#streaming
7 posts.
Why Rednote Moved from Kafka to Fluss: Lessons from a Real-Time Indexing Migration
A close look at the read amplification, historical replay bottleneck, Fluss architecture, results, and migration discipline in Rednote's real-time indexing path.
Keep Late Events from Overwriting Current State: Fluss Versioned Merge Engine
Use Apache Fluss Versioned Merge Engine to keep retries and late arrivals from replacing current state with an older event, with a runnable Flink SQL example.
What Your Sensor Event Is Missing: Enrich It with fluss-go
Create sensor-metadata and sensor-reading tables with fluss-go beta.10, then scan events and enrich them with current state from a Primary Key Table.
One Connection, One Table per Thread: Apache Fluss Java Client
Read and write the Flink Quickstart's Primary Key and Log Tables with the Apache Fluss 0.9.1 Java Client, starting from object lifecycles.
Your First Apache Fluss Run: What the Flink Quickstart Shows
Connect Apache Fluss to Flink in a local exercise environment, then use Flink SQL to examine its catalog, table models, primary-key reads, and updates.
What Is Apache Fluss? A Streaming Lakehouse Between Kafka, Flink, and Iceberg
Understand Apache Fluss by role: how it differs from Kafka, Flink, and Iceberg, and how its Log Tables, Primary Key Tables, and shared metadata connect real-time streams to a lakehouse.
Why Turn Immutable YAML Logs into Full Objects?
A practical look at why stream/event-based YAML processing can be a better fit than building a full DOM or object tree when high-volume YAML logs only need filtering.