Iceberg Sink Kafka Connector

Direct Iceberg output is not currently supported in Feldera. However, you can write to Iceberg indirectly via the Iceberg Sink Kafka Connect Connector.

Writing to Iceberg via Kafka Connect

Feldera enables integration with Apache Iceberg by first writing change data capture (CDC) records to Kafka, and then using the Iceberg Sink Connector for Kafka Connect to persist these changes to Iceberg tables.

Workflow

1. Feldera writes Avro-encoded CDC data to a Kafka topic.
2. Kafka Connect consumes this topic using the Iceberg Sink Connector.
3. The connector writes updates to an Iceberg table.

Avro format configuration

The Avro format must be configured with:

• An index on the identifying columns of the view, consistent with iceberg.tables.default-id-columns.
• update_format set to raw
• cdc_field defined (e.g. set to op)
  • This cdc_field should match the iceberg.tables.cdc-field config in Iceberg sink connector for Kafka Connect.
  • If cdc_field is not set, it will be append-only log of output records without any CDC metadata.
  • Each output record will contain the field op which will have one of the following values:
    • I for Insert
    • D for Delete
    • U for Upsert

Example:

create materialized view pizzas with (
   'connectors' = '[
    {
      "index": "idx1",
      "transport": {
          "name": "kafka_output",
          "config": {
              "bootstrap.servers": "localhost:29092",
              "topic": "pizzas"
          }
      },
      "format": {
          "name": "avro",
          "config": {
              "registry_urls": ["http://localhost:18081"],
              "update_format": "raw",
              "cdc_field": "op",
              "subject_name_strategy": "topic_name"
          }
      }
    }
   ]'
) as select * from tbl order by order_number desc limit 10;
create index idx1 on pizzas(order_number);

important

The index attribute is required and ensures proper materialization of the Iceberg table. For more information, see documentation](/connectors/unique_keys#views-with-unique-keys).

Iceberg sink connector configuration for Kafka Connect

Sample configuration for setting up Iceberg Sink Connector using Kafka Connect.

{
    "connector.class": "io.tabular.iceberg.connect.IcebergSinkConnector",
    "tasks.max": "6",
    "topics": "pizzas",
    "iceberg.tables": "rpc.pizzas",
    "iceberg.catalog": "demo",
    "iceberg.catalog.type": "rest",
    "iceberg.catalog.uri": "http://iceberg-rest:8181",
    "iceberg.catalog.client.region": "us-east-1",
    "iceberg.catalog.s3.endpoint": "http://minio:9000",
    "iceberg.catalog.s3.path-style-access": "true",
    "iceberg.tables.auto-create-enabled": "true",
    "iceberg.tables.evolve-schema-enabled": "true",
    "iceberg.control.commit.interval-ms": 30000,
    "iceberg.tables.cdc-field": "op",
    "iceberg.tables.default-id-columns": "order_number",
    "iceberg.tables.upsert-mode-enabled": "true",
    "key.converter.schema.registry.url": "http://registry:8081",
    "key.converter": "io.confluent.connect.avro.AvroConverter",
    "key.converter.schemas.enable": "true",
    "value.converter.schema.registry.url": "http://registry:8081",
    "value.converter": "io.confluent.connect.avro.AvroConverter",
    "value.converter.schemas.enable": "true"
}

• Ensure that iceberg.tables.default-id-columns is consistent with the index definition in Feldera.
• Ensure that the Iceberg table is accessible from Kafka Connect.
• Ensure that iceberg.tables.auto-create-enabled is set to true if the table doesn't already exist.
• Ensure that iceberg.tables.evolve-schema-enabled is set to true if you want to dynamically update the Iceberg table schema to match the SQL view declaration.
• Ensure that iceberg.tables.cdc-field is set to the same value as cdc_field in the output connector configuration in Feldera.