Synchronize data from an ApsaraDB RDS for MySQL instance to a MaxCompute project

Precautions

• DTS uses read and write resources of the source and destination databases during initial full data synchronization. This may increase the loads of the database servers. If the database performance is unfavorable, the specification is low, or the data volume is large, database services may become unavailable. For example, DTS occupies a large amount of read and write resources in the following cases: a large number of slow SQL queries are performed on the source database, the tables have no primary keys, or a deadlock occurs in the destination database. Before you synchronize data, evaluate the impact of data synchronization on the performance of the source and destination databases. We recommend that you synchronize data during off-peak hours. For example, you can synchronize data when the CPU utilization of the source and destination databases is less than 30%.
• You can select only tables as the objects to be synchronized.
• We recommend that you do not use gh-ost or pt-online-schema-change to perform data definition language (DDL) operations on objects during data synchronization. Otherwise, data synchronization may fail.
• MaxCompute does not support the PRIMARY KEY constraint. If network errors occur, DTS may synchronize duplicate data records to MaxCompute.

Supported source database types

You can use DTS to synchronize data from the following types of MySQL databases:

• User-created database that is hosted on ECS
• User-created database that is connected over Express Connect, VPN Gateway, or Smart Access Gateway
• User-created database that is connected over Database Gateway
• ApsaraDB RDS for MySQL instance that is owned by the same Alibaba Cloud account as the MaxCompute project or a different Alibaba Cloud account from the MaxCompute project

SQL operations that can be synchronized

• DDL operation: ADD COLUMN
  Note Only the following data types are supported: INTEGER, BIGINTEGER, IGINT, LONGSTRING, YEAR, TIME, DATA, TIME STAMP, DATA TIME BYTE BOOLEAN DECIMAL, DOUBLE, and FLOAT.
• Data manipulation language (DML) operations: INSERT, UPDATE, and DELETE

Synchronization process

1. Initial schema synchronization
   DTS synchronizes the schemas of the required objects from the source database to MaxCompute. During initial schema synchronization, DTS adds the _base suffix to the end of the source table name. For example, if the name of the source table is customer, the name of the table in MaxCompute is customer_base.
2. Initial full data synchronization
   DTS synchronizes the historical data of the table from the source database to the destination table in MaxCompute. For example, the customer table in the source database is synchronized to the customer_base table in MaxCompute. The data is the basis for subsequent incremental synchronization.

   Note The destination table that is suffixed with _base is known as a full baseline table.
3. Incremental data synchronization.
   DTS creates an incremental data table in MaxCompute. The name of the incremental data table is suffixed with _log, for example, customer_log. Then, DTS synchronizes the incremental data that was generated in the source database to the incremental data table.

   Note For more information, see Schema of an incremental data table.

Procedure

1. Purchase a data synchronization instance. For more information, see Purchase a DTS instance.
   Note On the buy page, set Source Instance to MySQL, set Target Instance to MaxCompute, and set Synchronization Topology to One-Way Synchronization.
2. Log on to the DTS console.
3. In the left-side navigation pane, click Data Synchronization.
4. At the top of the Synchronization Tasks page, select the region where the destination instance resides.
   
5. Find the data synchronization instance and click Configure Synchronization Channel in the Actions column.
6. 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	Select RDS Instance.
   	Instance Region	The source region that you selected on the buy page. You cannot change the value of this parameter.
   	Instance ID	Select the ID of the source RDS instance.
   	Database Account	Enter the database account of the source RDS instance. Note If the database engine of the source RDS instance is MySQL 5.5 or MySQL 5.6, you do not need to configure the database account or database password.
   	Database Password	Enter the password of the source database account.
   	Encryption	Select Non-encrypted or SSL-encrypted. If you want to select SSL-encrypted, you must enable SSL encryption for the RDS instance before you configure the data synchronization task. For more information, see Configure SSL encryption on an ApsaraDB RDS for MySQL instance. Notice The Encryption parameter is available only for regions in mainland China and the China (Hong Kong) region.
   Destination Instance Details	Instance Type	This parameter is set to MaxCompute and cannot be changed.
   	Instance Region	The destination region that you selected on the buy page. You cannot change the value of this parameter.
   	Project	Enter the name of the MaxCompute project. You can search for a project on the Workspaces page in the DataWorks console.

7. In the lower-right corner of the page, click Set Whitelist and Next.
   Note DTS adds the CIDR blocks of DTS servers to the whitelists of the RDS instance and the MaxCompute project. This ensures that DTS servers can connect to the source and destination instances.
8. In the lower-right corner of the page, click Next. In this step, the permissions on the MaxCompute project are granted to the synchronization account.
   
9. Select the synchronization policy and the objects to be synchronized.
   

   Parameter	Description
   Partition Definition of Incremental Data Table	Select the partition name based on your business requirements. For more information about partitions, see Partition.
   Initial Synchronization	Initial synchronization includes initial schema synchronization and initial full data synchronization. Select both Initial Schema Synchronization and Initial Full Data Synchronization. In this case, DTS synchronizes the schemas and historical data of the required objects and then synchronizes incremental data.
   Select the processing mode of conflicting tables	Pre-check and Intercept: 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 precheck and the data synchronization task cannot be started. Note You can use the object name mapping feature to change the names of 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 Specify the name of an object in the destination instance. Ignore: skips the precheck for identical table names in the source and destination databases. Warning If you select Ignore, data consistency is not guaranteed and your business may be exposed to potential risks. During initial data synchronization, DTS does not synchronize the data records that have the same primary keys as the data records in the destination database. This occurs if the source and destination databases have the same schema. However, DTS synchronizes these data records during incremental data synchronization. If the source and destination databases have different schemas, initial data synchronization may fail. In this case, only some columns are synchronized or the data synchronization task fails.
   Select the 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 tables from multiple databases as the objects to be synchronized. After an object is synchronized to the destination instance, the name of the object remains unchanged. You can use the object name mapping feature to change the names of the objects that are synchronized to the destination database. For more information, see Specify the name of an object in the destination instance.

10. 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.
11. Close the Precheck dialog box after the following message is displayed: The precheck is passed.
12. 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.

Schema of an incremental data table

DTS synchronizes incremental data that is generated in the source MySQL database to the incremental data table in MaxCompute. The incremental data table stores incremental data and specific metadata. The following figure shows the schema of an incremental data table.

Schema of an incremental data table

Additional information about the before_flag and after_flag fields

The before_flag and after_flag fields of an incremental log entry are defined depending on the operation type.

• INSERT

  For an INSERT operation, the column values are the newly inserted record values (post-update values). The value of the before_flag field is N and the value of the after_flag field is Y.

  
• UPDATE

  DTS generates two incremental log entries for an UPDATE operation. The two incremental log entries have the same values for the record_id, operation_flag, and utc_timestamp fields.

  The first log entry records the pre-update values, so the value of the before_flag field is Y and the value of the after_flag field is N. The second log entry records the post-update values, so the value of the before_flag field is N and the value of the after_flag field is Y.

  
• DELETE

  For a DELETE operation, the column values are the deleted record values (pre-update values). The value of the before_flag field is Y and the value of the after_flag field is N.

  

Merge a full baseline table and an incremental data table

After a data synchronization task is started, DTS creates a full baseline table and an incremental data table in MaxCompute. You can use SQL statements to merge the two tables. This allows you to obtain the full data at a specific time point.

This section describes how to merge data for a table named customer. The following figure shows the schema of the customer table.

1. Create a table in MaxCompute based on the schema of the source table. The table is used to store the merged data.

   For example, you can obtain full data of the customer table at the 1565944878 time point. Run the following SQL statements to create the required table:

   CREATE TABLE `customer_1565944878` (
       `id` bigint NULL,
       `register_time` datetime NULL,
       `address` string);

   Note

   • You can use the ad-hoc query feature to run SQL statements. For more information, see (Optional) Use an ad-hoc query to run SQL statements.
   • For more information about the data types that are supported by MaxCompute, see Data types.
2. Run the following SQL statements in MaxCompute to merge the full baseline table and the incremental data table and obtain full data at a specific time point:

   set odps.sql.allow.fullscan=true;
   insert overwrite table <result_storage_table>
   select <col1>,
          <col2>,
          <colN>
     from(
   select row_number() over(partition by t.<primary_key_column>
    order by record_id desc, after_flag desc) as row_number, record_id, operation_flag, after_flag, <col1>, <col2>, <colN>
     from(
   select incr.record_id, incr.operation_flag, incr.after_flag, incr.<col1>, incr.<col2>,incr.<colN>
     from <table_log> incr
    where utc_timestamp< <timestamp>
    union all
   select 0 as record_id, 'I' as operation_flag, 'Y' as after_flag, base.<col1>, base.<col2>,base.<colN>
     from <table_base> base) t) gt
   where record_num=1 
     and after_flag='Y'

   Note

   • <result_storage_table>: the name of the table that stores the merged data.
   • <col1>/<col2>/<colN>: the names of the columns in the table to be merged.
   • <primary_key_column>: the name of the primary key column in the table to be merged.
   • <table_log>: the name of the incremental data table.
   • <table_base>: the name of the full baseline table.
   • <timestamp>: the timestamp that is generated when full data is obtained.

   Run the following SQL statements to obtain full data of the customer table at the 1565944878 time point:

   set odps.sql.allow.fullscan=true;
   insert overwrite table customer_1565944878
   select id,
          register_time,
          address
     from(
   select row_number() over(partition by t.id
    order by record_id desc, after_flag desc) as row_number, record_id, operation_flag, after_flag, id, register_time, address
     from(
   select incr.record_id, incr.operation_flag, incr.after_flag, incr.id, incr.register_time, incr.address
     from customer_log incr
    where utc_timestamp< 1565944878
    union all
   select 0 as record_id, 'I' as operation_flag, 'Y' as after_flag, base.id, base.register_time, base.address
     from customer_base base) t) gt
    where gt.row_number= 1
      and gt.after_flag= 'Y';

3. Query the merged data from the customer_1565944878 table.