Stream Processing with the Spring Framework Like You’ve Never Seen It Before
summary
Live-codes a movie-ratings pipeline that reads pipe-delimited files, generates Avro POJOs with a Maven plugin, and produces messages to Kafka using KafkaTemplate; topics are auto-created by Spring, Confluent provides Kafka + Schema Registry for local dev, and Spring Cloud Stream + Kafka Streams implement a topology that counts ratings, materializes a KTable using RocksDB changelog, joins movies with averages to emit rated movies — the demo runs end-to-end and shows messages flowing to the output topic. Spring Cloud Stream + Kafka Streams Avro + Schema Registry KTable materialized state
AI-written summary · about
chapters (24)
- 0:00Introduction
- 1:55What is Kafka
- 6:00How to use Avro
- 7:40Confluent
- 10:50Getting Data
- 12:00Producer
- 13:00Kafka Templates
- 13:45Kafka Configuration
- 14:30Producer Factory
- 15:35Config Map
- 16:10Bootstrap URL
- 17:20Kafka Config
- 18:20Kafka Topic Definition
- 19:10Kafka Topic Example
- 20:30Parser
- 21:10Kafka Topics
- 22:50Reading from Kafka
- 24:20Copying our method
- 25:30What is a template
- 28:10Stream confluence
- 29:00Stream confluence test
- 30:50Spring Code Stream
- 34:50Kafka Stream
- 42:20Readings
related talks
01h 11mBootiful Stream Processing!
43mEvent streaming applications with Kafka Streams, Spring Kafka and Actuator
01h 12mCloud Event Driven Architectures with Spring Cloud Stream 2.0
58mGame of Streams
38mWalking Through the Spring Stack for Apache Kafka
36mLiterate Stream Processing
33mKafka Microservices with Kafka plus Akka and Kafka Streams
01h 01mMigrating applications to serverless Apache Kafka + KSQL