Create a stream reactor sink connector from Apache Kafka® to Redis®*#

The Redis stream reactor sink connector enables you to move data from an Aiven for Apache Kafka® cluster to a Redis®* database. The Lenses.io implementation enables you to write KCQL transformations on the topic data before sending it to the Redis database.

Important

A known issue with the GEOADD command in version 4.2.0 of the Redis stream reactor sink connector may cause exceptions during initialization under specific configurations. For more information, see the GitHub issue.

Note

You can check the full set of available parameters and configuration options in the connector’s documentation.

Prerequisites#

To setup a Redis sink connector, you need an Aiven for Apache Kafka service with Kafka Connect enabled or a dedicated Aiven for Apache Kafka Connect cluster.

Furthermore you need to collect the following information about the target Redis database upfront:

  • REDIS_HOSTNAME: The Redis hostname

  • REDIS_PORT: The Redis port

  • REDIS_PASSWORD: The Redis password

  • REDIS_SSL: The Redis SSL setting, should be true or false

  • TOPIC_LIST: The list of topics to sink divided by comma

  • KCQL_TRANSFORMATION: The KCQL syntax to parse the topic data, should be in the format:

    [INSERT INTO REDIS_CACHE]
SELECT LIST_OF_FIELDS
FROM APACHE_KAFKA_TOPIC

  • APACHE_KAFKA_HOST: The hostname of the Apache Kafka service, only needed when using Avro as data format

  • SCHEMA_REGISTRY_PORT: The Apache Kafka’s schema registry port, only needed when using Avro as data format

  • SCHEMA_REGISTRY_USER: The Apache Kafka’s schema registry username, only needed when using Avro as data format

  • SCHEMA_REGISTRY_PASSWORD: The Apache Kafka’s schema registry user password, only needed when using Avro as data format

Note

If you’re using Aiven for Redis and Aiven for Apache Kafka, the above details are available in the Aiven console service Overview tab or via the dedicated avn service get command with the Aiven CLI.

The SCHEMA_REGISTRY related parameters are available in the Aiven for Apache Kafka® service page, Overview tab, and Schema Registry subtab

As of version 3.0, Aiven for Apache Kafka no longer supports Confluent Schema Registry. For more information, read the article describing the replacement, Karapace

Setup a Redis sink connector with Aiven Console#

The following example demonstrates how to setup a Redis sink connector for Apache Kafka using the Aiven Console.

Define a Kafka Connect configuration file#

Define the connector configurations in a file (we’ll refer to it with the name redis_sink.json) with the following content, creating a file is not strictly necessary but allows to have all the information in one place before copy/pasting them in the Aiven Console:

{
    "name":"CONNECTOR_NAME",
    "connector.class": "com.datamountaineer.streamreactor.connect.redis.sink.RedisSinkConnector",
    "topics": "TOPIC_LIST",
    "connect.redis.host": "REDIS_HOSTNAME",
    "connect.redis.port": "REDIS_PORT",
    "connect.redis.password": "REDIS_PASSWORD",
    "connect.redis.ssl.enabled": "REDIS_SSL",
    "connect.redis.kcql": "KCQL_TRANSFORMATION",
    "key.converter": "io.confluent.connect.avro.AvroConverter",
    "key.converter.schema.registry.url": "https://APACHE_KAFKA_HOST:SCHEMA_REGISTRY_PORT",
    "key.converter.basic.auth.credentials.source": "USER_INFO",
    "key.converter.schema.registry.basic.auth.user.info": "SCHEMA_REGISTRY_USER:SCHEMA_REGISTRY_PASSWORD",
    "value.converter": "io.confluent.connect.avro.AvroConverter",
    "value.converter.schema.registry.url": "https://APACHE_KAFKA_HOST:SCHEMA_REGISTRY_PORT",
    "value.converter.basic.auth.credentials.source": "USER_INFO",
    "value.converter.schema.registry.basic.auth.user.info": "SCHEMA_REGISTRY_USER:SCHEMA_REGISTRY_PASSWORD"
}

The configuration file contains the following entries:

  • name: the connector name, replace CONNECTOR_NAME with the name you want to use for the connector.

  • connect.redis.*: sink parameters collected in the prerequisite phase.

  • key.converter and value.converter: defines the messages data format in the Apache Kafka topic. The io.confluent.connect.avro.AvroConverter converter translates messages from the Avro format. To retrieve the messages schema we use Aiven’s Karapace schema registry as specified by the schema.registry.url parameter and related credentials.

Note

The key.converter and value.converter sections define how the topic messages will be parsed and needs to be included in the connector configuration.

When using Avro as source data format, you need to set following parameters

  • value.converter.schema.registry.url: pointing to the Aiven for Apache Kafka schema registry URL in the form of https://APACHE_KAFKA_HOST:SCHEMA_REGISTRY_PORT with the APACHE_KAFKA_HOST and SCHEMA_REGISTRY_PORT parameters retrieved in the previous step.

  • value.converter.basic.auth.credentials.source: to the value USER_INFO, since you’re going to login to the schema registry using username and password.

  • value.converter.schema.registry.basic.auth.user.info: passing the required schema registry credentials in the form of SCHEMA_REGISTRY_USER:SCHEMA_REGISTRY_PASSWORD with the SCHEMA_REGISTRY_USER and SCHEMA_REGISTRY_PASSWORD parameters retrieved in the previous step.

Create a Kafka Connect connector with the Aiven Console#

To create a Apache Kafka Connect connector, follow these steps:

  1. Log in to the Aiven Console and select the Aiven for Apache Kafka® or Aiven for Apache Kafka Connect® service where the connector needs to be defined.

  2. Select Connectors from the left sidebar.

  3. Select Create New Connector, the button is enabled only for services with Kafka Connect enabled.

  4. Select Stream Reactor Redis Sink.

  5. In the Common tab, locate the Connector configuration text box and select on Edit.

  6. Paste the connector configuration (stored in the redis_sink.json file) in the form.

  7. Select Apply.

    Note

    The Aiven Console parses the configuration file and fills the relevant UI fields. You can review the UI fields across the various tab and change them if necessary. The changes will be reflected in JSON format in the Connector configuration text box.

  8. After all the settings are correctly configured, select Create connector.

  9. Verify the connector status under the Connectors screen.

  10. Verify the presence of the data in the target Redis service.

Note

You can also create connectors using the Aiven CLI command.

Example: Create a Redis sink connector#

If you have a topic named students containing the following data that you want to move to Redis:

{"id":1, "name":"carlo", "age": 77}
{"id":2, "name":"lucy", "age": 55}
{"id":3, "name":"carlo", "age": 33}
{"id":2, "name":"lucy", "age": 21}

You can sink the students topic to Redis with the following connector configuration, after replacing the placeholders for REDIS_HOST, REDIS_PORT, REDIS_DB_NAME, REDIS_USERNAME and REDIS_PASSWORD:

{
    "name": "my-redis-sink",
    "connector.class": "com.datamountaineer.streamreactor.connect.redis.sink.RedisSinkConnector",
    "connect.redis.host": "REDIS_HOSTNAME",
    "connect.redis.port": "REDIS_PORT",
    "connect.redis.password": "REDIS_PASSWORD",
    "connect.redis.ssl.enabled": "REDIS_SSL",
    "topics": "students",
    "value.converter": "org.apache.kafka.connect.json.JsonConverter",
    "value.converter.schemas.enable": "false",
    "connect.redis.kcql": "INSERT INTO students- SELECT * FROM students PK id"
}

The configuration file contains the following peculiarities:

  • "topics": "students": setting the topic to sink

  • "connect.redis": the connection parameters placeholders

  • "value.converter": "org.apache.kafka.connect.json.JsonConverter" and "value.converter.schemas.enable": "false": the topic value is in JSON format without a schema

  • "connect.redis.kcql": "INSERT INTO students- SELECT * FROM students PK id": the connector logic is to insert every topic message as new entry in Redis, using the id field as key prefixed with students- (configured in the INSERT INTO statement).

Once the connector is created successfully, you should see the following three entries in the target Redis database.

1) "students-1" containing "{\"name\":\"carlo\",\"id\":1,\"age\":77}"
2) "students-2" containing "{\"name\":\"lucy\",\"id\":2,\"age\":21}"
3) "students-3" containing "{\"name\":\"carlo\",\"id\":3,\"age\":33}"

There are only three keys in Redis since there were two messages in the topic sharing the "id": 2, and the connector will overwrite entries sharing the same key.