Ordering events to capture causality

In cases where there is no causal link between events, the lack of a total order is not a big problem, since concurrent events can be ordered arbitrarily. Some other cases are easy to handle: for example, when there are multiple updates of the same object, they can be totally ordered by routing all updates for a particular object ID to the same log partition. However, causal dependencies sometimes arise in more subtle ways (see also “Ordering and Causality” on page 339).

For example, consider a social networking service, and two users who were in a relationship but have just broken up. One of the users removes the other as a friend, and then sends a message to their remaining friends complaining about their ex-partner. The user’s intention is that their ex-partner should not see the rude message, since the message was sent after the friend status was revoked.

However, in a system that stores friendship status in one place and messages in another place, that ordering dependency between the unfriend event and the message- send event may be lost. If the causal dependency is not captured, a service that sends notifications about new messages may process the message-send event before the unfriend event, and thus incorrectly send a notification to the ex-partner.

In this example, the notifications are effectively a join between the messages and the friend list, making it related to the timing issues of joins that we discussed previously (see “Time-dependence of joins” on page 475). Unfortunately, there does not seem to be a simple answer to this problem [2, 3]. Starting points include:

  • • Logical timestamps can provide total ordering without coordination (see “Sequence Number Ordering” on page 343), so they may help in cases where total order broadcast is not feasible. However, they still require recipients to handle events that are delivered out of order, and they require additional metadata to be passed around.
  • • If you can log an event to record the state of the system that the user saw before making a decision, and give that event a unique identifier, then any later events can reference that event identifier in order to record the causal dependency [4]. We will return to this idea in “Reads are events too” on page 513.
  • • Conflict resolution algorithms (see “Automatic Conflict Resolution” on page 174) help with processing events that are delivered in an unexpected order. They are useful for maintaining state, but they do not help if actions have external side effects (such as sending a notification to a user).

Perhaps, over time, patterns for application development will emerge that allow causal dependencies to be captured efficiently, and derived state to be maintained correctly, without forcing all events to go through the bottleneck of total order broadcast.

 
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