and Report Errors: checks whether the destination database contains tables that have the same names as tables in the source database. If the source and destination databases do not contain identical table names, the precheck is passed. Otherwise, an error is returned during the precheck and the data synchronization task cannot be started.

        Note You can use the object name mapping feature to rename the tables that are synchronized to the destination database. You can use this feature if the source and destination databases contain identical table names and the tables in the destination database cannot be deleted or renamed. For more information, see Map object names.
      • Ignore Errors and Proceed: skips the precheck for identical table names in the source and destination databases.
        Warning If you select Ignore Errors and Proceed, data consistency is not guaranteed and your business may be exposed to potential risks.
        • If the source and destination databases have the same schema, and a data record has the same primary key as an existing data record in the destination database:
          • During full data synchronization, DTS does not synchronize the data record to the destination database. The existing data record in the destination database is retained.
          • During incremental data synchronization, DTS synchronizes the data record to the destination database. The existing data record in the destination database is overwritten.
        • If the source and destination databases have different schemas, data may fail to be initialized. In this case, only some columns are synchronized or the data synchronization task fails.
      DDL and DML Operations to Be Synchronized

      Select the DDL and DML operations that you want to synchronize. For more information, see SQL operations that can be migrated.

      Note To select the SQL operations performed on a specific database or table, perform the following steps: In the Selected Objects section, right-click an object. In the dialog box that appears, select the SQL operations that you want to synchronize.
      Merge Tables
      • Yes: In online transaction processing (OLTP) scenarios, sharding is implemented to speed up the response to business tables. In online analytical processing (OLAP) scenarios, you can store a large volume of data in a single table. This makes your SQL queries more efficient. You can merge multiple source tables that have the same schema into a single destination table. This feature allows you to synchronize data from multiple tables in the source database to a single table in the destination database.
        Note
        • After you select multiple tables from the source database, you must change the names of these tables to the name of the destination table. To do this, you can use the object name mapping feature. For more information, see Map object names.
        • DTS adds a column named __dts_data_source to the destination table. This column is used to record the data source. The data type of this column is TEXT. DTS specifies the column values based on the following format: <DTS instance ID>:<Database name>:<Schema name>:<Table name>. Such column values allow DTS to identify each source table. For example, dts********:dtstestdata:testschema:customer1 indicates that the source table is customer1.
        • If you set this parameter to Yes, all the selected source tables in the task are merged into the destination table. If you do not need to merge specific source tables, you can create a separate data synchronization task for these tables.
        Warning We recommend that you do not perform DDL operations to change the schemas of source databases or tables. Otherwise, data inconsistency may occur or the data synchronization task fails.
      • No is selected by default.
      Select Objects

      Select one or more objects from the Source Objects section and click the Rightwards arrow icon to add the objects to the Selected Objects section.

      Note You can select columns, tables, or databases as the objects to be synchronized. If you select tables or columns as the objects to be synchronized, DTS does not synchronize other objects such as views, triggers, and stored procedures to the destination database.
      Rename Databases and Tables
      • To rename an object that you want to synchronize to the destination instance, right-click the object in the Selected Objects section. For more information, see Map the name of a single object.
      • To rename multiple objects at a time, click Batch Edit in the upper-right corner of the Selected Objects section. For more information, see Map multiple object names at a time.
      Filter data

      You can specify WHERE conditions to filter data. For more information, see Use SQL conditions to filter data.

      Select the SQL operations to be synchronized In the Selected Objects section, right-click an object. In the dialog box that appears, select the SQL operations that you want to synchronize. For more information, see SQL operations that can be migrated.
    • Advanced SettingsAdvanced Settings
      Parameter Description
      Set Alerts
      Specify whether to set alerts for the data synchronization task. If the task fails or the synchronization latency exceeds the threshold, the alert contacts will receive notifications.
      • Select No if you do not want to set alerts.
      • Select Yes to set alerts. In this case, you must also set the alert threshold and alert contacts.
      Capitalization of Object Names in Destination Instance

      Specify the capitalization of database names, table names, and column names in the destination instance. By default, DTS default policy is selected. You can select other options to make sure that the capitalization of object names is consistent with that of the source or destination database. For more information,see Specify the capitalization of object names in the destination instance.

      Replicate Temporary Tables When DMS Performs DDL Operations
      In this scenario, DTS does not synchronize DDL operations. You must set this parameter to No. However, DTS may support DDL operations for this scenario in the future. In this case, if you use Data Management (DMS) to perform online DDL operations on the source database, you can specify whether to synchronize temporary tables generated by the operations.
      • Yes: DTS synchronizes the data of temporary tables generated by online DDL operations.
        Note If online DDL operations generate a large amount of data, the data synchronization task may be delayed.
      • No: DTS does not synchronize the data of temporary tables generated by online DDL operations. Only the original DDL data of the source database is synchronized.
        Note If you select No, the tables in the destination database may be locked.
      Retry Time for Failed Connection
      Specify the retry time range for failed connections. If a data synchronization task is disconnected, DTS immediately retries a connection within the specified time range. Valid values: 10 to 1440. Unit: minutes. Default value: 120. We recommend that you set the retry time range to more than 30 minutes. If DTS reconnects to the source and destination databases within the specified time range, DTS resumes the data synchronization task. Otherwise, the data synchronization task fails.
      Note
      • If multiple DTS instances have the same source or destination database, the lowest value of this parameter takes effect. For example, the retry time range is set to 30 minutes for Instance A and 60 minutes for Instance B, DTS retries failed connections within 30 minutes.
      • When DTS retries a connection, you are charged for the DTS instance. We recommend that you specify the retry time range based on your business requirements. You can also release the DTS instance at your earliest opportunity after the source and destination instances are released.
  6. In the lower part of the page, click Next: Configure Database and Table Fields. On the page that appears, set the primary key columns and distribution key columns of the tables that you want to synchronize to the destination AnalyticDB for MySQL cluster.
    Note If you select Schema Synchronization as the synchronization type, you must specify the Type, Primary Key Column, and Distribution Key parameters for the tables that you want to synchronize to the AnalyticDB for MySQL V3.0 cluster. For more information, see CREATE TABLE.
  7. In the lower part of the page, click Next: Save Task Settings and Precheck.
    Note
    • Before you can start the data synchronization task, DTS performs a precheck. You can start the data synchronization task only after the task passes the precheck.
    • If the task fails to pass the precheck, you can click the Info icon icon next to each failed item to view details.
      • You can troubleshoot the issues based on the causes and run a precheck again.
      • If you do not need to troubleshoot the issues, you can ignore failed items and run a precheck again.
  8. Wait until the Success Rate becomes 100%. Then, click Next: Purchase Instance.
  9. On the Purchase Instance page, specify the Billing Method and Instance Class parameters for the data synchronization instance. The following table describes the parameters.
    Section Parameter Description
    Parameters Billing Method
    • Subscription: You pay for your subscription when you create an instance. We recommend that you select the subscription billing method for long-term use because it is more cost-effective than the pay-as-you-go billing method. You can save more costs with longer subscription periods.
    • Pay-as-you-go: A pay-as-you-go instance is billed on an hourly basis. We recommend that you select the pay-as-you-go billing method for short-term use. If you no longer require a pay-as-you-go instance, you can release the instance to reduce costs.
    Instance Class DTS provides several instance classes that have different performance in synchronization speed. You can select an instance class based on your business scenario. For more information, see Specifications of data synchronization instances.
    Subscription Length If you select the subscription billing method, set the subscription length and the number of instances that you want to create. The subscription length can be one to nine months or one to three years.
    Note This parameter is available only if you select the subscription billing method.
  10. Read and select Data Transmission Service (Pay-as-you-go) Service Terms.
  11. Click Buy and Start to start the data synchronization task. You can view the progress of the task in the task list.