Apache-Flink

Architecting Exactly-Once Semantics with Apache Flink Checkpoints

A deep dive into Flink’s checkpointing mechanism, fault-tolerant state management, and practical patterns for building reliable streaming pipelines.

Diagram of Apache Flink coordinator and sink operators exchanging pre-commit and commit calls during a checkpoint barrier.

Inside Apache Flink's Two-Phase Commit Sink: Exactly-Once Guarantees Across Sinks

How Apache Flink coordinates checkpoints with sink writers via a two-phase commit protocol to deliver end-to-end exactly-once guarantees across Kafka, filesystems, and databases.

Diagram of Flink checkpoint barriers flowing through a streaming pipeline with aligned state snapshots.

Inside Apache Flink's Checkpointing Algorithm: How Exactly-Once State Guarantees Survive Pipeline Failures

How Apache Flink’s distributed snapshot algorithm coordinates barriers across operators, persists state to durable storage, and recovers jobs after failure without losing or duplicating records.

Illustration of a data stream with timestamps and a watermark line.

Where Stream Processing Systems Draw the Line for Late Data

A deep dive into how stream engines decide what counts as late data, the mechanisms they expose, and best‑practice patterns for robust pipelines.

Illustration of a flowing data stream with timestamp markers.

How Stream Watermarks Define Event Time Progress

Watermarks are the backbone of event‑time handling in modern stream processors. This post explains their purpose, generation, and impact on windowing.