Configuring a Job for Synchronizing Data from DMS for Kafka to Doris

Supported Source and Destination Database Versions

**Table 1** Supported database versions
Source Database	Destination Database
Kafka cluster (2.7 and 3.x)	Doris (Doris1.2 and Doris2.0)

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.

**Table 2** Database account permissions
Type	Required Permissions
Source database connection account	When ciphertext access is enabled for Kafka, the account must have the permissions to publish and subscribe to topics. In other scenarios, there are no special permission requirements.
Destination database connection account	The account must have the following permissions for each table in the destination database: LOAD, SELECT, CREATE, ALTER, and DROP.

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.

**Table 3** Synchronization objects
Type	Note
Synchronization objects	All Kafka messages can be synchronized. The CDC JSON message body can be parsed, and only messages corresponding to the specified upstream database tables can be synchronized.

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.

**Table 4** Notes
Type	Constraint
Database	Kafka instances are supported if SASL_PLAINTEXT is enabled, including the SCRAM-SHA-512 and PLAIN authentication mechanisms. During data synchronization, SASL_SSL authentication can be enabled only for DMS for Kafka that uses the default certificate. It cannot be enabled for other types of Kafka. MRS Kafka for which Kerberos authentication is enabled is supported. Object names in the destination database must meet the following requirements: The table name can contain a maximum of 64 characters and must start with a letter. Only letters, digits, underscores (_), and hyphens (-) are allowed. The field name can contain a maximum of 255 characters. You are advised to use common characters. Do not use special characters such as Chinese characters.
Usage	General: During real-time synchronization, the IP addresses, ports, accounts, and passwords cannot be changed. Doris tables using aggregation models cannot be automatically created. They can only be manually created. MRS Doris supports HTTP and HTTPS. Cloud table Doris supports only HTTP. Only the StreamLoad mode is supported for import. Troubleshooting: If any problem occurs during task creation, startup, full synchronization, incremental synchronization, or completion, rectify the fault by referring to FAQs.
Other	Doris cannot use a string as the primary key, even if as one of the fields in a composite primary key. DDL operations cannot be synchronized in multi-concurrency scenarios.

Procedure

This section uses real-time synchronization from Kafka to Doris 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.

Create a real-time migration job by following the instructions in Creating a Real-Time Migration Job and go to the job configuration page.
Select the data connection type. Select Kafka for Source and Doris for Destination.

Figure 1 Selecting the data connection type
Select a job type. The default migration type is Real-time. The migration scenario is Single table.

Figure 2 Setting the migration job type

For details about synchronization scenarios, see Synchronization Scenarios.
Configure network resources. Select the created Kafka and Doris 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.
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?
Configure source parameters.

Select the Kafka topics to be synchronized.
Figure 4 Entering a Kafka topic
- Topic
  Enter a Kafka topic to be migrated.
- Data Format
  Format of the message content in the source Kafka topic. DataArts Migration can process the following message:
  
  DEBEZIUM_JSON: CDC JSON messages in Debezium format can be parsed and synchronized to the destination table.
- Consumer Group ID
  A consumer subscribes to a topic. A consumer group consists of one or more consumers. DataArts Migration allows you to specify the Kafka consumer group to which a consumption action belongs.
- Source Kafka Attributes
  You can add Kafka configuration items with the properties. prefix. The job automatically removes the prefix and transfers configuration items to the underlying Kafka client. For details about the parameters, see the configuration descriptions in Kafka documentation.
- Upstream Data Source Type
  This parameter is mandatory only when Data Format is set to DEBEZIUM_JSON. Currently, only MySQL is supported, indicating that CDC JSON data is generated by MySQL.
- Database Table Names
  This parameter is mandatory only when Data Format is set to DEBEZIUM_JSON. It indicates the database tables that Kafka messages come from. The task parses CDC JSON data and synchronizes only the data for which database tables have been configured.

Configure destination parameters.

The source Kafka data in CDC_JSON format may come from multiple upstream database tables. DataArts Migration can match upstream database tables with destination database tables.

Set Database and Table Matching Policy.
- Database Matching Policy
  - Same name as the source database: Data will be synchronized to the Doris database with the same name as the source database.
  - Custom: Data will be synchronized to the Doris database you specify.
- Table Matching Policy
  - Same name as the source table: Data will be synchronized to the Doris table with the same name as the source table.
  - Custom: Data will be synchronized to the Doris table you specify.
Figure 5 Database and table matching policy in the sharding 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 Doris parameters.

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

**Table 5** Doris advanced parameters
Parameter	Type	Default Value	Unit	Description
doris.request.connect.timeout.ms	int	30000	ms	Doris connection timeout interval
doris.request.read.timeout.ms	int	30000	ms	Doris read timeout interval
doris.request.retries	int	3	-	Number of retries upon a Doris request failure
sink.max-retries	int	3	-	Maximum number of retries upon a data writing failure
sink.batch.interval	string	1s	h/min/s	Interval at which an asynchronous thread writes data
sink.enable-delete	boolean	true	-	Whether to enable the deletion function. If this function is disabled, data deleted from the source will not be deleted from the destination.
sink.batch.size	int	20000	-	Maximum number of rows that can be written (inserted, updated, or deleted) at a time
sink.batch.bytes	long	10485760	bytes	Maximum number of bytes that can be written (inserted, updated, or deleted) at a time
logical.delete.enabled	boolean	false	-	Whether to enable logical deletion. If this function is enabled, the destination must contain the deletion flag column. When data is deleted from the source database, the corresponding data in the destination database will not be deleted. Instead, the deletion flag column is set to true, indicating that the data is not contained at the source.
logical.delete.column	string	logical_is_deleted	-	Name of the logical deletion column. The default value is logical_is_deleted. You can customize the value.
sink.keyby.mode	string	pk	-	Partitioning mode when concurrent writes are performed on Doris. Default value: pk (primary key). If the source is Kafka, and it does not have a primary key, select table to partition data by table name.
doris.sink.flush.tasks	int	1	-	Number of concurrent flushes of a single TaskManager
sink.properties.format	string	json	-	Data format used by Stream Load. The value can be json or csv.
sink.properties.Content-Encoding	string	-	-	Compression format of the HTTP header message body. Currently, only CSV files can be compressed, and the .gzip format is supported.
sink.properties.compress_type	string	-	-	File compression format. Currently, only CSV files can be compressed. The .gz, .lzo, .bz2, .lz4, .lzop, and .deflate compression formats are supported.

Refresh the mapping between the source and destination tables.

Figure 6 Mapping between source and destination tables
- Synchronization Primary Key
  Primary key of the destination Doris table
- Table Source
  This link does not support automatic table creation. You must manually create Doris tables.
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

Configure task parameters.

**Table 6** 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

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
Click to enlarge

After submitting the job, click Start on the job development page. In the displayed dialog box, set required parameters and click OK.

Figure 9 Starting the job
Click to enlarge

**Table 7** Parameters for starting the job
Parameter	Description
Offset	Earliest: Data consumption starts from the earliest offset of the Kafka topic. Latest: Data consumption starts from the latest offset of the Kafka topic. Time Range: Data consumption starts from the offset of the Kafka topic obtained based on the time.
Time	This parameter is required if Offset Parameter is set to Time Range. It specifies the start time of synchronization. NOTE: If you set a time earlier than the earliest offset of Kafka messages, data consumption starts from the earliest offset by default.

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