if I am sending a message onto a multicast topic using:
TibrvMsg replyMessage = TibRvdTransport.sendRequest(message,timeout)
and there are two subscribers, which one actually sends the replyMessage, and what happens to the other replyMessage ?
I can only guess the fastest one that that answers. But I cannot see this documented anywhere.
Since your components are decoupled, they are unaware of each other. Rendezvous is pub-sub, which means that all subscribers receive all messages published to subjects that they have subscribed to. Furthermore, Rendezvous uses a peer-to-peer messaging approach vis-a-vis a centralized message forwarding approach. Therefore both components will receive the message and both components will reply.
If this is not the desired behavior, with Rendezvous you can use a distributed queue (RVDQ). With that approach a "scheduler" assigns work to workers, ensuring that messages get processed only once.
Related
I have implemented the example from the RabbitMQ website:
RabbitMQ Example
I have expanded it to have an application with a button to send a message.
Now I started two consumer on two different computers.
When I send the message the first message is sent to computer1, then the second message is sent to computer2, the thrid to computer1 and so on.
Why is this, and how can I change the behavior to send each message to each consumer?
Why is this
As noted by Yazan, messages are consumed from a single queue in a round-robin manner. The behavior your are seeing is by design, making it easy to scale up the number of consumers for a given queue.
how can I change the behavior to send each message to each consumer?
To have each consumer receive the same message, you need to create a queue for each consumer and deliver the same message to each queue.
The easiest way to do this is to use a fanout exchange. This will send every message to every queue that is bound to the exchange, completely ignoring the routing key.
If you need more control over the routing, you can use a topic or direct exchange and manage the routing keys.
Whatever type of exchange you choose, though, you will need to have a queue per consumer and have each message routed to each queue.
you can't it's controlled by the server check Round-robin dispatching section
It decides which consumer turn is. i'm not sure if there is a set of algorithms you can pick from, but at the end server will control this (i think round robin algorithm is default)
unless you want to use routing keys and exchanges
I would see this more as a design question. Ideally, producers should create the exchanges and the consumers create the queues and each consumer can create its own queue and hook it up to an exchange. This makes sure every consumer gets its message with its private queue.
What youre doing is essentially 'worker queues' model which is used to distribute tasks among worker nodes. Since each task needs to be performed only once, the message is sent to only one node. If you want to send a message to all the nodes, you need a different model called 'pub-sub' where each message is broadcasted to all the subscribers. The following link shows a simple pub-sub tutorial
https://www.rabbitmq.com/tutorials/tutorial-three-python.html
I am trying to implement an application(Java) which will subscribe to different message types (XMLs) from other different applications via TIBCO EMS. Each of these message types will have a specific purpose. I am of the opinion that I should have multiple queues with multiple subscribers in my application, however, the TIBCO guy is adamant that there should be only one queue where all of these messages will be published and I will have one subscriber and the subscriber then should have logic to different tasks based on the XML received.
Which approach is better? One with multiple queues and subscribers OR the one queue and one subscriber? Please let me know reasons for the choice.
Thanks!
-Naveen
In general, if the same application is reading all the messages, it is much cleaner for that application to have a single input queue instead of multiple input queues. With multiple then the application will need to have logic to know which order to process the queues and so on. With one input queue, the messaging system can deal with the order of the messages - whether FIFO or by priority etc, and the application can just read the next message and process it.
Use unique message header for each type of xml while sending the message. And use message selectors / filters while receiving the same, so that it can be routed / delegated to the respective handler based on the header value. This way, you will be able to handle different type of xml messages by single queue as well.
Say I have one JMS message FooCompleted
{"businessId": 1,"timestamp": "20140101 01:01:01.000"}
and another JMS message BazCompleted
{"businessId": 1,"timestamp": "20140101 01:02:02.000"}
The use case is that I want some action triggered when both messages have been received for the business id in question - essentially a join point of reception of the two messages. The two messages are published on two different queues and order between reception of FooCompleted and BazCompleted may change. In reality, I may need to have join of reception of several different messages for the businessId in question.
The naive approach was that to store the reception of the message in a db and check if message(s) its dependent join arm(s) have been received and only then kick off the action desired. Given that the problem seems generic enough, we were wondering if there is a better way to solve this.
Another thought was to move messages from these two queues into a third queue on reception. The listener on this third queue will be using a special avataar of DefaultMessageListenerContainer which overrides the doReceiveAndExecute to call receiveMessage for all outstanding messages in the queue and adding messages back to the queue whose all dependent messages have not yet arrived - the remaining ones will be acknowledged and hence removed. Given that the quantum of messages will be low, probing the queue over and adding messages again should not be a problem. The advantage would be avoiding the DB dependency and the associated scaffolding code. Wanted to see if there is something glaringly bad with this
Gurus, please critique and point out better ways to achieve this.
Thanks in advance!
Spring Integration with a JMS message-driven adapter and an aggregator with custom correlation and release strategies, and a peristent (JDBC) message store will provide your first solution without writing much (or any) code.
I was wondering what is the difference between a JMS Queue and JMS Topic.
ActiveMQ page says
Topics
In JMS a Topic implements publish and subscribe semantics. When you publish a message it goes to all the subscribers who are
interested - so zero to many subscribers will receive a copy of the
message. Only subscribers who had an active subscription at the time
the broker receives the message will get a copy of the message.
Queues
A JMS Queue implements load balancer semantics. A single message will be received by exactly one consumer. If there are no
consumers available at the time the message is sent it will be kept
until a consumer is available that can process the message. If a
consumer receives a message and does not acknowledge it before closing
then the message will be redelivered to another consumer. A queue can
have many consumers with messages load balanced across the available
consumers.
I want to have 'something' what will send a copy of the message to each subscriber in the same sequence as that in which the message was received by the ActiveMQ broker.
Any thoughts?
That means a topic is appropriate. A queue means a message goes to one and only one possible subscriber. A topic goes to each and every subscriber.
It is simple as that:
Queues = Insert > Withdraw (send to single subscriber) 1:1
Topics = Insert > Broadcast (send to all subscribers) 1:n
Topics are for the publisher-subscriber model, while queues are for point-to-point.
A JMS topic is the type of destination in a 1-to-many model of distribution.
The same published message is received by all consuming subscribers. You can also call this the 'broadcast' model. You can think of a topic as the equivalent of a Subject in an Observer design pattern for distributed computing. Some JMS providers efficiently choose to implement this as UDP instead of TCP. For topic's the message delivery is 'fire-and-forget' - if no one listens, the message just disappears. If that's not what you want, you can use 'durable subscriptions'.
A JMS queue is a 1-to-1 destination of messages. The message is received by only one of the consuming receivers (please note: consistently using subscribers for 'topic client's and receivers for queue client's avoids confusion). Messages sent to a queue are stored on disk or memory until someone picks it up or it expires. So queues (and durable subscriptions) need some active storage management, you need to think about slow consumers.
In most environments, I would argue, topics are the better choice because you can always add additional components without having to change the architecture. Added components could be monitoring, logging, analytics, etc.
You never know at the beginning of the project what the requirements will be like in 1 year, 5 years, 10 years. Change is inevitable, embrace it :-)
Queues
Pros
Simple messaging pattern with a transparent communication flow
Messages can be recovered by putting them back on the queue
Cons
Only one consumer can get the message
Implies a coupling between producer and consumer as it’s an one-to-one relation
Topics
Pros
Multiple consumers can get a message
Decoupling between producer and consumers (publish-and-subscribe pattern)
Cons
More complicated communication flow
A message cannot be recovered for a single listener
As for the order preservation, see this ActiveMQ page. In short: order is preserved for single consumers, but with multiple consumers order of delivery is not guaranteed.
If you have N consumers then:
JMS Topics deliver messages to N of N
JMS Queues deliver messages to 1 of N
You said you are "looking to have a 'thing' that will send a copy of the message to each subscriber in the same sequence as that in which the message was received by the ActiveMQ broker."
So you want to use a Topic in order that all N subscribers get a copy of the message.
TOPIC:: topic is one to many communication... (multipoint or publish/subscribe)
EX:-imagine a publisher publishes the movie in the youtub then all its subscribers will gets notification....
QUEVE::queve is one-to-one communication ...
Ex:-When publish a request for recharge it will go to only one qreciever ...
always remember if request goto all qreceivers then multiple recharge happened so while developing analyze which is fit for a application
Queue is JMS managed object used for holding messages waiting for subscribers to consume. When all subscribers consumed the message , message will be removed from queue.
Topic is that all subscribers to a topic receive the same message when the message is published.
I have a design query regarding queues. My scenario is as follows:
I have to use a messaging system, with single producer and multiple consumers (asynchronous). The producer pushes different types of messages into the messaging system. Depending upon the message type, that particular consumer has to consume that message. (Each consumer is running on a different server). If one consumer is down and a message comes for that consumer, it will be in the messaging system only. If I use a message queue, the message in the queue will block the next messages that can be consumed by the other consumers. Are queues suitable for handling this kind of situation? Or do we need to go for a topic?
Whether you use a queue or a topic should depend on whether there an instance where multiple consumers must process the same message. If that is the case then a topic is required do generate that one-to-many pattern.
On the other hand, if any one message will only ever be consumed by one consumer, then you can use a queue or topic and the consumers specify the message type as a JMS selector. In this way, all consumers can listen on the same queue and each selects a different subset of messages. In the event one application is not there, it's messages do not "block the next messages that can be consumed by the other consumers" but rather they just stack up in the queue and other consumers still receive their messages based on selection criteria.
Please also realize that queues are lightweight constructions and you can easily have one queue per consumer. Typically, things providing a service listen on a well-known queue and each queue represents a different function of the service or a different service. Thus there may be many service input queues. Similarly, reply messages are generally uniquely addressed to the application instance that made the request and go to a unique, often dynamic, reply-to queue. Both of these implementations I have described lead to a separation of traffic across queues rather than pooling different message types into the same queue. Since JMS selectors always impart an additional processing cost, using more queues is generally more performant than selecting many types of message from the same queue.
I am responding to your question about selectors in the comment section here since I have more space and can put links in...
Section 3.8.1 of the JMS 1.1 spec states:
A JMS message selector allows a client to specify, by message header, the
messages it’s interested in. Only messages whose headers and properties
match the selector are delivered. The semantics of not delivered differ a bit
depending on the MessageConsumer being used. See Section 5.8,
“QueueReceiver,” and Section 6.11, “TopicSubscriber,” for more details.
Message selectors cannot reference message body values.
A message selector matches a message if the selector evaluates to true when
the message’s header field and property values are substituted for their
corresponding identifiers in the selector.
As noted above, selectors can be on fields that are implicit in the message such as MsgID or CorrelationID or thsey can be on fields specifically set by the message producer such as a message property. Either way, the client must specify the value of any selectors used by the message consumer.