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Distributed Time

Hydroflow does not embed a particular notion of distributed time, but instead provides primitives for you to implement one of many possible distributed time models. If you're a distributed systems aficionado, you might be interested to read this chapter to learn about how Hydroflow's time model compares to classical distributed time models.

Lamport Time​

Lamport's paper on Time, Clocks, and the Ordering of Events in a Distributed System provides a classical definition of time in a distributed system. In that paper, each single-threaded process has a sequential clock (a so-called Lamport Clock). The clock in a process advances by one unit of time for each event that the process observes. Between events, the clock is frozen and the process does local computation.

In addition, to maintain Lamport Clocks, each process stamps its outbound messages with the current clock value, and begins each "tick" by advancing its local clock to the larger of

  • its current clock value and
  • the largest clock value of any message it received.

The way that Lamport clocks jump ahead provides a desirable property: the timestamps provide a reasonable notion of what events happen-before other events in a distributed system. Lamport timestamps track not only the order of events on a single node, they also ensure that the timestamps on events reflect distributed ordering. Suppose that node source wants to send a message to node dest, and node source has current clock value T_source. The events that precede that message on node source have smaller timestamps. In addition, consider an event at node dest that follows the receipt of that message. That event must have a timestamp greater than T_source by Lamport's advancing rule above. Hence all the events on node source that preceded the sending of the message have lower timestamps than the events on node dest following the receipt of the message. This is Lamport's distributed "happens-before" relation, and the Lamport clock capture that relation.

Hydroflow Time​

As a built-in primitive, Hydroflow defines time only for a single transducer, as a sequence of consecutive ticks without any gaps.

Thus the main difference between Hydroflow events and Lamport events are:

  1. Batched Events: Hydroflow treats the ingestion of a batch of multiple inbound events as a single tick. TODO: is it possible to limit batch size to 1?
  2. Fixpoints between Events: Hydroflow requires a fixpoint computation to complete between ticks.
  3. Consecutive Ticks: the built-in clock primitive in Hydroflow always advances sequentially and cannot skip a tick like the Lamport clock does.

Implementing Distributed Time in Hydroflow​

Although Lamport clocks are not built into Hydroflow, it is straightforward to implement them in Hydroflow. Alternatively, one can implement more sophisticated distributed clocks like vector clocks in Hydroflow instead. By leaving this decision to the user, Hydroflow can be used in a variety of distributed time models.

TODO: add example of implementing Lamport clocks?.