Kafka Streams applications can add extra load to the Kafka cluster even though stream processing doesn't take place on the Kafka cluster itself. Which of the following increase the load on the…

The correct answer is A. Internal topics C. Changelog topics for local state stores. Kafka Streams automatically creates internal topics (such as those for repartitioning during stream transformations or joins) to manage data shuffling across tasks. These topics reside on the Kafka brokers, consuming storage, generating replication traffic, and increasing…

Apache Kafka Fundamentals

Question

Kafka Streams applications can add extra load to the Kafka cluster even though stream processing doesn't take place on the Kafka cluster itself. Which of the following increase the load on the brokers based on stream processing? (Choose two.)

Options

AInternal topics
BNumber of connectors
CChangelog topics for local state stores
DZookeeper ephemeral nodes

How the community answered

(55 responses)

A
84% (46)
B
5% (3)
D
11% (6)

Explanation

Kafka Streams automatically creates internal topics (such as those for repartitioning during stream transformations or joins) to manage data shuffling across tasks. These topics reside on the Kafka brokers, consuming storage, generating replication traffic, and increasing broker CPU/network load for handling produce/fetch requests. Changelog Topics for Local State Stores Stateful operations like aggregations or windowed computations use local RocksDB state stores, backed by changelog topics on the brokers. These topics log all state changes, creating continuous write/read traffic and compaction load on brokers as Streams instances update their local state from these topics.

Topics

#Kafka Streams#internal topics#changelog topics#broker load

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