# Commits and Delivery Semantics — Apache Kafka: Event Streaming from Basics to Production

Source: https://www.geekswithgeeks.com/en/kafka/kc-delivery-semantics

> Choose between at-most-once, at-least-once and exactly-once processing.

## When you commit decides what can go wrong

If you **commit before processing**, a crash can lose records (**at-most-once**). If you **process, then commit**, a crash can reprocess some records (**at-least-once**), which is the usual default and requires your processing to be **idempotent** or de-duplicated. **Exactly-once** results need extra machinery (transactions, or an idempotent sink using the record's key or offset). Turn off auto-commit for important work and commit after the side effect succeeds, either synchronously or in batches.

## A manual-commit consumer loop (illustrative)

Commit only after the database write succeeds. If the process dies in between, the record is read again, so `save_order` must tolerate duplicates (for example `INSERT ... ON CONFLICT DO NOTHING`).

```python
from confluent_kafka import Consumer

c = Consumer({"bootstrap.servers": "localhost:9092", "group.id": "billing",
              "enable.auto.commit": False, "auto.offset.reset": "earliest"})
c.subscribe(["orders"])
try:
    while True:
        msg = c.poll(1.0)
        if msg is None: continue
        if msg.error(): raise RuntimeError(msg.error())
        save_order(msg.key(), msg.value())      # idempotent write
        c.commit(message=msg)                   # commit AFTER success
finally:
    c.close()
```

## Design for duplicates

Even with careful commits, retries and rebalances can deliver a record twice. Use a natural unique key (such as an order ID) so repeating the same record has no extra effect.

**Quiz:** Which order gives at-least-once processing?

- [ ] Commit twice
- [ ] Commit the offset, then process
- [ ] Never commit
- [x] Process the record, then commit the offset

*Answer:* Process the record, then commit the offset. A crash between processing and commit causes a re-read, never a loss.