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HazelcastMQ Core

The core MQ library that provides a JMS 2.0-like API for sending and receiving messages. Core has no dependencies on JMS and can be used directly as a light weight messaging framework. Other messaging APIs can be layered on top of the core API to provide compatibility with existing frameworks and tools.

Features

  • Send and receive from queues, topics, and temporary queues
  • Transactional message sending (per thread, not context due to Hazelcast limitation)
  • Message expiration (in the consumer only)
  • Request/reply pattern using correlation IDs and reply-to destinations

Not Going to Work Any Time Soon

  • Transactional message reception

Examples

A code example of sending a message using HazelcastMQ Core is shown below. Normally the MQ instance is created at application startup using your DI framework of choice.

HazelcastMQConfig mqConfig = new HazelcastMQConfig();
mqConfig.setHazelcastInstance(hz);

HazelcastMQInstance mqInstance = HazelcastMQ
      .newHazelcastMQInstance(mqConfig); // (1)
HazelcastMQContext mqContext = mqInstance.createContext(); // (2)

HazelcastMQMessage msg = new HazelcastMQMessage();
msg.setContentAsString("Hello World!");

HazelcastMQProducer mqProducer = mqContext.createProducer(); // (3)
mqProducer.send("/queue/example.dest", msg); // (4)

mqContext.close();
mqInstance.shutdown();

Using HazelcastMQ Core is similar to using the JMS 2.0 API (but with no JMS dependencies):

  1. Create a HazelcastMQ instance
  2. Create a HazelcastMQ context
  3. Create a message producer or consumer
  4. Send or receive messages

Simple Send and Receive

This example shows a simple send and receive message pattern where both the producer and consumer are implemented in the same code.

View the example.

Node Failure

One of the major benefits of using Hazelcast as the message transport/store is that it offers flexible reliability and replication options. This example shows a (local) three node cluster and how messages can be produced and consumed even in the event of a single or multiple node failure in the cluster. If you've ever worked with a clustered JMS broker before, you'll appreciate the simplicity of this configuration.

View the example.