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elasticsearch的zenDiscovery和master选举机制原理分析

作者:zziawan

这篇文章主要介绍了elasticsearch的zenDiscovery和master选举机制原理分析,有需要的朋友可以借鉴参考下,希望能够有所帮助,祝大家多多进步,早日升职加薪

前言

上一篇通过 ElectMasterService源码,分析了master选举的原理的大部分内容:master候选节点ID排序保证选举一致性及通过设置最小可见候选节点数目避免brain split。节点排序后选举只能保证局部一致性,如果发生节点接收到了错误的集群状态就会选举出错误的master,因此必须有其它措施来保证选举的一致性。这就是上一篇所提到的第二点:被选举的数量达到一定的数目同时自己也选举自己,这个节点才能成为master。这一点体现在zenDiscovery中,本篇将结合节点的发现过程进一步介绍master选举机制。

节点启动后首先启动join线程,join线程会寻找cluster的master节点,如果集群之前已经启动,并且运行良好,则试图连接集群的master节点,加入集群。否则(集群正在启动)选举master节点,如果自己被选为master,则向集群中其它节点发送一个集群状态更新的task,如果master是其它节点则试图加入该集群。

join的代码

private void innerJoinCluster() {
        DiscoveryNode masterNode = null;
        final Thread currentThread = Thread.currentThread();
     //一直阻塞直到找到master节点,在集群刚刚启动,或者集群master丢失的情况,这种阻塞能够保证集群一致性
        while (masterNode == null && joinThreadControl.joinThreadActive(currentThread)) {
            masterNode = findMaster();
        }
      //有可能自己会被选举为master(集群启动,或者加入时正在选举)
      if (clusterService.localNode().equals(masterNode)) {
      //如果本身是master,则需要向其它所有节点发送集群状态更新
            clusterService.submitStateUpdateTask("zen-disco-join (elected_as_master)", Priority.IMMEDIATE, new ProcessedClusterStateNonMasterUpdateTask() {
                @Override
                public ClusterState execute(ClusterState currentState) {
            //选举时错误的,之前的master状态良好,则不更新状态,仍旧使用之前状态。
                    if (currentState.nodes().masterNode() != null) {
                       return currentState;
                    }
                    DiscoveryNodes.Builder builder = new DiscoveryNodes.Builder(currentState.nodes()).masterNodeId(currentState.nodes().localNode().id());
                    // update the fact that we are the master...
                    ClusterBlocks clusterBlocks = ClusterBlocks.builder().blocks(currentState.blocks()).removeGlobalBlock(discoverySettings.getNoMasterBlock()).build();
                    currentState = ClusterState.builder(currentState).nodes(builder).blocks(clusterBlocks).build();
                    // eagerly run reroute to remove dead nodes from routing table
                    RoutingAllocation.Result result = allocationService.reroute(currentState);
                    return ClusterState.builder(currentState).routingResult(result).build();
                }
                @Override
                public void onFailure(String source, Throwable t) {
                    logger.error("unexpected failure during [{}]", t, source);
                    joinThreadControl.markThreadAsDoneAndStartNew(currentThread);
                }
                @Override
                public void clusterStateProcessed(String source, ClusterState oldState, ClusterState newState) {
                    if (newState.nodes().localNodeMaster()) {
                        // we only starts nodesFD if we are master (it may be that we received a cluster state while pinging)
                        joinThreadControl.markThreadAsDone(currentThread);
                        nodesFD.updateNodesAndPing(newState); // start the nodes FD
                    } else {
                        // if we're not a master it means another node published a cluster state while we were pinging
                        // make sure we go through another pinging round and actively join it
                        joinThreadControl.markThreadAsDoneAndStartNew(currentThread);
                    }
                    sendInitialStateEventIfNeeded();
                    long count = clusterJoinsCounter.incrementAndGet();
                    logger.trace("cluster joins counter set to [{}] (elected as master)", count);
                }
            });
        } else {
            // 找到的节点不是我,试图连接该master
            final boolean success = joinElectedMaster(masterNode);
            // finalize join through the cluster state update thread
            final DiscoveryNode finalMasterNode = masterNode;
            clusterService.submitStateUpdateTask("finalize_join (" + masterNode + ")", new ClusterStateNonMasterUpdateTask() {
                @Override
                public ClusterState execute(ClusterState currentState) throws Exception {
                    if (!success) {
                        // failed to join. Try again...
                        joinThreadControl.markThreadAsDoneAndStartNew(currentThread);
                        return currentState;
                    }
                    if (currentState.getNodes().masterNode() == null) {
                        // Post 1.3.0, the master should publish a new cluster state before acking our join request. we now should have
                        // a valid master.
                        logger.debug("no master node is set, despite of join request completing. retrying pings.");
                        joinThreadControl.markThreadAsDoneAndStartNew(currentThread);
                        return currentState;
                    }
                    if (!currentState.getNodes().masterNode().equals(finalMasterNode)) {
                        return joinThreadControl.stopRunningThreadAndRejoin(currentState, "master_switched_while_finalizing_join");
                    }
                    // Note: we do not have to start master fault detection here because it's set at {@link #handleNewClusterStateFromMaster }
                    // when the first cluster state arrives.
                    joinThreadControl.markThreadAsDone(currentThread);
                    return currentState;
                }
                @Override
                public void onFailure(String source, @Nullable Throwable t) {
                    logger.error("unexpected error while trying to finalize cluster join", t);
                    joinThreadControl.markThreadAsDoneAndStartNew(currentThread);
                }
            });
        }
    }

以上就是join的过程。zenDiscovery在启动时会启动一个join线程,这个线程调用了该方法。同时在节点离开,master丢失等情况下也会重启这一线程仍然运行join方法。

findMaster方法

这个方法体现了master选举的机制。代码如下:

private DiscoveryNode findMaster() {
      //ping集群中的节点
        ZenPing.PingResponse[] fullPingResponses = pingService.pingAndWait(pingTimeout);
        if (fullPingResponses == null) {return null;
        }// 过滤所得到的ping响应,虑除client节点,单纯的data节点
        List<ZenPing.PingResponse> pingResponses = Lists.newArrayList();
        for (ZenPing.PingResponse pingResponse : fullPingResponses) {
            DiscoveryNode node = pingResponse.node();
            if (masterElectionFilterClientNodes && (node.clientNode() || (!node.masterNode() && !node.dataNode()))) {
                // filter out the client node, which is a client node, or also one that is not data and not master (effectively, client)
            } else if (masterElectionFilterDataNodes && (!node.masterNode() && node.dataNode())) {
                // filter out data node that is not also master
            } else {
                pingResponses.add(pingResponse);
            }
        }
       final DiscoveryNode localNode = clusterService.localNode();
        List<DiscoveryNode> pingMasters = newArrayList();
     //获取所有ping响应中的master节点,如果master节点是节点本身则过滤掉。pingMasters列表结果要么为空(本节点是master)要么是同一个节点(出现不同节点则集群出现了问题
不过没关系,后面会进行选举)
        for (ZenPing.PingResponse pingResponse : pingResponses) {
            if (pingResponse.master() != null) {
                if (!localNode.equals(pingResponse.master())) {
                    pingMasters.add(pingResponse.master());
                }
            }
        }
        // nodes discovered during pinging
        Set<DiscoveryNode> activeNodes = Sets.newHashSet();
        // nodes discovered who has previously been part of the cluster and do not ping for the very first time
        Set<DiscoveryNode> joinedOnceActiveNodes = Sets.newHashSet();
        Version minimumPingVersion = localNode.version();
    for (ZenPing.PingResponse pingResponse : pingResponses) {
        activeNodes.add(pingResponse.node());
        minimumPingVersion = Version.smallest(pingResponse.node().version(), minimumPingVersion);
        if (pingResponse.hasJoinedOnce() != null && pingResponse.hasJoinedOnce()) {
          joinedOnceActiveNodes.add(pingResponse.node());
        }
    }
//本节点暂时是master也要加入候选节点进行选举
        if (localNode.masterNode()) {
            activeNodes.add(localNode);
            long joinsCounter = clusterJoinsCounter.get();
            if (joinsCounter > 0) {
                logger.trace("adding local node to the list of active nodes who has previously joined the cluster (joins counter is [{}})", joinsCounter);
                joinedOnceActiveNodes.add(localNode);
            }
        }
      //pingMasters为空,则本节点是master节点,
    if (pingMasters.isEmpty()) {
            if (electMaster.hasEnoughMasterNodes(activeNodes)) {//保证选举数量,说明有足够多的节点选举本节点为master,但是这还不够,本节点还需要再选举一次,如果
          本次选举节点仍旧是自己,那么本节点才能成为master。这里就体现了master选举的第二条原则。
                DiscoveryNode master = electMaster.electMaster(joinedOnceActiveNodes);
                if (master != null) {
                    return master;
                }
                return electMaster.electMaster(activeNodes);
            } else {
                // if we don't have enough master nodes, we bail, because there are not enough master to elect from
                logger.trace("not enough master nodes [{}]", activeNodes);
                return null;
            }
        } else {
        //pingMasters不为空(pingMasters列表中应该都是同一个节点),本节点没有被选举为master,那就接受之前的选举。
            return electMaster.electMaster(pingMasters);
        }
    }

上面的重点部分都做了标注,就不再分析。除了findMaster方法,还有一个方法也体现了master选举,那就是handleMasterGone。下面是它的部分代码,提交master丢失task部分,

clusterService.submitStateUpdateTask("zen-disco-master_failed (" + masterNode + ")", Priority.IMMEDIATE, new ProcessedClusterStateNonMasterUpdateTask() {           
       @Override
            public ClusterState execute(ClusterState currentState) {
                //获取到当前集群状态下的所有节点
                DiscoveryNodes discoveryNodes = DiscoveryNodes.builder(currentState.nodes())
                        // make sure the old master node, which has failed, is not part of the nodes we publish
                        .remove(masterNode.id())
                        .masterNodeId(null).build();
          //rejoin过程仍然是重复findMaster过程
          if (rejoin) {
                    return rejoin(ClusterState.builder(currentState).nodes(discoveryNodes).build(), "master left (reason = " + reason + ")");
                }
          //无法达到选举数量,进行findMaster过程
                if (!electMaster.hasEnoughMasterNodes(discoveryNodes)) {
                    return rejoin(ClusterState.builder(currentState).nodes(discoveryNodes).build(), "not enough master nodes after master left (reason = " + reason + ")");
                }
          //在当前集群状态下,如果候选节点数量达到预期数量,那么选举出来的节点一定是同一个节点,因为所有的节点看到的集群states是一致的
                final DiscoveryNode electedMaster = electMaster.electMaster(discoveryNodes); // elect master
                final DiscoveryNode localNode = currentState.nodes().localNode();
              ....
            }

从以上的代码可以看到master选举节点的应用场景,无论是findMaster还是handlemasterGone,他们都保证了选举一致性。那就是所选节点数量必须要达到一定的数量,否则不能认为选举成功,进入等待环境。如果当前节点被其它节点选举为master,仍然要进行选举一次以保证选举的一致性。这样在保证了选举数量同时对候选节点排序从而保证选举的一致性。

发现和加入集群是zenDiscovery的主要功能,当然它还有一些其它功能,如处理节点离开(handleLeaveRequest),处理master发送的最小clustersates(handleNewClusterStateFromMaster)等功能。这里就不一一介绍,有兴趣请参考相关源码。

总结

本节结合zenDiscovery,分析了master选举的另外一部分内容。同时zenDiscovery是节点发现集群功能的集合,它主要功能是发现(选举)出集群的master节点,并试图加入集群。同时如果 本机是master还会处理节点的离开和节点丢失,如果不是master则会处理来自master的节点状态更新。

以上就是elasticsearch的zenDiscovery和master选举机制原理分析的详细内容,更多关于elasticsearch的zenDiscovery和master选举机制的资料请关注脚本之家其它相关文章!

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