Synchronize data from a PolarDB for MySQL cluster to an Elasticsearch cluster

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%.
• DTS does not synchronize data definition language (DDL) operations. If a DDL operation is performed on a table in the source database during data synchronization, you must perform the following steps: Remove the table from the required objects, remove the index for the table from the Elasticsearch cluster, and then add the table to the required objects. For more information, see Remove an object from a data synchronization task and Add an object to a data synchronization task.
• To add columns to the table that you want to synchronize, perform the following steps: Modify the mapping of the table in the Elasticsearch cluster, perform DDL operations in the PolarDB for MySQL cluster, and then pause and start the data synchronization task.

SQL operations that can be synchronized

INSERT, DELETE, and UPDATE

Data type mappings

The data types of the PolarDB for MySQL cluster and the Elasticsearch cluster do not have one-to-one correspondence. During initial schema synchronization, DTS converts the data types of the PolarDB for MySQL cluster into those of the Elasticsearch cluster. For more information, see Data type mappings for schema synchronization.

Procedure

1. Purchase a data synchronization instance. For more information, see Purchase a DTS instance.
   Note On the buy page, set Source Instance to PolarDB, Destination Instance to Elasticsearch, and 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	The task name that DTS automatically generates. We recommend that you specify a descriptive name that makes it easy to identify the task. You do not need to use a unique task name.
   Source Instance Details	Instance Type	The value of this parameter is set to PolarDB Instance and cannot be changed.
   	Instance Region	The source region that you selected on the buy page. The value of this parameter cannot be changed.
   	PolarDB Instance ID	The ID of the source PolarDB for MySQL cluster.
   	Database Account	The database account of the PolarDB for MySQL cluster. Note The account must have read permissions on the source database.
   	Database Password	The password of the database account.
   Destination Instance Details	Instance Type	This parameter is set to Elasticsearch and cannot be changed.
   	Instance Region	The destination region that you selected on the buy page. The value of this parameter cannot be changed.
   	Elasticsearch	The ID of the destination Elasticsearch cluster.
   	Database Account	The account that is used to connect to the Elasticsearch cluster. The default account is elastic.
   	Database Password	The password of the database account.

7. In the lower-right corner of the page, click Set Whitelist and Next.
   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 complete, we recommend that you remove the CIDR blocks of DTS servers from the whitelists or security groups.
8. Configure the index name, the processing mode of identical index names, and the objects to be synchronized.
   

   Parameter	Description
   Index Name	Table Name If you select Table Name, the name of the index that is created in the Elasticsearch cluster is the same as the name of the table. In this example, the index name is customer. DatabaseName_TableName If you select DatabaseName_TableName, the name of the index that is created in the Elasticsearch cluster is <Database name>_<Table name>. In this example, the index name is dtstestdata_customer.
   Processing Mode In Existed Target Table	Pre-check and Intercept: checks whether the destination database contains indexes that have the same names as the source tables. If the destination database does not contain indexes that have the same names as the source tables, the precheck is passed. Otherwise, an error is returned during precheck and the data synchronization task cannot be started. Note If indexes in the destination database have the same names as the source tables, and cannot be deleted or renamed, you can use the object name mapping feature. For more information, see Rename an object to be synchronized. Ignore: skips the precheck for identical index 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. If the source and destination databases have the same mappings and the primary key of a record in the destination database is the same as that in the source database, the record remains unchanged during initial data synchronization. However, the record is overwritten during incremental data synchronization. If the source and destination databases have different mappings, 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 one or more objects from the Available section and click the icon to move the objects to the Selected section. You can select tables or databases as the objects to be synchronized.
   Rename Databases and Tables	You can use the object name mapping feature to rename the objects that are synchronized to the destination instance. For more information, see Object name mapping.
   Replicate Temporary Tables When DMS Performs DDL Operations	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 online DDL 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 Connections	By default, if DTS fails to connect to the source or destination database, DTS retries within the next 720 minutes (12 hours). You can specify the retry time based on your needs. If DTS reconnects to the source and destination databases within the specified time, DTS resumes the data synchronization task. Otherwise, the data synchronization task fails. Note When DTS retries a connection, you are charged for the DTS instance. We recommend that you specify the retry time based on your business needs. You can also release the DTS instance at your earliest opportunity after the source and destination instances are released.

9. In the Selected section, move the pointer over a table, and then click Edit. In the Edit Table dialog box, configure parameters for the table in the Elasticsearch cluster, such as the index name and type name.
   

   Parameter	Description
   Index Name	For more information, see Terms. Warning The only type of special characters that an index name and type name can contain is underscore (_). To synchronize multiple source tables with the same schema to a destination object, you must repeat this step to set the same index name and type name for the tables.
   Type Name
   Filter	Specify SQL conditions to filter data. Only the data records that meet the specified conditions are synchronized to the destination cluster. For more information, see Use SQL conditions to filter data.
   IsPartition	Select whether to set partitions. If you select Yes, you must also specify the partition key column and number of partitions.
   Settings_routing	Specify whether you want to store a document on a specified shard of the destination Elasticsearch cluster. For more information, see _routing. If you select Yes, you can specify custom columns for routing. If you select No, the _id value is used for routing. Note If the version of the destination Elasticsearch cluster is 7.4, you must select No.
   _id value	Primary key column Composite primary key fields are merged into one column. Business key If you select a business key, you must also specify the business key column.
   add param	Select the column parameter and parameter value. For more information, see Mapping parameters in the Elasticsearch documentation. Note DTS supports only the parameters that can be selected.

10. In the lower-right corner of the page, click 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 icon next to each failed item to view details.
      • After you troubleshoot the issues based on the causes, you can run a precheck again.
      • If you do not need to troubleshoot the issues, you can ignore failed items and run a precheck again.
11. Close the Precheck dialog box after the following message is displayed: The precheck is passed. Then, the data synchronization task starts.
12. Wait until initial synchronization is completed and the data synchronization task enters the Synchronizing state.
    You can view the state of the data synchronization task on the Synchronization Tasks page.

Check the index and data

If the data synchronization task is in the Synchronizing state, you can connect to the Elasticsearch cluster by using the Elasticsearch-Head plug-in. Then, you can check whether the index is created and data is synchronized as expected. For more information, see Use Cerebro to access an Elasticsearch cluster.