Manage Kafka Streams Application Topics in Confluent Platform

A Kafka Streams application continuously reads from Apache Kafka® topics, processes the read data, and then writes the processing results back into Kafka topics. The application may also auto-create other Kafka topics in the Kafka brokers, for example state store changelogs topics. This section describes the differences these topic types and how to manage the topics and your applications.

Kafka Streams distinguishes between user topics and internal topics.

User topics

User topics exist externally to an application and are read from or written to by the application, including:

Input topics
Topics that are specified via source processors in the application’s topology; e.g. via StreamsBuilder#stream(), StreamsBuilder#table() and Topology#addSource().
Output topics
Topics that are specified via sink processors in the application’s topology; e.g. via KStream#to(), and Topology#addSink().
Intermediate topics
Topics that are both input and output topics of the application’s topology.

User topics must be created and manually managed ahead of time (e.g., via the topic tools). If user topics are shared among multiple applications for reading and writing, the application users must coordinate topic management. If user topics are centrally managed, application users would not need to manage topics themselves but simply obtain access to them.

Don’t use the auto-create topic feature on the brokers to create user topics, for the following reasons:

  • Auto-creation of topics may be disabled in your Kafka cluster.
  • Auto-creation automatically applies the default topic settings, like the replicaton factor. These default settings may not be what you want for certain output topics, for example, auto.create.topics.enable=true in the Kafka broker configuration.

Internal topics

Internal topics are used internally by the Kafka Streams application while executing, for example the changelog topics for state stores. These topics are created by the application and are only used by that stream application.

From the broker perspective, internal topics are regular topics, in contrast to “broker internal” topics like __consumer_offsets or __transaction_state.

If security is enabled on the Kafka brokers, you must grant the underlying clients admin permissions so that they can create internal topics set. For more information, see Secure Deployment for Kafka Streams in Confluent Platform.

The internal topics follow the naming convention <>-<operatorName>-<suffix>, but this convention isn’t guaranteed for future releases. For more information about configuring parameters for internal topics, see Internal topic parameters.

If automatic topic creation has been disabled, Kafka Streams applications will continue to work. Kafka Streams applications use the Admin Client, so internal topics are still created. Even if automatic topic creation is enabled, internal topics will be created with a specific number of partitions and a replication factor as specified in the StreamsConfig.

The following settings apply to the default configuration for internal topics:

  • For all internal topics, message.timestamp.type is set to CreateTime.
  • For internal repartition topics, the compaction policy is delete and the retention time is -1 (infinite).
  • For internal changelog topics for key-value stores, the compaction policy is compact.
  • For internal changelog topics for windowed key-value stores, the compaction policy is delete,compact. The retention time is set to 24 hours plus your setting for the windowed store.
  • For internal changelog topics for versioned state stores, the cleanup policy is compact, and is set to 24 hours plus the store’s historyRetentionMs value.


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