✳flâneur — a map of the web's best reading

Multi-Threaded Messaging with the Apache Kafka Consumer

confluent.io · 3,836 words · saved by 1 readers

Multithreading is “the ability of a central processing unit (CPU) (or a single core in a multi-core processor) to provide multiple threads of execution concurrently, supported by the operating system.” In situations where the work can be divided into smaller units, which can be run in parallel, without negative effects on data consistency, multithreading can be used to improve application performance. In Kafka topics, records are grouped into smaller units—partitions, which can be processed independently without compromising the correctness of the results and lays the foundations for parallel processing. This is usually achieved by scaling: using multiple consumers within the same group, each processing data from a subset of topic partitions and running in a single thread. For most use cases, reading and processing messages in a single thread is perfectly fine, so it’s not surprising that thread per consumer threading model is commonly used with the Apache Kafka® consumer. When process

Multi-Threaded Messaging with the Apache Kafka Consumer New in Confluent Cloud: Making Data & Pipelines Accessible for AI-Ready Streaming | Learn More Login Contact Sales Multithreading is “the ability of a central processing unit (CPU) (or a single core in a multi-core processor) to provide multiple threads of execution concurrently, supported by the operating system.” In situations where the work can be divided into smaller units, which can be run in parallel, without negative effects on data consistency, multithreading can be used to improve application performance. In Kafka topics, re

Explore this link on the map →

related reading