Let me try explaining the situation:
There is a messaging system that we are going to incorporate which could either be a Queue or Topic (JMS terms).
1 ) Producer/Publisher : There is a service A. A produces messages and writes to a Queue/Topic
2 ) Consumer/Subscriber : There is a service B. B asynchronously reads messages from Queue/Topic. B then calls a web service and passes the message to it. The webservice takes significant amount of time to process the message. (This action need not be processed real-time.)
The Message Broker is Tibco
My intention is : Not to miss out processing any message from A. Re-process it at a later point in time in case the processing failed for the first time (perhaps as a batch).
Question:
I was thinking of writing the message to a DB before making a webservice call. If the call succeeds, I would mark the message processed. Otherwise failed. Later, in a cron job, I would process all the requests that had initially failed.
Is writing to a DB a typical way of doing this?
Since you have a fail callback, you can just requeue your Message and have your Consumer/Subscriber pick it up and try again. If it failed because of some problem in the web service and you want to wait X time before trying again then you can do either schedule for the web service to be called at a later date for that specific Message (look into ScheduledExecutorService) or do as you described and use a cron job with some database entries.
If you only want it to try again once per message, then keep an internal counter either with the Message or within a Map<Message, Integer> as a counter for each Message.
Crudely put that is the technique, although there could be out-of-the-box solutions available which you can use. Typical ESB solutions support reliable messaging. Have a look at MuleESB or Apache ActiveMQ as well.
It might be interesting to take advantage of the EMS platform your already have (example 1) instead of building a custom solution (example 2).
But it all depends on the implementation language:
Example 1 - EMS is the "keeper" : If I were to solve such problem with TIBCO BusinessWorks, I would use the "JMS transaction" feature of BW. By encompassing the EMS read and the WS call within the same "group", you ask for them to be both applied, or not at all. If the call failed for some reason, the message would be returned to EMS.
Two problems with this solution : You might not have BW, and the first failed operation would block all the rest of the batch process (that may be the desired behavior).
FYI, I understand it is possible to use such feature in "pure java", but I never tried it : http://www.javaworld.com/javaworld/jw-02-2002/jw-0315-jms.html
Example 2 - A DB is the "keeper" : If you go with your "DB" method, your queue/topic customer continuously drops insert data in a DB, and all records represent a task to be executed. This feels an awful lot like the simple "mapping engine" problem every integration middleware aims to make easier. You could solve this with anything from a custom java code and multiples threads (DB inserter, WS job handlers, etc.) to an EAI middleware (like BW) or even a BPM engine (TIBCO has many solutions for that)
Of course, there are also other vendors... EMS is a JMS standard implementation, as you know.
I would recommend using the built in EMS (& JMS) features,as "guaranteed delivery" is what it's built for ;) - no db needed at all...
You need to be aware that the first decision will be:
do you need to deliver in order? (then only 1 JMS Session and Client Ack mode should be used)
how often and in what reoccuring times do you want to retry? (To not make an infinite loop of a message that couldn't be processed by that web service).
This is independent whatever kind of client you use (TIBCO BW or e.g. Java onMessage() in a MDB).
For "in order" delivery: make shure only 1 JMS Session processes the messages and it uses Client acknolwedge mode. After you process the message sucessfully, you need to acknowledge the message with either calling the JMS API "acknowledge()" method or in TIBCO BW by executing the "commit" activity.
In case of an error you don't execute the acknowledge for the method, so the message will be put back in the Queue for redelivery (you can see how many times it was redelivered in the JMS header).
EMS's Explicit Client Acknolwedge mode also enables you to do the same if order is not important and you need a few client threads to process the message.
For controlling how often the message get's processed use:
max redelivery properties of the EMS queue (e.g. you could put the message in the dead
letter queue afer x redelivery to not hold up other messages)
redelivery delay to put a "pause" in between redelivery. This is useful in case the
Web Service needs to recover after a crash and not gets stormed by the same message again and again in high intervall through redelivery.
Hope that helps
Cheers
Seb
Related
Our app uses Spring Boot and JMS messages with Tibco. We have two production servers running and processing messages concurrently. Servers are listening to the same one queue. Each server has 10 concurrent listeners. I do not want the very same message gets processed by both servers at the same time. Nothing prevents our queue of having duplicate messages, like we can have two copies of the message A in the queue. If messages in the queue are: A, A, B, C, D, then if first A gets delivered to server1 and second A gets delivered to server2, and both servers process A at the same time, then they are chances of creating duplicate entities. I want to find a way to send all A messages to only one server. I can't use Message Selector b/c we have the same code base running on both servers. This is what I'm considering:
Based on the message, set properties in the headers. Once the message got delivered to the process() method, depending on which server is processing the message, either discard, simply return the message or process the message and acknowledge it. The problem with this solution is that since we need to dynamicacaly find out which server is processing the message, the server name needs to be hardcoded, meaning if the server moves, the code breaks!
Other solution - that might work - is the Destination field.
https://docs.spring.io/spring/docs/4.0.x/spring-framework-reference/html/jms.html
Destinations, like ConnectionFactories, are JMS administered objects
that can be stored and retrieved in JNDI. When configuring a Spring
application context you can use the JNDI factory class
JndiObjectFactoryBean / to perform dependency
injection on your object’s references to JMS destinations.
It's something I never done before. Is there anyway, to configure the Destination that it picks up the right server to route the message to? Meaning, if message1 is supposed to be delivered to server1, then it does not even gets delivered to server2 and remains in the queue until server1 consumes it?
What are other ways to implement this?
EDIT:
I still do not know what’s the best way to send certain messages to only one server for processing, however, accepted the response given to use database as validation, b/c this is what we consider to avoid creating duplicate entities when processing the data.
I think the idea of using the JMS Destination is a non-starter as there is nothing in the JMS specification which guarantees any kind of link between the destination and a broker. The destination is just an encapsulation for the provider-specific queue/topic name.
The bottom line here is that you either need to prevent the duplicate messages in the first place or have some way to coordinate the consumers to deal with the duplicates after they've been pulled off the queue. I think you could do either of these using an external system like a database, e.g.:
When producing the message check the database for an indication that the message was sent already. If no indication is found then write a record to the database (will need to use a primary key to prevent duplicates) and send the message. Otherwise don't send the message.
When consuming the message check the database for an indication that the message is being (or was) consumed already. If no indication is found then write a record to the database (will need to use a primary key to prevent duplicates) and process the message. Otherwise just acknowledge the message without processing it.
I suggest an alternative to "post DB sync".
Keep the servers and listeners as-is, and broadcast all+ the the processed messages on a topic. For servers just starting, you can use "durable subscribers" to not miss any messages.
If you broadcast each start and end of processing for messages A, B, C, etc AND consider adding a little pause (in milli), you should avoid collisions. It's the main risk of course.
It's not clear to me if you should validate for duplicate processing at the beginning or end of a message processing... it depends on your needs.
If this whole idea is not acceptable, DB validation might be the only option, but as stated in comments above, I fear for scaling.
I have a piece of middleware that sits between two JMS queues. From one it reads, processes some data into the database, and writes to the other.
Here is a small diagram to depict the design:
With that in mind, I have some interesting logic that I would like to integrate into the service.
Scenario 1: Say the middleware service receives a message from Queue 1, and hits the database to store portions of that message. If all goes well, it constructs a new message with some data, and writes it to Queue 2.
Scenario 2: Say that the database complains about something, when the service attempts to perform some logic after getting a message from Queue 1.In this case, instead of writing a message to Queue 2, I would re-try to perform the database functionality in incremental timeouts. i.e Try again in 5 sec., then 30 sec, then 1 minute if still down. The catch of course, is to be able to read other messages independently of this re-try. i.e Re-try to process this one request, while listening for other requests.
With that in mind, what is both the correct and most modern way to construct a future proof solution?
After reading some posts on the net, it seems that I have several options.
One, I could spin off a new thread once a new message is received, so that I can both perform the "re-try" functionality and listen to new requests.
Two, I could possibly send the message back to the Queue, with a delay. i.e If the process failed to execute in the db, write the message to the JMS queue by adding some amount of delay to it.
I am more fond of the first solution, however, I wanted to get the opinion of the community if there is a newer/better way to solve for this functionality in java 7. Is there something built into JMS to support this sort of "send message back for reprocessing at a specific time"?
JMS 2.0 specification describes the concept of delayed delivery of messages. See "What's new" section of https://java.net/projects/jms-spec/pages/JMS20FinalReleaseMany JMS providers have implemented the delayed delivery feature.
But I wonder how the delayed delivery will help your scenario. Since the database writes have issues, subsequent messages processing and attempt to write to database might end up in same situation. I guess it might be better to sort out issues with database updates and then pickup messages from queue.
I am trying to understand the best use of RabbitMQ to satisfy the following problem.
As context I'm not concerned with performance in this use case (my peak TPS for this flow is 2 TPS) but I am concerned about resilience.
I have RabbitMQ installed in a cluster and ignoring dead letter queues the basic flow is I have a service receive a request, creates a persistent message which it queues, in a transaction, to a durable queue (at this point I'm happy the request is secured to disk). I then have another process listening for a message, which it reads (not using auto ack), does a bunch of stuff, writes a new message to a different exchange queue in a transaction (again now happy this message is secured to disk). Assuming the transaction completes successfully it manually acks the message back to the original consumer.
At this point my only failure scenario is is I have a failure between the commit of the transaction to write to my second queue and the return of the ack. This will lead to a message being potentially processed twice. Is there anything else I can do to plug this gap or do I have to figure out a way of handling duplicate messages.
As a final bit of context the services are written in java so using the java client libs.
Paul Fitz.
First of all, I suggest you to look a this guide here which has a lot of valid information on your topic.
From the RabbitMQ guide:
At the Producer
When using confirms, producers recovering from a channel or connection
failure should retransmit any messages for which an acknowledgement
has not been received from the broker. There is a possibility of
message duplication here, because the broker might have sent a
confirmation that never reached the producer (due to network failures,
etc). Therefore consumer applications will need to perform
deduplication or handle incoming messages in an idempotent manner.
At the Consumer
In the event of network failure (or a node crashing), messages can be
duplicated, and consumers must be prepared to handle them. If
possible, the simplest way to handle this is to ensure that your
consumers handle messages in an idempotent way rather than explicitly
deal with deduplication.
So, the point is that is not possibile in any way at all to guarantee that this "failure" scenario of yours will not happen. You will always have to deal with network failure, disk failure, put something here failure etc.
What you have to do here is to lean on the messaging architecture and implement if possibile "idempotency" of your messages (which means that even if you process the message twice is not going to happen anything wrong, check this).
If you can't than you should provide some kind of "processed message" list (for example you can use a guid inside every message) and check this list every time you receive a message; you can simply discard them in this case.
To be more "theorical", this post from Brave New Geek is very interesting:
Within the context of a distributed system, you cannot have
exactly-once message delivery.
Hope it helps :)
Edited Question : I am working on a multithreaded JMS receiver and publisher code (stand alone multithreaded java application). MOM is MQSonic.
XML message is received from a Queue, stored procedures(takes 70 sec to execute) are called and response is send to Topic within 90 sec.
I need to handle a condition when broker is down or application is on scheduled shutdown. i.e. a condition in which messages are received from Queue and are being processed in java, in the mean time both Queue and Topic will be down. Then to handle those messages which are not on queue and not send to topic but are in java memory, I have following options:
(1) To create CLIENT_ACKNOWLEDGE session as :
connection.createSession(false, javax.jms.Session.CLIENT_ACKNOWLEDGE)
Here I will acknowledge message only after the successful completion of transactions(stored procedures)
(2) To use transacted session i.e., connection.createSession(true, -1). In this approach because of some exception in transaction (stored procedure) the message is rolled back and Redelivered. They are rolled back again and again and continue until I kill the program. Can I limit the number of redelivery of jms messages from queue?
Also in above two approached which one is better?
The interface progress.message.jclient.ConnectionFactory has a method setMaxDeliveryCount(java.lang.Integer value) where you can set the maximum number of times a message will be redelivered to your MessageConsumer. When this number of times is up, it will be moved to the SonicMQ.deadMessage queue.
You can check this in the book "Sonic MQ Application Programming Guide" on page 210 (in version 7.6).
As to your question about which is better... that depends on whether the stored procedure minds being executed multiple times. If that is a problem, you should use a transaction that spans the JMS queue and the database both (Sonic has support for XA transactions). If you don't mind executing multiple times, then I would go for not acknowledging the message and aborting the processing when you notice that the broker is down (when you attempt to acknowledge the message, most likely). This way, another processor is able to handle the message if the first one is unable to do so after a connection failure.
If the messages take variable time to process, you may also want to look at the SINGLE_MESSAGE_ACKNOWLEDGE mode of the Sonic JMS Session. Normally, calling acknowledge() on a message also acknowledges all messages that came before it. If you're processing them out of order, that's not what you want to happen. In single message acknowledge mode (which isn't in the JMS standard), acknowledge() only acknowledges the message on which it is called.
If you are worried about communicating with a message queue/broker/server/etc that might be down, and how that interrupts the overall flow of the larger process you are trying to design, then you should probably look into a JMS queue that supports clustering of servers so you can still reliably produce/consume messages when individual servers in the cluster go down.
Your question isn't 100% clear, but it seems the issue is that you're throwing an exception while processing a message when you really shouldn't be.
If there is an actual problem with the message, say the xml is malformed or it's invalid according to your data model, you do not want to roll back your transaction. You might want to log the error, but you have successfully processed that message, it's just that "success" in this case means that you've identified the message as problematic.
On the other hand, if there is a problem in processing the message that is caused by something external to the message (e.g. the database is down, or the destination topic is unavailable) you probably do want to roll the transaction back, however you also want to make sure you stop consuming messages until the problem is resolved otherwise you'll end up with the scenario you've described where you continually process the same message over and over and fail every time you try to access whatever resource is currently unavailable.
Without know what messaging provider you are using, I don't know whether this will help you.
MQ Series messages have a backout counter, that can be enabled by configuring the harden backout counter option on the queue.
When I have previously had this problem , I do as follows:
// get/receive message from queue
if ( backout counter > n ) {
move_message_to_app_dead_letter_queue();
return;
}
process_message();
The MQ series header fields are accessible as JMS properties.
Using the above approach would also help if you can use XA transactions to rollback or commit the database and the queue manager simultaneously.
However XA transactions do incur a significant performance penalty and with stored proc's this probably isn't possible.
An alternative approach would be to write the message immediately to a message_table as a blob, and then commit the message from the queue.
Put a trigger on the message_table to invoke the stored proc, and then add the JMS response mechanism into the stored proc.
We have a custom messaging system written in Java, and I want to implement a basic batching/compression feature that basically under heavy load it will aggregate a bunch of push responses into a single push response.
Essentially:
if we detect 3 messages were sent in the past second then start batching responses and schedule a timer to fire in 5 seconds
The timer will aggregate all the message responses received in the next 5 seconds into a single message
I'm sure this has been implemented before I'm just looking for the best example of it in Java. I'm not looking for a full blown messaging layer, just the basic detect messages per second and schedule some task (obviously I can easily write this myself I just want to compare it with any existing algorithms to make sure I'm not missing any edge cases or that I've simplified the problem as much as possible).
Are there any good open source examples of building a basic QoS batching/throttling/compression implementations?
we are using a very similar mechanism for high load.
it will work as you described it
* Aggregate messages over a given interval
* Send a List instead of a single message after that.
* Start aggregating again.
You should watch out for the following pitfalls:
* If you are using a transacted messaging system like JMS you can get into trouble because your implementation will not be able to send inside the JMS transaction so it will keep aggregating. Depending on the size of your data structure to hold the messages this can run out of space. If you are have very long transactions sending many messages this can pose a problem.
* Sending a message in such a way will happen asynchronous because a different thread will be sending the message and the thread calling the send() method will only put it in the data structure.
* Sticking to the JMS example you should keep in mind that they way messages are consumed is also changed by this approach. Because you will receive the list of messages from JMS as a single message. So once you commit this single JMS message you commited the entire list of messages. You should check if this i a problem to your requirements.