为什么选择批量消息?

批量发送消息可提高单次发送消息的性能.

使用限制

相同批次的消息应具有：相同的主题，相同的等待消息处理成功但是不支持定时处理. 此外，一个批量的消息的总大小不要错过1MB.

怎么使用批量消息

如果您一次只发送不超过1MB的消息，使用批量发送很方便:

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
}

分割成列表

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

目前，你最好分开列表:

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
   }
}