KafkaCDC

Overview

The KafkaCDC module reads data changes in MariaDB via replication and converts them into JSON objects that are then streamed to a Kafka broker.

DDL events (CREATE TABLE, ALTER TABLE) are streamed as JSON objects in the following format (example created by CREATE TABLE test.t1(id INT)):

{
  "namespace": "MaxScaleChangeDataSchema.avro",
  "type": "record",
  "name": "ChangeRecord",
  "table": "t2",              // name of the table
  "database": "test",         // the database the table is in
  "version": 1,               // schema version, incremented when the table format changes
  "gtid": "0-3000-14",        // GTID that created the current version of the table
  "fields": [
    {
      "name": "domain",       // First part of the GTID
      "type": "int"
    },
    {
      "name": "server_id",    // Second part of the GTID
      "type": "int"
    },
    {
      "name": "sequence",     // Third part of the GTID
      "type": "int"
    },
    {
      "name": "event_number", // Sequence number of the event inside the GTID
      "type": "int"
    },
    {
      "name": "timestamp",    // UNIX timestamp when the event was created
      "type": "int"
    },
    {
      "name": "event_type",   // Event type
      "type": {
        "type": "enum",
        "name": "EVENT_TYPES",
        "symbols": [
          "insert",           // The row that was inserted
          "update_before",    // The row before it was updated
          "update_after",     // The row after it was updated
          "delete"            // The row that was deleted
        ]
      }
    },
    {
      "name": "id",           // Field name
      "type": [
        "null",
        "long"
      ],
      "real_type": "int",     // Field type
      "length": -1,           // Field length, if found
      "unsigned": false       // Whether the field is unsigned
    }
  ]
}

The domain, server_id and sequence fields contain the GTID that this event belongs to. The event_number field is the sequence number of events inside the transaction starting from 1. The timestamp field is the UNIX timestamp when the event occurred. The event_type field contains the type of the event, one of:

• insert: the event is the data that was added to MariaDB
• delete: the event is the data that was removed from MariaDB
• update_before: the event contains the data before an update statement modified it
• update_after: the event contains the data after an update statement modified it

All remaining fields contains data from the table. In the example event this would be the fields id and data.

DML events (INSERT, UPDATE, DELETE) are streamed as JSON objects that follow the format specified in the DDL event. The objects are in the following format (example created by INSERT INTO test.t1 VALUES (1)):

{
  "domain": 0,
  "server_id": 3000,
  "sequence": 20,
  "event_number": 1,
  "timestamp": 1580485945,
  "event_type": "insert",
  "id": 1,
  "table_name": "t2",
  "table_schema": "test"
}

The table_name and table_schema fields were added in MaxScale 2.5.3. These contain the table name and schema the event targets.

The router stores table metadata in the MaxScale data directory. The default value is /var/lib/maxscale/<service name>. If data for a table is replicated before a DDL event for it is replicated, the CREATE TABLE will be queried from the master server.

During shutdown, the Kafka event queue is flushed. This can take up to 60 seconds if the network is slow or there are network problems.

Configuration

The servers parameter defines the set of servers where the data is replicated from. The replication will be done from the first master server that is found.

The user and password of the service will be used to connect to the master. This user requires the REPLICATION SLAVE grant.

The KafkaCDC service must not be configured to use listeners. If a listener is configured, all attempts to start a session will fail.

Parameters

bootstrap_servers

The list of Kafka brokers to use in host:port format. Multiple values can be separated with commas. This is a mandatory parameter.

topic

The Kafka topic where the replicated events will be sent. This is a mandatory parameter.

enable_idempotence

Enable idempotent producer mode. This feature requires Kafka version 0.11 or newer to work and is disabled by default.

When enabled, the Kafka producer enters a strict mode which avoids event duplication due to broker outages or other network errors. In HA scenarios where there are more than two MaxScale instances, event duplication can still happen as there is no synchronization between the MaxScale instances.

The Kafka C library, librdkafka, describes the parameter as follows:

When set to true, the producer will ensure that messages are successfully produced exactly once and in the original produce order. The following configuration properties are adjusted automatically (if not modified by the user) when idempotence is enabled: max.in.flight.requests.per.connection=5 (must be less than or equal to 5), retries=INT32_MAX (must be greater than 0), acks=all, queuing.strategy=fifo.

timeout

The connection and read timeout for the replication stream. The default value is 10 seconds.

gtid

The initial GTID position from where the replication is started. By default the replication is started from the beginning. The value of this parameter is only used if no previously replicated events with GTID positions can be retrieved from Kafka.

Once the replication has started and a GTID position has been recorded, this parameter will be ignored. To reset the recorded GTID position, delete the current_gtid.txt file located in /var/lib/maxscale/<SERVICE>/ where <SERVICE> is the name of the KafkaCDC service.

server_id

The server_id used when replicating from the master in direct replication mode. The default value is 1234. This parameter was added in MaxScale 2.5.7.

match

• Type: regex
• Mandatory: No
• Dynamic: Yes

Only include data from tables that match this pattern.

For example, if configured with match=accounts[.].*, only data from the accounts database is sent to Kafka.

The pattern is matched against the combined database and table name separated by a period. This means that the event for the table t1 in the test database would appear as test.t1. The behavior is the same even if the database or the table name contains a period. This means that an event for the test.table table in the my.data database would appear as my.data.test.table.

Here is an example configuration that only sends events for tables from the db1 database. The accounts and users tables in the db1 database are filtered out using the exclude parameter.

[Kafka-CDC]
type=service
router=kafkacdc
servers=server1
user=maxuser
password=maxpwd
bootstrap_servers=127.0.0.1:9092
topic=my-cdc-topic
match=db1[.]
exclude=db1[.](accounts|users)

exclude

• Type: regex
• Mandatory: No
• Dynamic: Yes

Exclude data from tables that match this pattern.

For example, if configured with exclude=mydb[.].*, all data from the tables in the mydb database is not sent to Kafka.

The pattern matching works the same way for both of the exclude and match parameters. See match for an explanation on how the patterns are matched against the database and table names.

cooperative_replication

Controls whether multiple instances cooperatively replicate from the same cluster. This is a boolean parameter and is disabled by default. It was added in MaxScale 6.0.

When this parameter is enabled and the monitor pointed to by the cluster parameter supports cooperative monitoring (currently only mariadbmon), the replication is only active if the monitor owns the cluster it is monitoring.

Whenever an instance that does not own the cluster gains ownership of the cluster, the replication will continue from the latest GTID that was delivered to Kafka.

This means that multiple MaxScale instances can replicate from the same set of servers and the event is only processed once. This feature does not provide exactly-once semantics for the Kafka event delivery. However, it does provide high-availability for the kafkacdc instances which allows automated failover between multiple MaxScale instances.

kafka_ssl

Enable SSL for Kafka connections. This is a boolean parameter and is disabled by default.

kafka_ssl_ca

Path to the certificate authority file in PEM format. If this is not provided, the default system certificates will be used.

kafka_ssl_cert

Path to the public certificate in PEM format.

The client must provide a certificate if the Kafka server performs authentication of the client certificates. This feature is enabled by default in Kafka and is controlled by ssl.endpoint.identification.algorithm.

If kafka_ssl_cert is provided, kafka_ssl_key must also be provided.

kafka_ssl_key

Path to the private key in PEM format.

If kafka_ssl_key is provided, kafka_ssl_cert must also be provided.

kafka_sasl_user

Username for SASL authentication.

If kafka_sasl_user is provided, kafka_sasl_password must also be provided.

kafka_sasl_password

Password for SASL authentication.

If kafka_sasl_password is provided, kafka_sasl_user must also be provided.

kafka_sasl_mechanism

The SASL mechanism used. The default value is PLAIN which uses plaintext authentication. It is recommended to enable SSL whenever plaintext authentication is used.

Allowed values are:

• PLAIN
• SCRAM-SHA-256
• SCRAM-SHA-512

The value that should be used depends on the SASL mechanism used by the Kafka broker.

Example Configuration

The following configuration defines the minimal setup for streaming replication events from MariaDB into Kafka as JSON:

# The server we're replicating from
[server1]
type=server
address=127.0.0.1
port=3306
protocol=MariaDBBackend

# The monitor for the server
[MariaDB-Monitor]
type=monitor
module=mariadbmon
servers=server1
user=maxuser
password=maxpwd
monitor_interval=5000

# The MariaDB-to-Kafka CDC service
[Kafka-CDC]
type=service
router=kafkacdc
servers=server1
user=maxuser
password=maxpwd
bootstrap_servers=127.0.0.1:9092
topic=my-cdc-topic

Limitations

• The KafkaCDC module provides at-least-once semantics for the generated events. This means that each replication event is delivered to kafka at least once but there can be duplicate events in case of failures.