Friday, September 30, 2022

Emergent Chief


One of many frequent strategies utilized in peer-to-peer methods is to
order cluster nodes in keeping with their ‘age’. The oldest member of
the cluster performs the function of the coordinator for the cluster.
The coordinator is liable for deciding on membership modifications
in addition to making choices resembling the place
Mounted Partitions ought to be positioned
throughout cluster nodes.

To kind the cluster,
one of many cluster nodes acts as a seed node or an introducer node.
All of the cluster nodes be part of the cluster by contacting the seed node.

Each cluster node is configured with the seed node tackle.
When a cluster node is began, it tries to contact the seed node
to hitch the cluster.

class ClusterNode…

  MembershipService membershipService;
  public void begin(Config config) {
      this.membershipService =  new MembershipService(config.getListenAddress()); part of(config.getSeedAddress());

The seed node may very well be any of the cluster nodes. It is configured with its personal
tackle because the seed node tackle and is the primary node that’s began.
It instantly begins accepting requests. The age of the seed node is 1.

class MembershipService…

  Membership membership;
  public void be part of(InetAddressAndPort seedAddress) {
      int maxJoinAttempts = 5;
      for(int i = 0; i < maxJoinAttempts; i++){
          attempt {
          } catch (Exception e) {
              logger.information("Be part of try " + i + "from " + selfAddress + " to " + seedAddress + " failed. Retrying");
      throw new JoinFailedException("Unable to hitch the cluster after " + maxJoinAttempts + " makes an attempt");

  non-public void joinAttempt(InetAddressAndPort seedAddress) throws ExecutionException, TimeoutException {
      if (selfAddress.equals(seedAddress)) {
          int membershipVersion = 1;
          int age = 1;
          updateMembership(new Membership(membershipVersion, Arrays.asList(new Member(selfAddress, age, MemberStatus.JOINED))));
      lengthy id = this.messageId++;
      CompletableFuture<JoinResponse> future = new CompletableFuture<>();
      JoinRequest message = new JoinRequest(id, selfAddress);
      pendingRequests.put(id, future);
      community.ship(seedAddress, message);

      JoinResponse joinResponse = Uninterruptibles.getUninterruptibly(future, 5, TimeUnit.SECONDS);

  non-public void begin() {
      logger.information(selfAddress + " joined the cluster. Membership=" + membership);

  non-public void updateMembership(Membership membership) {
      this.membership  = membership;

There will be a couple of seed node. However seed nodes begin accepting
requests solely after they themselves be part of the cluster. Additionally the cluster
can be useful if the seed node is down, however no new nodes can be ready
so as to add to the cluster.

Non seed nodes then ship the be part of request to the seed node.
The seed node handles the be part of request by creating a brand new member report
and assigning its age.
It then updates its personal membership listing and sends messages to all of the
current members with the brand new membership listing.
It then waits to guarantee that the response is
returned from each node, however will finally return the be part of response
even when the response is delayed.

class MembershipService…

  public void handleJoinRequest(JoinRequest joinRequest) {

  non-public void handleNewJoin(JoinRequest joinRequest) {
      Checklist<Member> existingMembers = membership.getLiveMembers();
      ResultsCollector resultsCollector = broadcastMembershipUpdate(existingMembers);
      JoinResponse joinResponse = new JoinResponse(joinRequest.messageId, selfAddress, membership);
      resultsCollector.whenComplete((response, exception) -> {
          logger.information("Sending be part of response from " + selfAddress + " to " + joinRequest.from);
          community.ship(joinRequest.from, joinResponse);

class Membership…

  public Membership addNewMember(InetAddressAndPort tackle) {
      var newMembership = new ArrayList<>(liveMembers);
      int age = yongestMemberAge() + 1;
      newMembership.add(new Member(tackle, age, MemberStatus.JOINED));
      return new Membership(model + 1, newMembership, failedMembers);

  non-public int yongestMemberAge() {
      return -> m.age).max(Integer::examine).orElse(0);

If a node which was already a part of the cluster is attempting to rejoin
after a crash, the failure detector state associated to that member is

class MembershipService…

  non-public void handlePossibleRejoin(JoinRequest joinRequest) {
      if (membership.isFailed(joinRequest.from)) {
          //member rejoining
          logger.information(joinRequest.from  + " rejoining the cluster. Eradicating it from failed listing");

It is then added as a brand new member. Every member must be recognized
uniquely. It may be assigned a novel identifier at startup.
This then gives a degree of reference that makes it potential to
verify whether it is an current cluster node that’s rejoining.

The membership class maintains the listing of reside members in addition to
failed members. The members are moved from reside to failed listing
in the event that they cease sending HeartBeat as defined within the
failure detection part.

class Membership…

  public class Membership {
      Checklist<Member> liveMembers = new ArrayList<>();
      Checklist<Member> failedMembers = new ArrayList<>();
      public boolean isFailed(InetAddressAndPort tackle) {
          return -> m.tackle.equals(tackle));

Sending membership updates to all the prevailing members

Membership updates are despatched to all the opposite nodes concurrently.
The coordinator additionally wants to trace whether or not all of the members
efficiently obtained the updates.

A typical method is to ship a a method request to all nodes
and anticipate an acknowledgement message.
The cluster nodes ship acknowledgement messages to the coordinator
to verify receipt of the membership replace.
A ResultCollector object can monitor receipt of all of the
messages asynchronously, and is notified each time
an acknowledgement is obtained for a membership replace.
It completes its future as soon as the anticipated
acknowledgement messages are obtained.

class MembershipService…

  non-public ResultsCollector broadcastMembershipUpdate(Checklist<Member> existingMembers) {
      ResultsCollector resultsCollector = sendMembershipUpdateTo(existingMembers);
      resultsCollector.orTimeout(2, TimeUnit.SECONDS);
      return resultsCollector;

  Map<Lengthy, CompletableFuture> pendingRequests = new HashMap();
  non-public ResultsCollector sendMembershipUpdateTo(Checklist<Member> existingMembers) {
      var otherMembers = otherMembers(existingMembers);
      ResultsCollector collector = new ResultsCollector(otherMembers.dimension());
      if (otherMembers.dimension() == 0) {
          return collector;
      for (Member m : otherMembers) {
          lengthy id = this.messageId++;
          CompletableFuture<Message> future = new CompletableFuture();
          future.whenComplete((end result, exception)->{
              if (exception == null){
          pendingRequests.put(id, future);
          community.ship(m.tackle, new UpdateMembershipRequest(id, selfAddress, membership));
      return collector;

class MembershipService…

  non-public void handleResponse(Message message) {

  non-public void completePendingRequests(Message message) {
      CompletableFuture requestFuture = pendingRequests.get(message.messageId);
      if (requestFuture != null) {

class ResultsCollector…

  class ResultsCollector {
      int totalAcks;
      int receivedAcks;
      CompletableFuture future = new CompletableFuture();
      public ResultsCollector(int totalAcks) {
          this.totalAcks = totalAcks;
      public void ackReceived() {
          if (receivedAcks == totalAcks) {
      public void orTimeout(int time, TimeUnit unit) {
          future.orTimeout(time, unit);
      public void whenComplete(BiConsumer<? tremendous Object, ? tremendous Throwable> func) {
      public void full() {

To see how ResultCollector works, think about a cluster
with a set of nodes: let’s name them athens, byzantium and cyrene.
athens is appearing as a coordinator. When a brand new node – delphi –
sends a be part of request to athens, athens updates the membership and sends the updateMembership request
to byantium and cyrene. It additionally creates a ResultCollector object to trace
acknowledgements. It data every acknowledgement obtained
with ResultCollector. When it receives acknowledgements from each
byzantium and cyrene, it then responds to delphi.

Frameworks like Akka
use Gossip Dissemination and Gossip Convergence
to trace whether or not updates have reached all cluster nodes.

An instance state of affairs

Contemplate one other three nodes.
Once more, we’ll name them athens, byzantium and cyrene.
athens acts as a seed node; the opposite two nodes are configured as such.

When athens begins, it detects that it’s itself the seed node.
It instantly initializes the membership listing and begins
accepting requests.

When byzantium begins, it sends a be part of request to athens.
Observe that even when byzantium begins earlier than athens, it would preserve
attempting to ship be part of requests till it will possibly connect with athens.
Athens lastly provides byzantium to the membership listing and sends the
up to date membership listing to byzantium. As soon as byzantium receives
the response from athens, it will possibly begin accepting requests.

With all-to-all heartbeating, byzantium begins sending heartbeats
to athens, and athens sends heartbeat to byzantium.

cyrene begins subsequent. It sends be part of requests to athens.
Athens updates the membership listing and sends up to date membership
listing to byantium. It then sends the be part of response with
the membership listing to cyrene.

With all to all heartbeating, cyrene, athens and byzantium
all ship heartbeats to one another.

Dealing with lacking membership updates

It is potential that some cluster nodes miss membership updates.
There are two options to deal with this downside.

If all members are sending heartbeat to all different members,
the membership model quantity will be despatched as a part of the heartbeat.
The cluster node that handles the heartbeat can
then ask for the most recent membership.
Frameworks like Akka which use Gossip Dissemination
monitor convergence of the gossiped state.

class MembershipService…

  non-public void handleHeartbeatMessage(HeartbeatMessage message) {
      if (isCoordinator() && message.getMembershipVersion() < this.membership.getVersion()) {
          membership.getMember(message.from).ifPresent(member -> {
              logger.information("Membership model in " + selfAddress + "=" + this.membership.model + " and in " + message.from + "=" + message.getMembershipVersion());

              logger.information("Sending membership replace from " + selfAddress + " to " + message.from);

Within the above instance, if byzantium misses the membership replace
from athens, will probably be detected when byzantine sends the heartbeat
to athens. athens can then ship the most recent membership to byzantine.

Alternatively every cluster node can verify the lastest membership listing periodically,
– say each one second – with different cluster nodes.
If any of the nodes work out that their member listing is outdated,
it will possibly then ask for the most recent membership listing so it will possibly replace it.
To have the ability to examine membership lists, typically
a model quantity is maintained and incremented everytime
there’s a change.

Failure Detection

Every cluster additionally runs a failure detector to verify if
heartbeats are lacking from any of the cluster nodes.
In a easy case, all cluster nodes ship heartbeats to all the opposite nodes.
However solely the coordinator marks the nodes as failed and
communicates the up to date membership listing to all the opposite nodes.
This makes certain that not all nodes unilaterally deciding if
another nodes have failed. Hazelcast is an instance
of this implementation.

class MembershipService…

  non-public boolean isCoordinator() {
      Member coordinator = membership.getCoordinator();
      return coordinator.tackle.equals(selfAddress);

  TimeoutBasedFailureDetector<InetAddressAndPort> failureDetector
          = new TimeoutBasedFailureDetector<InetAddressAndPort>(Length.ofSeconds(2));

  non-public void checkFailedMembers(Checklist<Member> members) {
      if (isCoordinator()) {

      } else {
          //if failed member consists of coordinator, then verify if this node is the subsequent coordinator.

  void removeFailedMembers() {
      Checklist<Member> failedMembers = checkAndGetFailedMembers(membership.getLiveMembers());
      if (failedMembers.isEmpty()) {

Avoiding all-to-all heartbeating

All-to-all heartbeating just isn’t possible in giant clusters.
Sometimes every node will obtain heartbeats from
only some different nodes. If a failure is detected,
it is broadcasted to all the opposite nodes
together with the coordinator.

For instance in Akka a node ring is fashioned
by sorting community addresses and every cluster node sends
heartbeats to only some cluster nodes.
Ignite arranges all of the nodes within the cluster
in a hoop and every node sends heartbeat solely to the node subsequent
to it.
Hazelcast makes use of all-to-all heartbeat.

Any membership modifications, due to nodes being added or
node failures must be broadcast to all the opposite
cluster nodes. A node can join to each different node to
ship the required data.
Gossip Dissemination can be utilized
to broadcast this data.

Break up Mind State of affairs

Despite the fact that a single coordinator node decides when to
mark one other nodes as down, there isn’t any express leader-election
taking place to pick which node acts as a coordinator.
Each cluster node expects a heartbeat from the prevailing
coordinator node; if it would not get a heartbeat in time,
it will possibly then declare to be the coordinator and take away the prevailing
coordinator from the memberlist.

class MembershipService…

  non-public void claimLeadershipIfNeeded(Checklist<Member> members) {
      Checklist<Member> failedMembers = checkAndGetFailedMembers(members);
      if (!failedMembers.isEmpty() && isOlderThanAll(failedMembers)) {
          var newMembership = membership.failed(failedMembers);

  non-public boolean isOlderThanAll(Checklist<Member> failedMembers) {
      return -> m.age < thisMember().age);

  non-public Checklist<Member> checkAndGetFailedMembers(Checklist<Member> members) {
      Checklist<Member> failedMembers = members
              .filter(member -> !member.tackle.equals(selfAddress) && failureDetector.isMonitoring(member.tackle) && !failureDetector.isAlive(member.tackle))
              .map(member -> new Member(member.tackle, member.age, member.standing)).acquire(Collectors.toList());

          failureDetector.take away(member.tackle);
          logger.information(selfAddress + " marking " + member.tackle + " as DOWN");
      return failedMembers;

This will create a state of affairs the place there are two or extra subgroups
fashioned in an current cluster, every contemplating the others
to have failed. That is known as split-brain downside.

Contemplate a 5 node cluster, athens, byzantium, cyrene, delphi and euphesus.
If athens receives heartbeats from dephi and euphesus, however
stops getting heartbeats from byzantium, cyrene, it marks
each byzantium and cyrene as failed.

byzantium and cyrene may ship heartbeats to one another,
however cease receiving heartbeats from cyrene, dephi and euphesus.
byzantium being the second oldest member of the cluster,
then turns into the coordinator.
So two separate clusters are fashioned one with athens as
the coordinator and the opposite with byzantium because the coordinator.

Dealing with break up mind

One frequent technique to deal with break up mind situation is to
verify whether or not there are sufficient members to deal with any
shopper request, and reject the request if there
usually are not sufficient reside members. For instance,
Hazelcast means that you can configure
minimal cluster dimension to execute any shopper request.

public void handleClientRequest(Request request) {
    if (!hasMinimumRequiredSize()) {
        throw new NotEnoughMembersException("Requires minium 3 members to serve the request");

non-public boolean hasMinimumRequiredSize() {
    return membership.getLiveMembers().dimension() > 3;

The half which has nearly all of the nodes,
continues to function, however as defined within the Hazelcast
documentation, there’ll at all times be a
time window
during which this safety has but to return into impact.

The issue will be averted if cluster nodes are
not marked as down until it is assured that they
will not trigger break up mind.
For instance, Akka recommends
that you just don’t have nodes
marked as down
by means of the failure detector; you possibly can as a substitute use its
break up mind resolver.

Recovering from break up mind

The coordinator runs a periodic job to verify if it
can connect with the failed nodes.
If a connection will be established, it sends a particular
message indicating that it needs to set off a
break up mind merge.

If the receiving node is the coordinator of the subcluster,
it would verify to see if the cluster that’s initiating
the request is a part of the minority group. Whether it is,
it would ship a merge request. The coordinator of the minority group,
which receives the merge request, will then execute
the merge request on all of the nodes within the minority sub group.

class MembershipService…

  splitbrainCheckTask = taskScheduler.scheduleWithFixedDelay(() -> {
          1, 1, TimeUnit.SECONDS);

class MembershipService…

  non-public void searchOtherClusterGroups() {
      if (membership.getFailedMembers().isEmpty()) {
      Checklist<Member> allMembers = new ArrayList<>();
          if (isCoordinator()) {
          for (Member member : membership.getFailedMembers()) {
              logger.information("Sending SplitBrainJoinRequest to " + member.tackle);
              community.ship(member.tackle, new SplitBrainJoinRequest(messageId++, this.selfAddress, membership.model, membership.getLiveMembers().dimension()));

If the receiving node is the coordinator of the bulk subgroup, it asks the
sending coordinator node to merge with itself.

class MembershipService…

  non-public void handleSplitBrainJoinMessage(SplitBrainJoinRequest splitBrainJoinRequest) {
      logger.information(selfAddress + " Dealing with SplitBrainJoinRequest from " + splitBrainJoinRequest.from);
      if (!membership.isFailed(splitBrainJoinRequest.from)) {

      if (!isCoordinator()) {

      if(splitBrainJoinRequest.getMemberCount() < membership.getLiveMembers().dimension()) {
          //requesting node ought to be part of this cluster.
          logger.information(selfAddress + " Requesting " + splitBrainJoinRequest.from + " to rejoin the cluster");
          community.ship(splitBrainJoinRequest.from, new SplitBrainMergeMessage(splitBrainJoinRequest.messageId, selfAddress));

      } else {
          //we have to be part of the opposite cluster


  non-public void mergeWithOtherCluster(InetAddressAndPort otherClusterCoordinator) {
      handleMerge(new MergeMessage(messageId++, selfAddress, otherClusterCoordinator)); //provoke merge on this node.

  non-public void askAllLiveMembersToMergeWith(InetAddressAndPort mergeToAddress) {
      Checklist<Member> liveMembers = membership.getLiveMembers();
      for (Member m : liveMembers) {
          community.ship(m.tackle, new MergeMessage(messageId++, selfAddress, mergeToAddress));

Within the instance mentioned within the above part, when athens
can talk with byzantium, it would ask byzantium to merge
with itself.

The coordinator of the smaller subgroup,
then asks all of the cluster nodes
inside its group to set off a merge.
The merge operation shuts down and rejoins the cluster
nodes to the coordinator of the bigger group.

class MembershipService…

  non-public void handleMerge(MergeMessage mergeMessage) {
      logger.information(selfAddress + " Merging with " + mergeMessage.getMergeToAddress());
      //be part of the cluster once more by means of the opposite cluster's coordinator
      taskScheduler.execute(()-> {
          be part of(mergeMessage.getMergeToAddress());

Within the instance above, byzantium and cyrene shutdown and
rejoin athens to kind a full cluster once more.

Comparability with Chief and Followers

It is helpful to match this sample with that of
Chief and Followers. The leader-follower
setup, as utilized by patterns like Constant Core,
doesn’t operate until the chief is chosen
by operating an election. This ensures that the
Quorum of cluster nodes have
an settlement about who the chief is. Within the worst case
state of affairs, if an settlement is not reached, the system will
be unavailable to course of any requests.
In different phrases, it prefers consistency over availability.

The emergent chief, alternatively will at all times
have some cluster node appearing as a pacesetter for processing
shopper requests. On this case, availability is most popular
over consistency.



Please enter your comment!
Please enter your name here

Most Popular