ahuang98 commented on code in PR #18987:
URL: https://github.com/apache/kafka/pull/18987#discussion_r1980407781
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raft/src/test/java/org/apache/kafka/raft/RaftEventSimulationTest.java:
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@@ -117,40 +125,101 @@ public class RaftEventSimulationTest {
void canElectInitialLeader(
@ForAll int seed,
@ForAll @IntRange(min = 1, max = 5) int numVoters,
- @ForAll @IntRange(min = 0, max = 5) int numObservers
+ @ForAll @IntRange(min = 0, max = 5) int numObservers,
+ @ForAll boolean withKip853
) {
Random random = new Random(seed);
- Cluster cluster = new Cluster(numVoters, numObservers, random);
+ Cluster cluster = new Cluster(numVoters, numObservers, random,
withKip853);
MessageRouter router = new MessageRouter(cluster);
EventScheduler scheduler = schedulerWithDefaultInvariants(cluster);
- cluster.startAll();
- schedulePolling(scheduler, cluster, 3, 5);
- scheduler.schedule(router::deliverAll, 0, 2, 1);
- scheduler.schedule(new SequentialAppendAction(cluster), 0, 2, 3);
- scheduler.runUntil(cluster::hasConsistentLeader);
- scheduler.runUntil(() -> cluster.allReachedHighWatermark(10));
+ initializeClusterAndStartAppending(cluster, router, scheduler, 2);
+ }
+
+ @Property(tries = 100, afterFailure = AfterFailureMode.SAMPLE_ONLY)
+ void canElectInitialLeaderAndAddVoter(
+ @ForAll int seed,
+ @ForAll @IntRange(min = 1, max = 5) int numVoters,
+ @ForAll @IntRange(min = 1, max = 5) int numObservers
+ ) {
+ Random random = new Random(seed);
+ Cluster cluster = new Cluster(numVoters, numObservers, random, true);
+ MessageRouter router = new MessageRouter(cluster);
+ EventScheduler scheduler = schedulerWithKip853Invariants(cluster);
+
+ initializeClusterAndStartAppending(cluster, router, scheduler, 10);
+ int firstObserverId = numVoters;
+ scheduler.schedule(new AddVoterAction(cluster,
cluster.running.get(firstObserverId)), 0, 5, 3);
+ scheduler.runUntil(() ->
cluster.leaderWithMaxEpoch().get().client.partitionState().lastVoterSet().size()
== numVoters + 1);
+ VoterSet latestVoterSet =
cluster.leaderWithMaxEpoch().get().client.partitionState().lastVoterSet();
+ scheduler.runUntil(() ->
cluster.allHaveLatestVoterSet(latestVoterSet));
+ }
+
+ @Property(tries = 100, afterFailure = AfterFailureMode.SAMPLE_ONLY)
+ void canAddAndRemoveVoters(
Review Comment:
> I remove a random node so that the tries property means we will remove a
leader with probability = 1/numVoters on each try.
which test will do this? this one just removes all observers and I see
another which partitions a voter (would lose leadership) then removes it
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