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  1. 22:41Note however that this means that if say t2 is greater than t1 this means we keep v2 which was written by client2.
  2. 22:48And we simply discard v1.
  3. 22:52So value v1 is simply gone.
  4. 22:52So we're not even storing that value anywhere.
  5. 22:56It simply gets overwritten and forgotten.
  6. 24:05But if we have two concurrent updates then we will keep both of them.
  7. 24:09And so in this case now there's not a single value attached to the key x.
  8. 24:13But there could be multiple values.
  9. 24:13In this case v1 and v2.
  10. 24:17And so in this case we can give those two values back to the application.
  11. 24:22And the application can then resolve this.

Notes

  • Last writer wins discards data by overwriting values with lower timestamps and forgetting them entirely.
  • When concurrent updates are detected using vector clocks, multiple values can be kept for a single key and returned to the application for conflict resolution.

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When vector clocks detect concurrent updates to the same key, what can an application do to avoid losing data?

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Distributed Systems 5.1: Replication

Martin Kleppmann, YouTube, CC BY

Timestamp choice in replication

  • Last writer wins is a resolution policy where the value with the higher timestamp is kept and lower timestamps are overwritten.

  • Vector clocks are incomparable when generated for concurrent operations, allowing detection of concurrent updates.

  • An application can have explicit logic for conflict resolution to combine information from concurrent updates into a single value and avoid losing data.

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When vector clocks detect concurrent updates to the same key, what can an application do to avoid losing data?

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