When you enable the Kafka indexing service, you can configure supervisors on the Overlord to manage the creation and lifetime of Kafka indexing tasks.
Kafka indexing tasks read events using Kafka's own partition and offset mechanism to guarantee exactly-once ingestion. The supervisor oversees the state of the indexing tasks to:
This topic covers how to submit a supervisor spec to ingest event data, also known as message data, from Kafka. See the following for more information:
- For a reference of Kafka supervisor spec configuration options, see the [Kafka supervisor reference](./kafka-supervisor-reference.md).
- For operations reference information to help run and maintain Apache Kafka supervisors, see [Kafka supervisor operations](./kafka-supervisor-operations.md).
- For a walk-through, see the [Loading from Apache Kafka](../../tutorials/tutorial-kafka.md) tutorial.
The Kafka indexing service supports transactional topics introduced in Kafka 0.11.x by default. The consumer for Kafka indexing service is incompatible with older Kafka brokers. If you are using an older version, refer to the [Kafka upgrade guide](https://kafka.apache.org/documentation/#upgrade).
If your Kafka cluster enables consumer-group based ACLs, you can set `group.id` in `consumerProperties` to override the default auto generated group id.
To use the Kafka indexing service, load the `druid-kafka-indexing-service` extension on both the Overlord and the MiddleManagers. See [Loading extensions](../../configuration/extensions.md) for instructions on how to configure extensions.
Similar to the ingestion spec for batch ingestion, the supervisor spec configures the data ingestion for Kafka streaming ingestion. A supervisor spec has the following sections:
-`dataSchema` to specify the Druid datasource name, primary timestamp, dimensions, metrics, transforms, and any necessary filters.
-`ioConfig` to configure Kafka connection settings and configure how Druid parses the data. Kafka-specific connection details go in the `consumerProperties`. The `ioConfig` is also where you define the input format (`inputFormat`) of your Kafka data. For supported formats for Kafka and information on how to configure the input format, see [Data formats](../../ingestion/data-formats.md).
-`tuningConfig` to control various tuning parameters specific to each ingestion method.
For a full description of all the fields and parameters in a Kafka supervisor spec, see the [Kafka supervisor reference](./kafka-supervisor-reference.md).
The following example demonstrates a supervisor spec for Kafka that uses the `JSON` input format. In this case Druid parses the event contents in JSON format:
Using `{ "type": "json" }` as the input format would only parse the payload value.
To parse the Kafka metadata in addition to the payload, use the `kafka` input format.
You would configure it as follows:
-`valueFormat`: Define how to parse the payload value. Set this to the payload parsing input format (`{ "type": "json" }`).
-`timestampColumnName`: Supply a custom name for the Kafka timestamp in the Druid schema to avoid conflicts with columns from the payload. The default is `kafka.timestamp`.
Note that for `tsv`,`csv`, and `regex` formats, you need to provide a `columns` array to make a valid input format. Only the first one is used, and its name will be ignored in favor of `keyColumnName`.
-`keyColumnName`: Supply the name for the Kafka key column to avoid conflicts with columns from the payload. The default is `kafka.key`.
Putting it together, the following input format (that uses the default values for `timestampColumnName`, `headerColumnPrefix`, and `keyColumnName`)
Druid starts a supervisor for a dataSource when you submit a supervisor spec. You can use the data loader in the web console or you can submit a supervisor spec to the following endpoint:
