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本文主要研究一下rocketmq5的顺序消息的队列选择

SendMessageActivity

proxy/src/main/java/org/apache/rocketmq/proxy/grpc/v2/producer/SendMessageActivity.java

public class SendMessageActivity extends AbstractMessingActivity {

    public SendMessageActivity(MessagingProcessor messagingProcessor,
        GrpcClientSettingsManager grpcClientSettingsManager, GrpcChannelManager grpcChannelManager) {
        super(messagingProcessor, grpcClientSettingsManager, grpcChannelManager);
    }

    public CompletableFuture<SendMessageResponse> sendMessage(ProxyContext ctx, SendMessageRequest request) {
        CompletableFuture<SendMessageResponse> future = new CompletableFuture<>();

        try {
            if (request.getMessagesCount() <= 0) {
                throw new GrpcProxyException(Code.MESSAGE_CORRUPTED, "no message to send");
            }

            List<apache.rocketmq.v2.Message> messageList = request.getMessagesList();
            apache.rocketmq.v2.Message message = messageList.get(0);
            Resource topic = message.getTopic();
            validateTopic(topic);

            future = this.messagingProcessor.sendMessage(
                ctx,
                new SendMessageQueueSelector(request),
                topic.getName(),
                buildSysFlag(message),
                buildMessage(ctx, request.getMessagesList(), topic)
            ).thenApply(result -> convertToSendMessageResponse(ctx, request, result));
        } catch (Throwable t) {
            future.completeExceptionally(t);
        }
        return future;
    }

    //......
}    

SendMessageActivity继承了AbstractMessingActivity，其sendMessage方法通过messagingProcessor.sendMessage进行消息发送，其传递的QueueSelector参数为new SendMessageQueueSelector(request)

SendMessageQueueSelector

    protected static class SendMessageQueueSelector implements QueueSelector {

        private final SendMessageRequest request;

        public SendMessageQueueSelector(SendMessageRequest request) {
            this.request = request;
        }

        @Override
        public AddressableMessageQueue select(ProxyContext ctx, MessageQueueView messageQueueView) {
            try {
                apache.rocketmq.v2.Message message = request.getMessages(0);
                String shardingKey = null;
                if (request.getMessagesCount() == 1) {
                    shardingKey = message.getSystemProperties().getMessageGroup();
                }
                AddressableMessageQueue targetMessageQueue;
                if (StringUtils.isNotEmpty(shardingKey)) {
                    // With shardingKey
                    List<AddressableMessageQueue> writeQueues = messageQueueView.getWriteSelector().getQueues();
                    int bucket = Hashing.consistentHash(shardingKey.hashCode(), writeQueues.size());
                    targetMessageQueue = writeQueues.get(bucket);
                } else {
                    targetMessageQueue = messageQueueView.getWriteSelector().selectOneByPipeline(false);
                }
                return targetMessageQueue;
            } catch (Exception e) {
                return null;
            }
        }
    }

SendMessageQueueSelector实现了QueueSelector接口，其select方法先获取系统属性中的messageGroup作为shardingKey，若该值不为空则通过Hashing.consistentHash(shardingKey.hashCode(), writeQueues.size())进行hash，然后取writeQueues.get(bucket)作为targetMessageQueue；若shardingKey为空则通过messageQueueView.getWriteSelector().selectOneByPipeline(false)来选择targetMessageQueue

Hashing.consistentHash

com/google/common/hash/Hashing.java

  /**
   * Assigns to {@code input} a "bucket" in the range {@code [0, buckets)}, in a uniform manner that
   * minimizes the need for remapping as {@code buckets} grows. That is, {@code consistentHash(h,
   * n)} equals:
   *
   * <ul>
   *   <li>{@code n - 1}, with approximate probability {@code 1/n}
   *   <li>{@code consistentHash(h, n - 1)}, otherwise (probability {@code 1 - 1/n})
   * </ul>
   *
   * <p>This method is suitable for the common use case of dividing work among buckets that meet the
   * following conditions:
   *
   * <ul>
   *   <li>You want to assign the same fraction of inputs to each bucket.
   *   <li>When you reduce the number of buckets, you can accept that the most recently added
   *       buckets will be removed first. More concretely, if you are dividing traffic among tasks,
   *       you can decrease the number of tasks from 15 and 10, killing off the final 5 tasks, and
   *       {@code consistentHash} will handle it. If, however, you are dividing traffic among
   *       servers {@code alpha}, {@code bravo}, and {@code charlie} and you occasionally need to
   *       take each of the servers offline, {@code consistentHash} will be a poor fit: It provides
   *       no way for you to specify which of the three buckets is disappearing. Thus, if your
   *       buckets change from {@code [alpha, bravo, charlie]} to {@code [bravo, charlie]}, it will
   *       assign all the old {@code alpha} traffic to {@code bravo} and all the old {@code bravo}
   *       traffic to {@code charlie}, rather than letting {@code bravo} keep its traffic.
   * </ul>
   *
   * <p>See the <a href="http://en.wikipedia.org/wiki/Consistent_hashing">Wikipedia article on
   * consistent hashing</a> for more information.
   */
  public static int consistentHash(long input, int buckets) {
    checkArgument(buckets > 0, "buckets must be positive: %s", buckets);
    LinearCongruentialGenerator generator = new LinearCongruentialGenerator(input);
    int candidate = 0;
    int next;

    // Jump from bucket to bucket until we go out of range
    while (true) {
      next = (int) ((candidate + 1) / generator.nextDouble());
      if (next >= 0 && next < buckets) {
        candidate = next;
      } else {
        return candidate;
      }
    }
  }

guava的consistentHash使用LinearCongruentialGenerator来生成double

小结

rocketmq5的消息消息的队列选择是在proxy模块中，它根据messageGroup使用Hashing.consistentHash(shardingKey.hashCode(), writeQueues.size())来选择writeQueues的下标。