I'm trying to check if there are messages on a queue. To access the queue I'm using a Connection Factory, a Destination Resource and JNDI lookup (method below). The problem comes when the Connection Factory points to multiple nodes from a Glassfish 3 cluster. The AddressList property has the list with ip addresses of the nodes.
One way to solve it, would be to check each node. Is there a way to read the value of the AddressList property from a JMS Connection Factory defined in the Glassfish resources ?
Are there any other ways to check if there are messages on a queue on all the nodes of a Glassfish 3 cluster ?
Wouldn't like to save the addresses of the cluster nodes both in a configuration file and in the JMS Connection Factory (the Connection Factory is already used in some other parts of the application).
Thanks.
private boolean existsMessagesOnTheQueue(String connectionFactoryName, Queue queue, String selector) throws Exception {
QueueConnectionFactory connectionFactory;
QueueConnection connection;
Session session ;
QueueBrowser browser ;
try {
connectionFactory = (QueueConnectionFactory) InitialContext.doLookup(connectionFactoryName);
connection = connectionFactory.createQueueConnection();
session = connection.createSession(true, Session.AUTO_ACKNOWLEDGE);
browser = session.createBrowser(queue, selector);
connection.start();
if (browser.getEnumeration().hasMoreElements()) {
log.debug("Found message on " + queue.getQueueName());
return true;
}
} finally {
closeBrowser(browser);
closeSession(session);
closeConnection(connection);
}
return false;
}
Even if the connection factory lists multiple nodes in its AddressList attribute, it is sufficient to check for messages in any ONE of these addresses. All the other copies in the cluster would have the same messages.
From Oracle doc:
In a broker cluster, you create a physical destination on one broker and the cluster propagates it to all the others. Because the brokers cooperate to route messages across the cluster, client applications can consume messages from destinations on any broker in the cluster.
The above mentions about clients consuming messages from any broker in the cluster. So, Browsing could also be done through any broker.
Related
I am facing a scenario where the reply queue I connect to, runs out of handles. I have traced it to the fact that my JMS Producers are being cached but not my JMS consumers. I am able to send and receive messages just fine so there is no problem with connecting-sending-receiving to/from the queues. I am using the CachedConnectionFactory (SessionCacheSize = 10)with the target factory as com.ibm.mq.jms.MQQueueConnectionFactory while instantiating the jmsTemplate. Code snippet is as follows
:
:
String replyQueue = "MyQueue";// replyQueue which runs out of handles
messageCreator.setReplyToQueue(new MQQueue(replyQueue));
jmsTemplate.setReceiveTimeout(receiveTimeout);
jmsTemplate.send(destination, messageCreator);// Send to destination queue
Message message = jmsTemplate.receiveSelected(replyQueue,
String.format("JMSCorrelationID = '%s'", messageCreator.getMessageId()));
:
:
From the logs (jms TRACE is enabled) Producer is cached, so the destination queue "handle count" does not increase.
// The first time around (for Producer)
Registering cached JMS MessageProducer for destination[queue:///<destination>:com.ibm.mq.jms.MQQueueSender#c9x758b
// Second time around, the cached producer is reused
Found cached JMS MessageProducer for destination [queue:///<destination>]: com.ibm.mq.jms.MQQueueSender#c9x758b
However, the handles for the replyQueue keep increasing because for every call to that queue, I see a new JMS Consumer being registered. Ultimately the calls to open the replyQueue fail because of MQRC_HANDLE_NOT_AVAILABLE
// First time around
Registering cached JMS MessageConsumer for destination [queue:///<replyQueue>]:com.ibm.mq.jms.MQQueueReceiver#b3ytd25b
// Second time around, another MessageConsumer is registered !
Registering cached JMS MessageConsumer for destination [queue:///<replyQueue>]:com.ibm.mq.jms.MQQueueReceiver#re25b
My memory is a bit dim on this, but here is what is happening. You are receiving messages based on a message selector. This selector is always changing, however. As a test, either remove the selector or make it a constant and see what happens. So when you try to cache/pool based on connection/session/consumer, the consumer is always changing. This requires a new cache entry.
After you go through your 10 sessions, a new connection will be created, but the existing one is not closed. Increase your session count to 100, for example, and your connection count on the MQ broker should climb 10 time slower.
You need to create a new consumer for every message receive as your correlation ID is always changing. So just cache connection/session. No matter what you do, you will always have to round trip to the broker to ask for the new correlation ID.
We have a queue in production where message TTL was set via application. Now we want to change message TTL and attach policy via rabbit CTL than setting within application. Snippet:
Map<String, Object> args = new HashMap<>();
args.put("x-message-ttl", 86400000);
for (String queueName : queueNames) {
Queue queue = new Queue(queueName, true, false, false, args);
admin.declareQueue(queue);
...
}
To achieve this in running application we want way to validate if Queue already exists do nothing otherwise create new Queue without args. It is not possible to leverage local cache as multiple publisher/subscriber nodes can restart under unplanned outage scenario. With above would be able to change TTL during Rabbit upgrade/Migration
Can you help if there is an API to fetch all existing queues and its argument properties?
Note: Overriding x-message-ttl with different value throws error.
RabbitMQ has a REST API and a java client for it.
You can use that to get information about existing elements such as queues.
I have listeners configured in XML like this
<rabbit:listener-container connection-factory="connectionFactory" concurrency="1" acknowledge="manual">
<rabbit:listener ref="messageListener" queue-names="${address.queue.s1}" exclusive="true"/>
<rabbit:listener ref="messageListener" queue-names="${address.queue.s2}" exclusive="true"/>
<rabbit:listener ref="messageListener" queue-names="${address.queue.s3}" exclusive="true"/>
<rabbit:listener ref="messageListener" queue-names="${address.queue.s4}" exclusive="true"/>
<rabbit:listener ref="messageListener" queue-names="${address.queue.s5}" exclusive="true"/>
<rabbit:listener ref="messageListener" queue-names="${address.queue.s6}" exclusive="true"/>
</rabbit:listener-container>
I am trying to move that to Java Configuration and I don't see a way to add more than one MessageListener to a ListenerContainer. Creating multiple ListenerContainer beans is not an option in my case because I would not know the number of queues to consume from until runtime. Queue names will come from a configuration file.
I did the following
#PostConstruct
public void init()
{
for (String queue : queues.split(","))
{
// The Consumers would not connect if I don't call the 'start()' method.
messageListenerContainer(queue).start();
}
}
#Bean
public SimpleMessageListenerContainer messageListenerContainer(String queue)
{
SimpleMessageListenerContainer container = new SimpleMessageListenerContainer(consumerConnectionFactory);
container.setQueueNames(queue);
container.setMessageListener(messageListener());
// Set Exclusive Consumer 'ON'
container.setExclusive(true);
// Should be restricted to '1' to maintain data consistency.
container.setConcurrentConsumers(1);
container.setAcknowledgeMode(AcknowledgeMode.MANUAL);
return container;
}
It "sort" of works BUT I see some weird behavior with lots of ghost channels getting opened which never used to happen with the XML configuration. So it makes me suspicious that I am doing something wrong. I would like to know the correct way of creating MessageListenerContainers in Java configuration? Simply put, "How does Spring convert 'rabbit:listener-container' with multiple 'rabbit:listener' to java objects properly?" Any help/insight into this would be greatly appreciated.
Business Case
We have a Publisher that publishes User Profile Updates. The publisher could dispatch multiple updates for the same use and we have to process them in the correct order to maintain data integrity in the data store.
Example : User : ABC, Publish -> {UsrA:Change1,...., UsrA:Change 2,....,UsrA:Change 3} -> Consumer HAS to process {UsrA:Change1,...., UsrA:Change 2,....,UsrA:Change 3} in that order.
In our previous setup, we had 1 Queue that got all the User Updates and we had a consumer app with concurrency = 5. There were multiple app servers running the consumer app. That resulted in *5 * 'Number of instances of the consumer app' channels/threads* that could process the incoming messages. The speed was GREAT! but we were having out of order processing quite often resulting in data corruption.
To maintain strict FIFO order and still process message parallelly as much as possible, we implemented queue Sharding. We have a "x-consistent-hash with a hash-header on employee-id. Our Publisher publishes messages to the hash exchange and we have multiple sharded queues bound to the hash exchange. The idea is, we will have all changes for a given user (User A for example) queued up in the same shard. We then have our consumers connect to the sharded queues in 'Exclusive' mode and 'ConcurrentConsumers = 1' and process the messages. That way we are sure to process messages in the correct order while still processing messages parallelly. We could make it more parallel by increasing the number of shards.
Now on to the consumer configuration
We have the consumer app deployed on multiple app servers.
Original Approach:
I simply added multiple 'rabbit:listener' to my 'rabbit:listener-container' in my consumer app as you can see above and it works great except for the server that starts first get an exclusive lock on all the sharded queues and the other servers are just sitting there doing no work.
New Approach:
We moved the sharded queue names to the application configuration file. Like so
Consumer Instance 1 : Properties
queues=user.queue.s1,user.queue.s2,user.queue.s3
Consumer Instance 2 : Properties
queues=user.queue.s4,user.queue.s5,user.queue.s6
Also worth noting, we could have Any number of Consumer instances and the shards could be distributed unevenly between instances depending on resource availability.
With the queue names moved to configuration file, the XML confiugration will no longer work because we cannot dynamically add 'rabbit:listener' to my 'rabbit:listener-container' like we did before.
Then we decided to switch over to the Java Configuration. That is where we are STUCK!.
We did this initially
#Bean
public SimpleMessageListenerContainer messageListenerContainer()
{
SimpleMessageListenerContainer container = new SimpleMessageListenerContainer(consumerConnectionFactory);
container.setQueueNames(queues.split(","));
container.setMessageListener(messageListener());
container.setMissingQueuesFatal(false);
// Set Exclusive Consumer 'ON'
container.setExclusive(true);
// Should be restricted to '1' to maintain data consistency.
container.setConcurrentConsumers(1);
container.setAcknowledgeMode(AcknowledgeMode.MANUAL);
container.start();
return container;
}
and it works BUT all our queues are on one connection sharing 1 channel. That is NOT good for speed. What we want is One connection and every queue gets its own channel.
Next Step
No success here YET!. The java configuration in my original question is where we are at now.
I am baffled why this is so HARD to do. Clearly the XML configuration does something that is NOT easly doable in Java confiugration (Or atleast it feel sthat way to me). I see this as a gap that needs to be filled unless I am compeltly missing something. Please correct me if I am wrong. This is a genuine business case NOT some ficticious edge case. Please feel free to comment if you think otherwise.
and it works BUT all our queues are on one connection sharing 1 channel. That is NOT good for speed. What we want is One connection and every queue gets its own channel.
If you switch to the DirectMessageListenerContainer, each queue in that configuration gets its own Channel.
See the documentation.
To answer your original question (pre-edit):
#Bean
public SimpleMessageListenerContainer messageListenerContainer1(#Value("${address.queue.s1}") String queue)
{
SimpleMessageListenerContainer container = new SimpleMessageListenerContainer(consumerConnectionFactory);
container.setQueueNames(queue);
container.setMessageListener(messageListener());
// Set Exclusive Consumer 'ON'
container.setExclusive(true);
// Should be restricted to '1' to maintain data consistency.
container.setConcurrentConsumers(1);
container.setAcknowledgeMode(AcknowledgeMode.MANUAL);
return container;
}
...
#Bean
public SimpleMessageListenerContainer messageListenerContainer6(#Value("${address.queue.s6}" ) String queue)
{
SimpleMessageListenerContainer container = new SimpleMessageListenerContainer(consumerConnectionFactory);
container.setQueueNames(queue);
container.setMessageListener(messageListener());
// Set Exclusive Consumer 'ON'
container.setExclusive(true);
// Should be restricted to '1' to maintain data consistency.
container.setConcurrentConsumers(1);
container.setAcknowledgeMode(AcknowledgeMode.MANUAL);
return container;
}
Here is the Java Configuration for creating SimpleMessageListenerContainer
#Value("#{'${queue.names}'.split(',')}")
private String[] queueNames;
#Bean
public SimpleMessageListenerContainer listenerContainer(final ConnectionFactory connectionFactory) {
final SimpleMessageListenerContainer container = new SimpleMessageListenerContainer();
container.setConnectionFactory(connectionFactory);
container.setQueueNames(queueNames);
container.setMessageListener(vehiclesReceiver());
setCommonQueueProperties(container);
return container;
}
Each <rabbit:listener > creates its own SimpleListenerContainer bean with the same ConnectionFactory. To do similar in Java config, you have to declare as much SimpleListenerContainer beans as you have queues: one for each of them.
You also may consider to use #RabbitListener approach instead: https://docs.spring.io/spring-amqp/docs/2.0.4.RELEASE/reference/html/_reference.html#async-annotation-driven
I want to know the redelivery of JMS in a microservices.
For example, if I have a microservices system. And I have 2 instances of User service. And have a listener on a destination in user service. It means I have 2 listeners. The listener is like this:
#JmsListener(destination = "order:new", containerFactory = "orderFactory")
#Transactional
public void create(OrderDTO orderDTO) {
Order order = new Order(orderDTO);
orderRepository.save(order);
jmsTemplate.convertAndSend("order:need_to_pay", order);
}
So my question is, how many times a message will be delivered. And if there is some error in this function, and the message will be re-delivered. But I have 2 instances of the service. And on which this message will be delivered?
It's not part of the spec; it depends on the broker configuration how many times it will be delivered; many brokers can be configured to send the message to a dead-letter queue after some number of attempts.
There is no guarantee the redelivery will go to the same instance.
I use the following url to create ActiveMQConnactionFactory:
failover:(tcp://server1:port,tcp://server2:port,tcp://server2:port)
What I want to do is to create multiple message consumers from this network of brokers.
The following is not a real code, but it helps to undestand how I do that:
ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory("BROKER_URL");
connection = connectionFactory.createConnection();
connection.start();
for (int i=0; i<10; i++) {
session = connection.createSession(false, Session.CLIENT_ACKNOWLEDGE);
Destination queue = consumerSession.createQueue("QUEUE_NAME");
consumer = consumerSession.createConsumer(queue);
consumer.setMessageListener(new MessageListener());
}
The problem is that all consumers will be connected to one randomly choosen broker.
But I want them to be balanced over the network of brokers.
I believe it is possible to do that by creating multiple connections with the factory.
But what are the best practices for that?
And is this a good thing which I want? :)
Actually, the consumer would not be connected to a randomly chosen broker.
A connection is the part that connects to a broker. With the connection string you have provided, you will have ONE connection mapped to ONE randomly chosen broker. All consumers have their own sessions but these would use the same ONE connection to that ONE broker.
The only setting I know of, is that you can disable the randomize behavior of the failover protocol by setting ?randomize=false on the connection string. This would mean your connection will first try the first, then the second, then the third, etc.
But to achieve your requirement. I would make each consumer to have it's own connection. This, together with the randomize feature in the fail-over protocol would kinda load-balance the consumers; but not for real, there is no intelligence in there and is just "randomizing" the broker it is connecting to.
This means, I would do the following (from your code)
ActiveMQConnectionFactory connectionFactory = new ActiveMQConnectionFactory("BROKER_URL");
for (int i=0; i<10; i++) {
connection = connectionFactory.createConnection();
connection.start();
session = connection.createSession(false, Session.CLIENT_ACKNOWLEDGE);
Destination queue = consumerSession.createQueue("QUEUE_NAME");
consumer = consumerSession.createConsumer(queue);
consumer.setMessageListener(new MessageListener());
}
This way, each consumer will have it's own connection to "a" broker of your fail-over connection string
UPDATED AFTER QUESTION CHANGE:
If you want to let ActiveMQ randomly choose a broker for each consumer, the above mentioned solution is the way to go.
The best practice would be to put your consumers and producers as close to each other as possible. For this, I would recommend lowering the network consumer priority, so the local consumer and producer would have highest priority. Only when the local consumer is not idle, it would distribute further over the network to other consumers.
In addition to that, it will be a good idea if the operation on consumer side is long running to set a lower prefetch value, so that the messages do get load balanced around the network of brokers instead of one consumer snatching up 1,000 messages while other consumers are idle.