Configuring a Job for Synchronizing Data from MySQL to StarRocks (Internal Beta)

Supported Source and Destination Database Versions

Database Account Permissions

Before you use DataArts Migration for data synchronization, ensure that the source and destination database accounts meet the requirements in the following table. The required account permissions vary depending on the synchronization task type.

GRANT SELECT, SHOW DATABASES, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'Username'@'%';

• You are advised to create independent database accounts for DataArts Migration task connections to prevent task failures caused by password modification.
• After changing the account passwords for the source or destination databases, modify the connection information in Management Center as soon as possible to prevent automatic retries after a task failure. Automatic retries will lock the database accounts.

Supported Synchronization Objects

The following table lists the objects that can be synchronized using different links in DataArts Migration.

Notes

In addition to the constraints on supported data sources and versions, connection account permissions, and synchronization objects, you also need to pay attention to the notes in the following table.

Procedure

This section uses real-time synchronization from RDS for MySQL to StarRocks as an example to describe how to configure a real-time data migration job. Before that, ensure that you have read the instructions described in Check Before Use and completed all the preparations.

1. Create a real-time migration job by following the instructions in Creating a Real-Time Migration Job and go to the job configuration page.
2. Select the data connection type. Select MySQL for Source and StarRocks for Destination.
   Figure 1 Selecting the data connection type

   

3. Select a job type. The default migration type is Real-time. The migration scenario is Entire DB.
   Figure 2 Setting the migration job type
   
   

   For details about synchronization scenarios, see Synchronization Scenarios.

4. Configure network resources. Select the created MySQL and StarRocks data connections and the migration resource group for which the network connection has been configured.
   Figure 3 Selecting data connections and a migration resource group
   
   

   If no data connection is available, click Create to go to the Manage Data Connections page of the Management Center console and click Create Data Connection to create a connection. For details, see Configuring DataArts Studio Data Connection Parameters.

   If no migration resource group is available, click Create to create one. For details, see Buying a DataArts Migration Resource Group Incremental Package.

5. Check the network connectivity. After the data connections and migration resource group are configured, perform the following operations to check the connectivity between the data sources and the migration resource group.
   • Click Source Configuration. The system will test the connectivity of the entire migration job.
   • Click Test in the source and destination and migration resource group.
     

     If the network connectivity is abnormal, see How Do I Troubleshoot a Network Disconnection Between the Data Source and Resource Group?

6. Configure source parameters.
   • Select synchronization objects.
     • Table-level synchronization: Synchronize multiple tables in multiple databases of a MySQL instance.
     • Database-level synchronization: Synchronize all tables in multiple databases of a MySQL instance.
   • Select the MySQL databases and tables to be migrated.
     Figure 4 Selecting databases and tables
     

   Both databases and tables can be customized. You can select one database and one table, or multiple databases and tables.

7. Configure destination parameters.
   • Set Database and Table Matching Policy.
     • Database Matching Policy
       • Same name as the source database: Data will be synchronized to the StarRocks database with the same name as the source MySQL database.
       • Custom: Data will be synchronized to the StarRocks database you specify.
     • Table Matching Policy
       • Same name as the source table: Data will be synchronized to the StarRocks table with the same name as the source MySQL table.
       • Custom: Data will be synchronized to the StarRocks table you specify.
         Figure 5 Database and table matching policy in the entire database migration scenario
         
         

         When you customize a matching policy, you can use built-in variables #{source_db_name} and #{source_table_name} to identify the source database name and table name. The table matching policy must contain #{source_table_name}.

   • Set StarRocks parameters.

     You can configure the advanced parameters in the following table to enable some advanced functions.

     Table 5 StarRocks advanced parameters

     Parameter	Type	Default Value	Unit	Description
     sink.batch.size	-	20,000	Pieces	Maximum number of records written to StarRocks in a batch
     sink.max-retries	-	3	Count	Maximum number of retries upon a data writing failure
     sink.batch.interval	-	1	Second	Interval at which data is written to StarRocks
     sink.enable-delete	-	true	-	Whether to enable deletion
     sink.batch.bytes	-	10	MB	Maximum number of bytes that can be written, written or updated, and deleted

8. Refresh and check the mapping between the source and destination tables. In addition, you can add additional fields and use the automatic table creation capability to create tables in the destination StarRocks database.
   Figure 6 Mapping between source and destination tables
   
   • Edit additional fields: Click Additional Field in the Operation column to add custom fields to the destination StarRocks table. For a new table, you can add additional fields to the existing fields in the source table. You can customize the field name, select the field type, and enter the field value.
     • Field Name: name of the new field in the destination StarRocks table
     • Field Type: type of the new field in the destination StarRocks table
     • Field Value: value source of the new field in the destination StarRocks table

       Table 6 Additional field value obtaining mode

       Type	Example
       Constant	Any character
       Built-in variable	Source host IP address: source.host Source schema name: source.schema Source table name: source.table Destination schema name: target.schema Destination table name: target.table
       Source table field	Any field in the source table Do not change the name of the source table field when the job is running. Otherwise, the job may be abnormal.
       UDF	substring(#col, pos[, len]): obtains a substring of a specified length from the source column name. The substring range is [pos, pos+len). date_format(#col, time_format[, src_tz, dst_tz]): formats the source column name based on a specified time format. The time zone can be converted using src_tz and dst_tz. now([tz]): obtains the current time in a specified time zone. if(cond_exp, str1, str2): returns str1 if the condition expression cond_exp is met and returns str2 otherwise. concat(#col[, #str, ...]): concatenates multiple parameters, including source columns and strings. from_unixtime(#col[, time_format]): formats a Unix timestamp based on a specified time format. unix_timestamp(#col[, precision, time_format]): converts a time into a Unix timestamp of a specified time format and precision.

   • Automatic table creation: Click Auto Table Creation to automatically create tables in the destination database based on the configured mapping policy. After the tables are created, Existing table is displayed for them.
     

     • DataArts Migration supports only automatic table creation. You need to manually create databases and schemas at the destination before using this function.
     • For details about the field type mapping for automatic table creation, see Field Type Mapping.

9. Configure DDL message processing rules.

   Real-time migration jobs can synchronize data manipulation language (DML) operations, such as adding, deleting, and modifying data, as well as some table structure changes using the data definition language (DDL). You can set the processing policy for a DDL operation to Normal processing, Ignore, or Error.

   • Normal processing: When a DDL operation on the source database or table is detected, the operation is automatically synchronized to the destination.
   • Ignore: When a DDL operation on the source database or table is detected, the operation is ignored and not synchronized to the destination.
   • Error: When a DDL operation on the source database or table is detected, the migration job throws an exception.
     Figure 7 DDL configuration
     

10. Configure task parameters.

    Table 7 Task parameters

    Parameter	Description	Default Value
    Execution Memory	Memory allocated for job execution, which automatically changes with the number of CPU cores	8GB
    CPU Cores	Value range: 2 to 32 For each CPU core added, 4 GB execution memory and one concurrency are automatically added.	2
    Maximum Concurrent Requests	Maximum number of jobs that can be concurrently executed. This parameter does not need to be configured and automatically changes with the number of CPU cores.	1
    Auto Retry	Whether to enable automatic retry upon a job failure	No
    Maximum Retries	This parameter is displayed when Auto Retry is set to Yes.	1
    Retry Interval (Seconds)	This parameter is displayed when Auto Retry is set to Yes.	120s
    Write Dirty Data	Whether to record dirty data. By default, dirty data is not recorded. If there is a large amount of dirty data, the synchronization speed of the task is affected. No: Dirty data is not recorded. This is the default value. Dirty data is not allowed. If dirty data is generated during the synchronization, the task fails and exits. Yes: Dirty data is allowed, that is, dirty data does not affect task execution. When dirty data is allowed and its threshold is set: If the generated dirty data is within the threshold, the synchronization task ignores the dirty data (that is, the dirty data is not written to the destination) and is executed normally. If the generated dirty data exceeds the threshold, the synchronization task fails and exits. NOTE: Criteria for determining dirty data: Dirty data is meaningless to services, is in an invalid format, or is generated when the synchronization task encounters an error. If an exception occurs when a piece of data is written to the destination, this piece of data is dirty data. Therefore, data that fails to be written is classified as dirty data. For example, if data of the VARCHAR type at the source is written to a destination column of the INT type, dirty data cannot be written to the migration destination due to improper conversion. When configuring a synchronization task, you can configure whether to write dirty data during the synchronization and configure the number of dirty data records (maximum number of error records allowed in a single partition) to ensure task running. That is, when the number of dirty data records exceeds the threshold, the task fails and exits.	No
    Dirty Data Policy	This parameter is displayed when Write Dirty Data is set to Yes. The following policies are supported: Do not archive: Dirty data is only recorded in job logs, but not stored. Archive to OBS: Dirty data is stored in OBS and printed in job logs.	Do not archive
    Write Dirty Data Link	This parameter is displayed when Dirty Data Policy is set to Archive to OBS. Only links to OBS support dirty data writes.	N/A
    Dirty Data Directory	OBS directory to which dirty data will be written	N/A
    Dirty Data Threshold	This parameter is only displayed when Write Dirty Data is set to Yes. You can set the dirty data threshold as required. NOTE: The dirty data threshold takes effect for each concurrency. For example, if the threshold is 100 and the concurrency is 3, the maximum number of dirty data records allowed by the job is 300. Value -1 indicates that the number of dirty data records is not limited.	100
    Custom attributes	You can add custom attributes to modify some job parameters and enable some advanced functions. For details, see Job Performance Optimization.	N/A

11. Submit and run the job.

    After configuring the job, click Submit in the upper left corner to submit the job.

    Figure 8 Submitting the job
    

    After submitting the job, click Start in the upper left corner. In the displayed dialog box, set required parameters and click OK.

    Figure 9 Starting the job
    

    Table 8 Parameters for starting the job

    Parameter	Description
    Synchronous Mode	Incremental Synchronization: Incremental data synchronization starts from a specified time point. Full and incremental synchronization: All data is synchronized first, and then incremental data is synchronized in real time.
    Time	This parameter must be set for incremental synchronization, and it specifies the start time of incremental synchronization. NOTE: If you set a time that is earlier than the earliest binlog time, the latest log time is used.

12. Monitor the job.

    On the job development page, click Monitor to go to the Job Monitoring page. You can view the status and log of the job, and configure alarm rules for the job. For details, see Real-Time Migration Job O&M.

    Figure 10 Monitoring the job
    

Performance Optimization

If the synchronization speed is too slow, rectify the fault by referring to Job Performance Optimization.