I have a MDB which listens to WebSphere MQ. It does not picks up the messages in the order that has been received by the Queue. How can i make it read it in that order? Is it possible? Should i not use a MDB.
In general, WMQ delivers messages in the order that they were received. However, several things can impact that...
If the queue is set to priority instead of FIFO delivery and messages arrive in different priorities, they will be delivered "out of order".
Distinguish between order produced and order delivered. If the messages are produced on a remote QMgr and there are multiple paths to the local QMgr, messages may arrive out of order.
Difference in persistence - if messages are produced on a remote QMgr and are of different persistences, the non-persistent messages may arrive faster than the persistent ones, especially with channel NPMSPEED(FAST) set.
Multiple readers/writers - Any dependency on sequence implies a single producer sending to a single consumer over a single path. Any redundancy in producers, consumers or paths between them can result in messages delivered out of sequence.
Syncpoint - To preserve sequence, ALL messages must be written and consumed under syncpoint or else ALL must be written and consumed outside of syncpoint.
Selectors - These specifically are intended to deliver messages out of order with respect to the context of all messages in the queue.
Message groups - Retrieval of grouped messages typically waits until the entire group is present. If groups are interleaved, messages are delivered out of sequence.
DLQ - if the target queue fills, messages may be delivered to the DLQ. As the target queue is drained, messages start going back there. With a queue near capacity, messages can alternate between the target queue and DLQ.
So when an MDB is receiving messages out of order any of these things, or even several of them in combination, may be at cause. Either eliminate the dependency on message sequence (best choice) or else go back over the design and reconcile all the factors that may lead to out-of-sequence processing.
To add to T.Rob's list, MDBs use the application server WorkManager to schedule message delivery, so message order is also dependent on the order in which the WorkManager starts Work items. This is outside the control of WMQ. If you limit the MDB ServerSessionPool depth to one, then this limit is removed as there will only ever be one in-flight Work instance, but at the cost of reducing maximum throughput.
If you're running in WebSphere application server, then non-ASF mode with ListenerPorts can preserve message order subject to some transactional/backout caveats. There's a support technote here:
http://www-01.ibm.com/support/docview.wss?uid=swg21446463
Related
ActiveMQ 5.15.13
Context: I have a single queue with multiple Consumers. I want to stop some consumers from processing certain messages. This has to be dynamic, I don't want to create separate queues for this. This works without any problems. e.g. Consumer1 ignores Stocks -> Consumer1 can process all invoices and Consumer2 can process all Stocks
But if there is a large number of messages already in the Queue (of one type, e.g. stocks) and I send a message of another type (e.g. invoices), Consumer1 won't process the message of type invoices. It will instead be idle until Consumer2 has processed all Stocks messages. It does not happen every time, but quite often.
Is there any option to change the order of the new messages coming into the queue, such that an idle consumer with matching selector picks up the new message?
Things I've already tried:
using a PendingMessageLimitStrategy -> it seems like it does not work for queues
increasing the maxPageSize and maxBrowsePageSize in the hope that once all Messages are in RAM, the Consumers will search for their messages.
Exclusive Consumers aren't an option since I want to be able to use more than one Consumer per message type.
Im pretty sure that there is some configuration which allows this type of usage. I'm aware that there are better solutions for this issue, but sadly I can't use them easily due to other constraints.
Thanks a lot in advance!
EDIT: I noticed that when I'm refreshing on the localhost queue browser, the stuck messages get executed immediately. It seems like this action performs some sort of queue refresh where the messages get filtered based on their selector again. So I just need this action whenever a new message enters the queue...
This is a 'window' problem where the next set of 'stocks' data needs to be processed before the 'invoicing' data can be processed.
The gotcha with window problems like this is that you need to account for the fact that some messages may never come through, or a consumer may never come back online either. Also, eventually you will be asked 'how many invoices or stocks are left to be processed'-- aka observability.
ActiveMQ has you covered-- check out wild-card destinations and consumers.
Produce 'stocks' to:
queue://data.stocks.input
Produce 'invoices' to:
queue://data.invoices.input
You then setup consumes to connect:
queue://data.*.input
note: the wildard '*'.
ActiveMQ will match queues based on the wildcard pattern, and then process data accordingly. As a bonus, you can still use a selector.
I'm running a Go service that uses the Paho Go MQTT client for subscribing to a topic. The clients that produce the MQTT messages (also Paho, but on Android devices) log when they produce and my service logs when it receives. As you can see from this graph, there seems to be a pretty consistent "cap" right below 36.000 messages per day on the receiving side. The graphs follow each other almost perfectly up to the cap, but then it seems that the go service caps out on slightly below 600 messages per minute, which means around 10 msgs per second.
Where should I look for the solution to this? I cannot find any setting (options) that could explain this cap.
As per the comments paho.mqtt.golang defaults to ordered delivery of messages (the MQTT spec provides some guarantees re message ordering and and calling handlers in a go routine may break this). The upshot of this is that messages will be delivered one-by-one and, if your handler is not keeping up, a queue may form (at QOS1+ the broker needs to retain messages as it may be necessary to resend them).
Some brokers limit the number of messages queued for a client; for example the max_queued_messages option in Mosquitto defaults to 1000 (this default was lower in Mosquitto 1.X) and, if the queue exceeds the limit, "messages will be silently dropped".
This is what appears to have been happening here; the application was not keeping up with incoming messages so the broker began dropping messages when the queue exceeded a limit.
In many cases using the paho.mqtt.golangoption ClientOptions.SetOrderMatters(false) will help; with this option set the message handler will be called in a separate go routine (so the handler must be threadsafe). Alternatively start a go routine within the handler but note that this approach results in the ACK being sent before the handler completes (which may result in message loss if your application terminates unexpectedly).
I have been exploring EventStoreDB and trying to understand more about the ordering of messages on the consumer side. Read about persistent subscriptions and also the Pinned consumer strategy here.
I have a scenario wherein inventory updates get pushed to eventstore and different streams get created by the different unique inventoryIds in the inventory event.
We have multiple consumers with the same consumerGroup name to read these inventory events. We are using Pinned Persistent Subscription with ResolveLinkTos enabled.
My question:
Will every message from a particular stream always go to the same consumer instance of the consumerGroup?
If the answer to the above question is yes, will every message from that particular stream reach the particular consumer instance in the same order as the events were ingested?
The documentation has a warning that ordered message processing using persistent subscriptions is not guaranteed. Any strategy delivers messages with the best-effort level of ordering guarantees, if applicable.
There are a few reasons for this, some of those are:
Spreading out messages across consumer groups lead to a non-linearised checkpoint commit. It means that some messages can be processed before other messages.
Persistent subscriptions attempt to buffer messages, but when a timeout happens on the client side, the whole buffer is redelivered, which can eventually break the processing order
Built-in retry policies essentially can break the message order at any time
Most event log-based brokers, if not all, don't even attempt to guarantee ordered message delivery across multiple consumers. I often hear "but Kafka does it", ignoring the fact that Kafka delivers messages from one partition to at most one consumer in a group. There's no load balancing of one partition between multiple consumers due to exactly the same issue. That being said, EventStoreDB is still not a broker, but a database for events.
So, here are the answers:
Will every message from a particular stream always go to the same consumer instance of the consumer group?
No. It might work most of the time, but it will eventually break.
will every message from that particular stream reach the particular consumer instance in the same order as the events were ingested?
Most of the time, yes, but again, if a message is being retried, you might get the next message before the previous one is Acked.
Overall, load-balancing ordered processing of messages, which aren't pre-partitioned on the server is not an easy task. At most, you get messages re-delivered if the checkpoint fails to persist at some point, and the consumers restart.
What can be the best way to aggregate messages from many different sources (actually queues/topics) into a single queue/topic and then consume it. I am trying to design an application to receive messages from different topics in JMS using weblogic.
You could write your own "aggregator" as a stand-alone Java application:
For each queue/topic have a reader in its own thread.
Each reader sends its received message again on a "aggregate queue".
Have another thread to listen on the "aggregate queue".
As a variation, you could use a JVM Queue (like java.util.concurrent.ArrayBlockingQueue) as the "aggregate queue". This is faster, does not require another MQ queue, does not need network bandwidth, but it's not persistent.
Another idea is to use a "Message driven bean (MDB)" for each incoming queue/topic:
Again, each of these MDBs just reads the message and resends it to the "aggregate queue".
Have another MDB listening on the "aggregate queue".
A few suggestions on quality requirements. I belive you have to consider them.
They will be highly relate with your technical solution.
is that message loss acceptable?
client ack could be considered.
e.g. A memory queue sit in middle, e.g. incoming queue1...n -> ArrayBlockingQueue in memory -> outgoing queue. The data in the ArrayBlockingQueue , will lost when app crash.
is that message duplicate acceptable for the single outgoing queue?
I would suggest yes.
Set applicable level PossibleDuplicateFlag to make the client aware of that.
how fast the incoming messages per second on the diff incoming queue?
one queue session has only a uniqe thread. Performance has to be considered in advance.
I send a java object to a queue from a thread. The relavent MDB's onMessage is invoked with a message from the queue. onMessage, I match a key present in the message with a key in a cache, if key is not present I throw a custom runtimeexception just to make the container redeliver this message. (I have another autonomous system that adds key to the cache from the external system response, it may be little slow by 3-5 seconds)
In such case, does this container add this unprocessed message to the end of the queue, or is it redelivered immediately? is there a way to delay the redelivery time? assuming the queue is always filled with ~550 messages every second.
regards
There's current a redelivery delay feature on HornetQ but all the subsequent messages are delivered fine.
There's a feature request in place to hold the queue for some time if a redelivery happens but that has not been implemented yet.
but if you have multiple consumers on the queue the order will be spread with your consumers anyways. You could use message-grouping and add a sleep on your onMessage if deliveryCount > 1. The message grouping is to guarantee no other consumer (or another MDB instance) will receive the messages out of order.
Depending on how you're application is done, and depending on your requirements you may want to only allow a single instance of your MDB.
Also: look at the consumer-window-size where you can select no buffering on the client which has a better behaviour when you have multiple consumers or multiple mdb instances.