MQTT---HiveMQ源码详解(十七)Cluster-Consistent Hashing Ring & Node Lifecycle

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源博客地址:http://blog.csdn.net/pipinet123


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Consistent Hashing Ring

基本上只要做Cluster,都会使用到一致性Hash环,具体作用此处就不细讲,我们只了解HiveMQ怎么用它,怎么实现它,这样实现能够带来什么好处。

  • HiveMQ没有Master/Slave,它只由JGroup View(详情请查阅JGroup)第一个node作为Coordinator,这样就可以达到一个node也可以做集群(虽然这样的集群没有什么卵用)。

  • HiveMQ采用两个一致性Hash环,来解决脑裂问题,以及脑裂后merge的问题。

  • 每个node 500个虚拟节点,来增加node变化带来的动荡问题。

  • Primary环:排除joining的node,即只添加RUNNING状态的node。

  • Minority环:包含joining的node,即添加JOINING、RUNNING、MERGING状态的node。

  • 它的hash算法由net.openhft.hashing.LongHashFunction.xx_r39()提供

ConsistentHashingRing源码

相对来说比较简单,我就不一行一行写注释了,网上针对一致性hash环实现各种版本到处都是,详细讲解也到处都是。

@Singletonpublic class ConsistentHashingRing {    private static final Logger LOGGER = LoggerFactory.getLogger(ConsistentHashingRing.class);    private final String name;    public static final int NODE_BUCKET_COUNT = 500;    private final LongHashFunction hashFunction;    private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock(true);    @VisibleForTesting    final NavigableMap<Long, String> buckets;    @VisibleForTesting    final ConcurrentHashMap<String, String> bucketNodes = new ConcurrentHashMap<>();    final Set<String> nodes = Sets.newConcurrentHashSet();    public ConsistentHashingRing(String name, LongHashFunction hashFunction) {        this.name = name;        this.buckets = new ConcurrentSkipListMap();        this.hashFunction = hashFunction;    }    public void add(@NotNull String node) {        Preconditions.checkNotNull(node, "Name must not be null");        LOGGER.trace("Add node {} to the {}.", node, this.name);        Lock lock = this.readWriteLock.writeLock();        lock.lock();        try {            for (int bucketIndex = 0; bucketIndex < NODE_BUCKET_COUNT; bucketIndex++) {                long bucketHash = this.hashFunction.hashChars(node + bucketIndex);                if (this.buckets.containsKey(bucketHash)) {                    if (this.buckets.get(bucketHash).compareTo(node + 1) > 0) {                        this.buckets.put(bucketHash, node + bucketIndex);                        this.nodes.add(node);                        this.bucketNodes.put(node + bucketIndex, node);                    }                } else {                    this.buckets.put(bucketHash, node + bucketIndex);                    this.nodes.add(node);                    this.bucketNodes.put(node + bucketIndex, node);                }            }        } finally {            lock.unlock();        }    }    public void remove(@NotNull String node) {        Preconditions.checkNotNull(node, "Name must not be null");        LOGGER.trace("Remove node {} from the {}.", node, this.name);        Lock lock = this.readWriteLock.writeLock();        lock.lock();        try {            for (int bucketIndex = 0; bucketIndex < NODE_BUCKET_COUNT; bucketIndex++) {                long bucketHash = this.hashFunction.hashChars(node + bucketIndex);                this.buckets.remove(bucketHash);                this.bucketNodes.remove(node + bucketIndex);            }            this.nodes.remove(node);        } finally {            lock.unlock();        }    }    public Set<String> getReplicaNodes(@NotNull String key, int replicateCount) {        Preconditions.checkNotNull(key, "key must not be null");        int nodeCount = this.nodes.size();        if (replicateCount > nodeCount - 1) {            LOGGER.trace("There are not enough buckets in the consistent hash ring for {} replicas.", replicateCount);            replicateCount = nodeCount - 1;        }        String bucket = getBucket(key);        long bucketHash = this.hashFunction.hashChars(bucket);        Lock lock = this.readWriteLock.readLock();        lock.lock();        Set<String> buckets = new HashSet<>();        try {            for (Map.Entry<Long, String> entry = this.buckets.higherEntry(bucketHash);                 buckets.size() < replicateCount;                 entry = this.buckets.higherEntry(entry.getKey())) {                if (entry == null) {                    entry = this.buckets.firstEntry();                }                if (!this.bucketNodes.get(entry.getValue()).equals(this.bucketNodes.get(bucket))) {                    buckets.add(this.bucketNodes.get(entry.getValue()));                }            }            return buckets;        } finally {            lock.unlock();        }    }    public Set<String> getNodes() {        ImmutableSet.Builder<String> builder = ImmutableSet.builder();        Lock lock = this.readWriteLock.readLock();        lock.lock();        try {            return builder.addAll(this.nodes).build();        } finally {            lock.unlock();        }    }    public String getBucket(@NotNull String key) {        Preconditions.checkNotNull(key, "key must not be null");        if (this.buckets.isEmpty()) {            throw new IllegalStateException("Consistent hash ring is empty.");        }        long keyHash = this.hashFunction.hashChars(key);        Lock lock = this.readWriteLock.readLock();        lock.lock();        try {            Map.Entry<Long, String> entry = this.buckets.ceilingEntry(keyHash);            if (entry != null) {                return entry.getValue();            }            return this.buckets.ceilingEntry(Long.MIN_VALUE).getValue();        } finally {            lock.unlock();        }    }    public String getNode(@NotNull String key) {        Preconditions.checkNotNull(key, "key must not be null");        if (this.buckets.isEmpty()) {            throw new IllegalStateException("Consistent hash ring is empty.");        }        long keyHash = this.hashFunction.hashChars(key);        Lock lock = this.readWriteLock.readLock();        lock.lock();        try {            Map.Entry<Long, String> entry = this.buckets.ceilingEntry(keyHash);            if (entry != null) {                return this.bucketNodes.get(entry.getValue());            }            return this.bucketNodes.get(this.buckets.ceilingEntry(Long.MIN_VALUE).getValue());        } finally {            lock.unlock();        }    }}

Node Lifecycle

其实了解了上面HiveMQ Cluster的基础之后,再来看node的生命周期,就是一件简单的事情了。

废话少说,我们直接上状态变化图。

这里写图片描述

各种状态简介

UNKNOWN

当JGroup通知新的node连接,但在本地不存在,则该node状态标记为UNKNOWN

NOT_JOINED

当node连接上JGroup后,若它不是唯一的node,则它将自己主动标记为NOT_JOINED

JOINING

当node将自己的状态更新至Cluster完成后,它将自己主动标记为JOINING

MERGE_MINORITY

当脑裂后与Coordinator在同组的其他node都将被标记为MERGE_MINORITY;或者加入Primary Group失败后它将自己主动标记为MERGE_MINORITY

MERGING

MERGE_MINORITY会一直去尝试主动将自己标记为MERGING

RUNNING

当MERGING成功后,node将会进行Replicate操作,当Replicate操作完成,就主动将自己标记为RUNNING

SHUTTING_DOWN/SHUTDOWN_FINISHED/DEAD

这三种状态在源码中未被使用,但HiveMQ还这样定义,或许是保留吧,反正博主未搞懂,不过不重要,不懂就算了,^_^。

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