An Apache Flink and Kotlin streaming architecture where online machine learning detects concept drift from machinery wear, controlled by a shadow mode router.

Examples from the book Stream Processing with Apache Flink ported to Kotlin, updated to current Flink APIs and built with Gradle after PyFlink lacked features.

Apache Kyuubi as a multi-tenant SQL gateway that provisions on-demand Spark, Flink and Trino engines, giving self-service analytics with central governance.

Flink Table API in Kotlin states the supplier statistics as a declarative windowed aggregation over a DataStream, with late rows routed by hand.

Flink DataStream API in Kotlin computes the same supplier statistics, using watermarks for event time and side outputs to collect late order events.

Kafka Streams in Kotlin aggregates Avro order events into tumbling window supplier statistics and handles late records with a custom extractor.

Avro and Schema Registry replace hand written JSON codecs in a Kotlin Kafka producer and consumer, with generated classes and graceful shutdown.

A Kotlin Kafka producer and consumer for order events, with custom JSON serialisers, admin helpers and a Gradle build, run on Factor House Local.

Apache Paimon, Fluss and Apache Iceberg compared as table layers for streaming and batch, then combined into one architecture with Flink and Spark.

Docker Compose runs a local Apache Flink cluster and SQL Client so the Ververica Flink SQL Cookbook recipes work without the Ververica Platform.