四、RocketMQ案例（一）

作者: 恨别A鸟惊心 | 来源:发表于2019-03-31 10:54 被阅读0次

1、订单消息

RocketMQ使用FIFO顺序提供有序消息。

以下示例演示了发送/接收全局和分区排序的消息。

发送消息示例代码

public class OrderedProducer {
    public static void main(String[] args) throws Exception {
        //Instantiate with a producer group name.
        DefaultMQProducer producer = new DefaultMQProducer("example_group_name");
        // Specify name server addresses.
        producer.setNamesrvAddr("192.168.247.132:9876");
        //Launch the instance.
        producer.start();
        String[] tags = new String[] {"TagA", "TagB", "TagC", "TagD", "TagE"};
        for (int i = 0; i < 100; i++) {
            int orderId = i % 10;
            //Create a message instance, specifying topic, tag and message body.
            Message msg = new Message("TopicTestjjj", tags[i % tags.length], "KEY" + i,
                    ("Hello RocketMQ " + i).getBytes(RemotingHelper.DEFAULT_CHARSET));
            SendResult sendResult = producer.send(msg, new MessageQueueSelector() {
            @Override
            public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
                Integer id = (Integer) arg;
                int index = id % mqs.size();
                return mqs.get(index);
            }
            }, orderId);

            System.out.printf("%s%n", sendResult);
        }
        //server shutdown
        producer.shutdown();
    }
}

订阅消息示例代码


public class OrderedConsumer {
    public static void main(String[] args) throws Exception {
        DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("example_group_name");
        consumer.setNamesrvAddr("192.168.247.132:9876");
        consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);

        consumer.subscribe("TopicTest", "TagA || TagC || TagD");

        consumer.registerMessageListener(new MessageListenerOrderly() {

            AtomicLong consumeTimes = new AtomicLong(0);

            public ConsumeOrderlyStatus consumeMessage(List<MessageExt> msgs,
                                                       ConsumeOrderlyContext context) {
                context.setAutoCommit(false);
                System.out.printf(Thread.currentThread().getName() + " Receive New Messages: " + msgs + "%n");
                this.consumeTimes.incrementAndGet();
                if ((this.consumeTimes.get() % 2) == 0) {
                    return ConsumeOrderlyStatus.SUCCESS;
                } else if ((this.consumeTimes.get() % 3) == 0) {
                    return ConsumeOrderlyStatus.ROLLBACK;
                } else if ((this.consumeTimes.get() % 4) == 0) {
                    return ConsumeOrderlyStatus.COMMIT;
                } else if ((this.consumeTimes.get() % 5) == 0) {
                    context.setSuspendCurrentQueueTimeMillis(3000);
                    return ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT;
                }
                return ConsumeOrderlyStatus.SUCCESS;

            }
        });

        consumer.start();

        System.out.printf("Consumer Started.%n");
    }
}

2、Broadcasting 广播消息

什么是Broadcasting

Broadcasting正在向主题的所有订阅者发送消息。如果您希望所有订阅者都收到有关主题的消息，则Broadcasting是一个不错的选择。

Producer example

public class BroadcastProducer {
    public static void main(String[] args) throws Exception {
        DefaultMQProducer producer = new DefaultMQProducer("ProducerGroupName");
        producer.setNamesrvAddr("192.168.247.132:9876");
        producer.start();

        for (int i = 0; i < 100; i++){
            Message msg = new Message("TopicTest",
                "TagA",
                "OrderID188",
                "Hello world".getBytes(RemotingHelper.DEFAULT_CHARSET));
            SendResult sendResult = producer.send(msg);
            System.out.printf("%s%n", sendResult);
        }
        producer.shutdown();
    }
}

消费者的例子

public class BroadcastConsumer {
    public static void main(String[] args) throws Exception {
        DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("example_group_name");
        consumer.setNamesrvAddr("192.168.247.132:9876");
        consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);

        //set to broadcast mode
        consumer.setMessageModel(MessageModel.BROADCASTING);

        consumer.subscribe("TopicTest", "TagA || TagC || TagD");

        consumer.registerMessageListener(new MessageListenerConcurrently() {

            @Override
            public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> msgs,
                ConsumeConcurrentlyContext context) {
                System.out.printf(Thread.currentThread().getName() + " Receive New Messages: " + msgs + "%n");
                return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
            }
        });

        consumer.start();
        System.out.printf("Broadcast Consumer Started.%n");
    }
}

3、Schedule example 计划消息案例

什么是Schedule信息？

Schedule消息与普通消息的不同之处在于，它们将在指定的时间之后发送。

应用

启动consumer以等待传入的订阅消息

```
 import org.apache.rocketmq.client.consumer.DefaultMQPushConsumer;
 import org.apache.rocketmq.client.consumer.listener.ConsumeConcurrentlyContext;
 import org.apache.rocketmq.client.consumer.listener.ConsumeConcurrentlyStatus;
 import org.apache.rocketmq.client.consumer.listener.MessageListenerConcurrently;
 import org.apache.rocketmq.common.message.MessageExt;
 import java.util.List;

 public class ScheduledMessageConsumer {

     public static void main(String[] args) throws Exception {
         // Instantiate message consumer
         DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("ExampleConsumer");
          consumer.setNamesrvAddr("192.168.247.132:9876");
         // Subscribe topics
         consumer.subscribe("TestTopic", "*");
         // Register message listener
         consumer.registerMessageListener(new MessageListenerConcurrently() {
             @Override
             public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> messages, ConsumeConcurrentlyContext context) {
                 for (MessageExt message : messages) {
                     // Print approximate delay time period
                     System.out.println("Receive message[msgId=" + message.getMsgId() + "] "
                             + (System.currentTimeMillis() - message.getStoreTimestamp()) + "ms later");
                 }
                 return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
             }
         });
         // Launch consumer
         consumer.start();
     }
 }

```

发送预定的消息

```
 import org.apache.rocketmq.client.producer.DefaultMQProducer;
 import org.apache.rocketmq.common.message.Message;

 public class ScheduledMessageProducer {

     public static void main(String[] args) throws Exception {
         // Instantiate a producer to send scheduled messages
         DefaultMQProducer producer = new DefaultMQProducer("ExampleProducerGroup");
          producer.setNamesrvAddr("192.168.247.132:9876");
         // Launch producer
         producer.start();
         int totalMessagesToSend = 100;
         for (int i = 0; i < totalMessagesToSend; i++) {
             Message message = new Message("TestTopic", ("Hello scheduled message " + i).getBytes());
             // This message will be delivered to consumer 10 seconds later.
             message.setDelayTimeLevel(3);
             // Send the message
             producer.send(message);
         }

         // Shutdown producer after use.
         producer.shutdown();
     }

 }

```

验证

您应该看到消息比其存储时间晚10秒消耗。

4、Batch Example 批量消息示例

为何Batch ？

Batch发送消息可提高传递大量短消息的性能。

使用限制

同一批次的消息应该具有：相同的主题，相同的waitStoreMsgOK和没有schedule计划支持。

此外，一批消息的总大小不应超过1MiB。

如何使用批次

如果您一次只发送不超过1MiB的消息集，则很容易使用Batch：

String topic = "BatchTest";
List<Message> messages = new ArrayList<>();
messages.add(new Message(topic, "TagA", "OrderID001", "Hello world 0".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID002", "Hello world 1".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID003", "Hello world 2".getBytes()));
try {
    producer.send(messages);
} catch (Exception e) {
    e.printStackTrace();
    //handle the error
}

拆分成列表

只有在发送大批量时，复杂性才会增加，您可能不确定它是否超出了大小限制（1MiB）。

此时，您最好拆分列表：

public class ListSplitter implements Iterator<List<Message>> {
    private final int SIZE_LIMIT = 1000 * 1000;
    private final List<Message> messages;
    private int currIndex;
    public ListSplitter(List<Message> messages) {
            this.messages = messages;
    }
    @Override public boolean hasNext() {
        return currIndex < messages.size();
    }
    @Override public List<Message> next() {
        int nextIndex = currIndex;
        int totalSize = 0;
        for (; nextIndex < messages.size(); nextIndex++) {
            Message message = messages.get(nextIndex);
            int tmpSize = message.getTopic().length() + message.getBody().length;
            Map<String, String> properties = message.getProperties();
            for (Map.Entry<String, String> entry : properties.entrySet()) {
                tmpSize += entry.getKey().length() + entry.getValue().length();
            }
            tmpSize = tmpSize + 20; //for log overhead
            if (tmpSize > SIZE_LIMIT) {
                //it is unexpected that single message exceeds the SIZE_LIMIT
                //here just let it go, otherwise it will block the splitting process
                if (nextIndex - currIndex == 0) {
                   //if the next sublist has no element, add this one and then break, otherwise just break
                   nextIndex++;  
                }
                break;
            }
            if (tmpSize + totalSize > SIZE_LIMIT) {
                break;
            } else {
                totalSize += tmpSize;
            }

        }
        List<Message> subList = messages.subList(currIndex, nextIndex);
        currIndex = nextIndex;
        return subList;
    }
}
//then you could split the large list into small ones:
ListSplitter splitter = new ListSplitter(messages);
while (splitter.hasNext()) {
   try {
       List<Message>  listItem = splitter.next();
       producer.send(listItem);
   } catch (Exception e) {
       e.printStackTrace();
       //handle the error
   }
}