How-to: Deterministic replay with ReplayRecord and the data-driven clock

This guide shows how to replay events with an explicit wall-clock time so that your handlers see a deterministic time via getContext().getClock() during processing.

Key points:

• Publish a ReplayRecord which contains both the original event payload and a wallClockTime value to apply when processing.
• The event runner uses this time to drive the processor context clock for the corresponding event delivery.
• Handlers can read the time with getContext().getClock() and will observe the same values when the replay is repeated.
• The handler receives the event wrapped in the ReplayRecord and not the ReplayRecord itself.

Sample code

• Processor source: HandlerPipeServerBootExample.java
• Test node: HandlerPipeTest.java
• Complete how-to example: Replay Example

What it demonstrates:

• Booting the server with an InMemoryEventSource as an EventFeed.
• A handler that reads getContext().getClock() to capture the data-driven time.
• Publishing ReplayRecord objects through the source using the standard offer(...).
• Verifying that the observed times match the replayed timestamps.

Minimal example

• A handler that subscribes to a feed and writes the event and getContext().getClock() time to a sink:

public class ReplayCaptureHandler extends ObjectEventHandlerNode {
    private final String feedName;
    private MessageSink<String> sink;

    public ReplayCaptureHandler(String feedName) { this.feedName = feedName; }

    @ServiceRegistered
    public void wire(MessageSink<ReplayRecord> sink, String name) { this.sink = sink; }

    @Override
    public void start() { getContext().subscribeToNamedFeed(feedName); }

    @Override
    protected boolean handleEvent(Object event) {
        long time = getContext().getClock().getWallClockTime();
        sink.accept("event=" + event + ", time=" + time);
        return true;
    }
}

• Boot a server with an in-VM event source and publish ReplayRecord entries:

InMemoryEventSource<String> source = new InMemoryEventSource<>();
source.setName("replayFeed");
ReplayCaptureHandler handler = new ReplayCaptureHandler(source.getName());
InMemoryMessageSink sink = new InMemoryMessageSink();

// Build MongooseServerConfig with the event feed, processor, and sink (see full example below)

long t1 = 1_696_000_000_000L; // epoch millis
long t2 = t1 + 1234;
ReplayRecord r1 = new ReplayRecord();
r1.setEvent("alpha");
r1.setWallClockTime(t1);
ReplayRecord r2 = new ReplayRecord();
r2.setEvent("beta");
r2.setWallClockTime(t2);

// Publish with explicit replay times
source.offer(r1);
source.offer(r2);

The handler will emit lines like:

event=alpha, time=1696000000000
event=beta, time=1696000001234

Why the clock is data driven

When a ReplayRecord is processed, the event runner calls the event-to-invocation strategy with: (event, wallClockTime) . This sets the processor context clock to the supplied value for that event delivery. As a result, getContext().getClock() is deterministic with respect to the replay data. Re-running the same ReplayRecord stream will produce the same clock readings, ensuring reproducible behavior. The dispatcher unwraps the event in the ReplayRecord and publish this wrapped event to the handler not the ReplayRecord.

If you run the replay again with the same ReplayRecord inputs, your handler will see the same times. This makes tests and off-line analyses reproducible.