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Episode 03 / Pipelines

Full Refresh vs Incremental Load

Full refresh is simple and easier to trust while logic is still changing, but that simplicity gets expensive as data grows. This sketch is the checklist I use before moving into incremental loads: checkpoint, watermark, late updates, dedup, and merge safety.

Data Sketch Episode 3: Full Refresh vs Incremental Load

Reading the sketch

  1. Full refresh fits simpler loads

    It works well with simple logic, infrequent updates, and rebuild costs that remain acceptable.

  2. Full refresh needs fewer controls

    A pipeline can rebuild without a reliable watermark or upsert support.

  3. Incremental load fits growing workloads

    It becomes useful when data volume and refresh cost make full rebuilds too slow.

  4. Incremental load needs reliable state

    The pipeline needs a dependable watermark and a way to handle upserts.

  5. Late updates affect the decision

    Frequent late updates add another constraint to incremental processing.

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