MySQL CDC Source (Debezium) Connector for Confluent Cloud

Note

If you are installing the connector locally for Confluent Platform, see Debezium MySQL Source Connector for Confluent Platform.

The Kafka Connect MySQL Change Data Capture (CDC) Source (Debezium) connector for Confluent Cloud can obtain a snapshot of the existing data in a MySQL database and then monitor and record all subsequent row-level changes to that data. The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data formats. All of the events for each table are recorded in a separate Apache Kafka® topic. The events can then be easily consumed by applications and services. Note that deleted records are not captured.

Important

If you are still on Confluent Cloud Enterprise, please contact your Confluent Account Executive for more information about using this connector.

Features

The MySQL CDC Source (Debezium) connector provides the following features:

• Topics created automatically: The connector automatically creates Kafka topics using the naming convention: <database.server.name>.<schemaName>.<tableName>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3.
• Databases included and Databases excluded: Sets whether a database is or is not monitored for changes. By default, the connector monitors every database on the server.
• Tables included and Tables excluded: Sets whether a table is or is not monitored for changes. By default, the connector monitors every non-system table.
• Tasks per connector: Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").
• Snapshot mode: Specifies the criteria for running a snapshot.
• Tombstones on delete: Sets whether a tombstone event is generated after a delete event. Default is true.
• Database authentication: Uses password authentication.
• Data formats: Supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

Note

database.server.id is set to a random number between 5400 and 6400.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For more information, see the Confluent Cloud connector limitations.

Quick Start

Use this quick start to get up and running with the MySQL CDC Source (Debezium) connector. The quick start provides the basics of selecting the connector and configuring it to obtain a snapshot of the existing data in a MySQL database and then monitoring and recording all subsequent row-level changes.

Prerequisites

• Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).

• The Confluent Cloud CLI installed and configured for the cluster. See Install the Confluent Cloud CLI.

• Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

• Public access may be required for your database. See Internet Access to Resources for details. The example below shows the AWS Management Console when setting up a MySQL database.

  

  Public access enabled

• Public inbound traffic access (0.0.0.0/0) may be required for the VPC where the database is located, unless the environment is configured for VPC peering. For more information about public Internet access to resources, see Internet Access to Resources. The example below shows the AWS Management Console when setting up security group rules for the VPC.

  

  Open inbound traffic

  Note

  See your specific cloud platform documentation for how to configure security rules for your VPC.

• Kafka cluster credentials. You can use one of the following ways to get credentials:

  • Create a Confluent Cloud API key and secret. To create a key and secret, go to Kafka API keys in your cluster or you can autogenerate the API key and secret directly in the UI when setting up the connector.
  • Create a Confluent Cloud service account for the connector.

• An ACL to create a topic prefix is required. Note that the prefix is the database server name (example, the server name is cdc in the configuration property "database.server.name": "cdc"). See ccloud kafka acl create for the CLI command reference.

  ccloud kafka acl create --allow --service-account "<service-account-id>" --operation "CREATE" --prefix --topic "<database.server.name>"
  

  ccloud kafka acl create --allow --service-account "<service-account-id>" --operation "WRITE" --prefix --topic "<database.server.name>"
  

• Update the following settings for the MySQL database.

  1. Turn on backup for the database.

  2. Create a new parameter group and set the following parameters:

     binlog_format=ROW
     binlog_row_image=full
     

  3. Apply the new parameter group to the database.

  4. Reboot the database.

  The following example screens are from Amazon RDS:

  
  
  

Using the Confluent Cloud GUI

Step 1: Launch your Confluent Cloud cluster.

See the Quick Start for Apache Kafka using Confluent Cloud for installation instructions.

Step 2: Add a connector.

Click Connectors. If you already have connectors in your cluster, click Add connector.

Step 3: Select your connector.

Click the MySQL CDC Source connector icon.

Step 4: Set up the connection.

Complete the following and click Continue.

Note

• Make sure you have all your prerequisites completed.
• An asterisk ( * ) designates a required entry.

1. Enter a connector name.

2. Enter your Kafka Cluster credentials. The credentials are either the API key and secret or the service account API key and secret.

3. Add the connection details for the database.

   Important

   Do not include jdbc:xxxx:// in the Connection host field. The example below shows a sample host address.

   

4. Add the Database details for your database. Review the following notes for more information about field selections.

   • Databases included: Enter a comma-separated list of fully-qualified database identifiers for the connector to monitor. By default, the connector monitors all databases on the server. A fully-qualified database name is in the form <database-name>. This can’t be used with Databases excluded.
   • Databases excluded: Enter a comma-separated list of fully-qualified database identifiers for the connector to ignore. By default, the connector monitors all databases on the server. A fully-qualified database name is in the form <database-name>. This can’t be used with Databases included.
   • Tables included: Enter a comma-separated list of fully-qualified table identifiers for the connector to monitor. By default, the connector monitors all non-system tables. A fully-qualified table name is in the form schemaName.tableName. This can’t be used with Tables excluded.
   • Tables excluded: Enter a comma-separated list of fully-qualified table identifiers for the connector to ignore. A fully-qualified table name is in the form schemaName.tableName. This can’t be used Tables included.
   • Snapshot mode: Specifies the criteria for performing a database snapshot when the connector starts.
     • The default setting is initial. When selected, the connector takes a snapshot of the structure and data from captured tables. This is useful if you want the topics populated with a complete representation of captured table data when the connector starts.
     • never specifies that the connector should never perform snapshots, and that when starting for the first time, the connector starts reading from where it last left off.
     • when_needed specifies that the connector performs a snapshot when it considers a snapshot is needed.
   • Tombstones on delete: Configure whether a tombstone event should be generated after a delete event. The default is true.

5. Enter values for the following properties:

   • Poll interval (ms): The time in milliseconds that the connector waits before polling for new CDC events. Defaults to 1000 ms (1 second).
   • Max batch size: Integer that defines the maximum batch size to process each iteration. Defaults to 1000 events.

6. Select the values for the following properties:

   • Output message format: (data coming from the connector): AVRO, JSON (schemaless), JSON_SR (JSON Schema), or PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

   • After-state only: (Optional) Defaults to true, which results in the Kafka record having only the record state from change events applied. Select false to maintain the prior record states after applying the change events.

   • JSON output decimal format: (Optional) Defaults to BASE64.

     

7. Enter the number of tasks in use by the connector. Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").

Step 5: Launch the connector.

Verify the connection details and click Launch.

Step 6: Check the connector status.

The status for the connector should go from Provisioning to Running. It may take a few minutes.

Step 7: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

Note

A topic named dbhistory.<databas.server.name>.<connect-id> is automatically created. This topic is created based on the database.history.kafka.topic property (that may be configured). This topic has one partition.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For additional information about this connector, see Debezium MySQL Source Connector for Confluent Platform. Note that not all Confluent Platform connector features are provided in the Confluent Cloud connector.

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent Cloud CLI to manage your resources in Confluent Cloud.

Using the Confluent Cloud CLI

Complete the following steps to set up and run the connector using the Confluent Cloud CLI.

Note

Make sure you have all your prerequisites completed.

Step 1: List the available connectors.

Enter the following command to list available connectors:

ccloud connector-catalog list

Step 2: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

ccloud connector-catalog describe <connector-catalog-name>

For example:

ccloud connector-catalog describe MySqlCdcSource

Example output:

Following are the required configs:
connector.class: MySqlCdcSource
name
kafka.api.key
kafka.api.secret
database.hostname
database.user
database.server.name
output.data.format
tasks.max

Step 3: Create the connector configuration file.

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

{
  "connector.class": "MySqlCdcSource",
  "name": "MySqlCdcSourceConnector_0",
  "kafka.api.key": "****************",
  "kafka.api.secret": "****************************************************************",
  "database.hostname": "database-2.<host-ID>.us-west-2.rds.amazonaws.com",
  "database.port": "3306",
  "database.user": "admin",
  "database.password": "**********",
  "database.server.name": "mysql",
  "database.whitelist": "employee",
  "table.includelist":"employees.departments,
  "snapshot.mode": "initial",
  "output.data.format": "AVRO",
  "tasks.max": "1"
}

Note the following property definitions:

• "connector.class": Identifies the connector plugin name.
• "name": Sets a name for your new connector.
• "table.includelist": (Optional) Enter a comma-separated list of fully-qualified table identifiers for the connector to monitor. By default, the connector monitors all non-system tables. A fully-qualified table name is in the form schemaName.tableName.
• "snapshot.mode": Specifies the criteria for performing a database snapshot when the connector starts.
  • The default setting is initial. When selected, the connector takes a snapshot of the structure and data from captured tables. This is useful if you want the topics populated with a complete representation of captured table data when the connector starts.
  • never specifies that the connector should never perform snapshots, and that when starting for the first time, the connector starts reading from where it last left off.
  • when_needed specifies that the connector performs a snapshot when it considers a snapshot is needed.
• "output.data.format": Sets the output message format (data coming from the connector). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
• "after.state.only": (Optional) Defaults to true, which results in the Kafka record having only the record state from change events applied. Enter false to maintain the prior record states after applying the change events.
• "json.output.decimal.format": (Optional) Defaults to BASE64. Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:
  • BASE64 to serialize DECIMAL logical types as base64 encoded binary data.
  • NUMERIC to serialize Connect DECIMAL logical type values in JSON or JSON_SR as a number representing the decimal value.
• "tasks.max": Enter the number of tasks in use by the connector. Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").

Step 4: Load the properties file and create the connector.

Enter the following command to load the configuration and start the connector:

ccloud connector create --config <file-name>.json

For example:

ccloud connector create --config mysql-cdc-source.json

Example output:

Created connector MySqlCdcSourceConnector_0 lcc-ix4dl

Step 5: Check the connector status.

Enter the following command to check the connector status:

ccloud connector list

Example output:

ID          |            Name             | Status  |  Type
+-----------+-----------------------------+---------+-------+
lcc-ix4dl   | MySqlCdcSourceConnector_0   | RUNNING | source

Step 6: Check the Kafka topic.

After the connector is running, verify that messages are populating your Kafka topic.

Note

A topic named dbhistory.<databas.server.name>.<connect-id> is automatically created. This topic is created based on the database.history.kafka.topic property (that may be configured). This topic has one partition.

For more information and examples to use with the Confluent Cloud API for Connect, see the Connect API for Confluent Cloud section.

For additional information about this connector, see Debezium MySQL Source Connector for Confluent Platform. Note that not all Confluent Platform connector features are provided in the Confluent Cloud connector.

Next Steps

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent Cloud CLI to manage your resources in Confluent Cloud.