I am new to JMS, and I am trying to understand if there is a way to consume messages in parallel from a JMS queue and process them using Spring JMS.
I checked a few answers on Stack Overflow, but I am still confused.
The application I am working on uses Spring Boot and Weblogic JMS as the messaging broker. It listens to a JMS queue from a single producer using the JmsListener class.
In the JMS ConnectionFactory configuration of the application the following parameter has been set:
DefaultJmsListenerContainerFactory.setConcurrency("6-10");
Does that mean if there are 100 messages currently in a queue then 10 messages will be consumed and processed in parallel? If so, can I increase the value to process more messages in parallel? If so, are there any limitations to it?
Also, I am confused about what DefaultJmsListenerContainerFactory.setConcurrency and setConcurrentConsumers does.
Currently the processing of JMS client app is very slow. So I need suggestions to implement parallel processing.
concurrentConsumers is a fixed number of consumers where as concurrency can specify a variable number which scale up/down as needed. Also see maxConcurrentConsumers.
The actual behavior also depends on prefetch; if each consumer prefetches 100 messages then only one consumer might get them all.
There is no limit (aside from memory/cpu constraints).
I have a test app (first with RabbitMQ) which runs on partially trusted clients (in that i don't want them creating queues on their own), so i will look into the security permissions of the queues and credentials that the clients connect with.
For messaging there are mostly one-way broadcasts from server to clients, and sometimes a query from server to a specific client (over which the replies will be sent on a replyTo queue which is dedicated to that client on which the server listens for responses).
I currently have a receive function on the server which looks out for "Announce" broadcast from clients:
agentAnnounceListener.Received += (model, ea) =>
{
var body = ea.Body;
var props = ea.BasicProperties;
var message = Encoding.UTF8.GetString(body);
Console.WriteLine(
"[{0}] from: {1}. body: {2}",
DateTimeOffset.FromUnixTimeMilliseconds(ea.BasicProperties.Timestamp.UnixTime).Date,
props.ReplyTo,
message);
// create return replyTo queue, snipped in next code section
};
I am looking to create the return to topic in the above receive handler:
var result = channel.QueueDeclare(
queue: ea.BasicProperties.ReplyTo,
durable: false,
exclusive: false,
autoDelete: false,
arguments: null);
Alternatively, i could store the received announcements in a database, and on a regular timer run through this list and declare a queue for each on every pass.
In both scenarioes this newly created channel would then be used at a future point by the server to send queries to the client.
My questions are please:
1) Is it better to create a reply channel on the server when receiving the message from client, or if i do it externally (on a timer) are there any performance issues for declaring queues that already exist (there could be thousands of end points)?
2) If a client starts to miss behave, is there any way that they can be booted (in the receive function i can look up how many messages per minute and boot if certain criteria are met)? Are there any other filters that can be defined prior to receive in the pipeline to kick clients who are sending too many messages?
3) In the above example notice my messages continuously come in each run (the same old messages), how do i clear them out please?
I think preventing clients from creating queues just complicates the design without much security benefit.
You are allowing clients to create messages. In RabbitMQ, its not very easy to stop clients from flooding your server with messages.
If you want to rate-limit your clients, RabbitMQ may not be the best choice. It does rate-limiting automatically when servers starts to struggle with processing all the messages, but you can't set a strict rate limit on per-client basis on the server using out-of-the-box solution. Also, clients are normally allowed to create queues.
Approach 1 - Web App
Maybe you should try to use web application instead:
Clients authenticate with your server
To Announce, clients send a POST request to a certain endpoint, ie /api/announce, maybe providing some credentials that allow them to do so
To receive incoming messages, GET /api/messages
To acknowledge processed message: POST /api/acknowledge
When client acknowledges receipt, you delete your message from database.
With this design, you can write custom logic to rate-limit or ban clients that misbehave and you have full control of your server
Approach 2 - RabbitMQ Management API
If you still want to use RabbitMQ, you can potentially achieve what you want by using RabbitMQ Management API
You'll need to write an app that will query RabbitMQ Management API on timer basis and:
Get all the current connections, and check message rate for each of them.
If message rate exceed your threshold, close connection or revoke user's permissions using /api/permissions/vhost/user endpoint.
In my opinion, web app may be easier if you don't need all the queueing functionality like worker queues or complicated routing that you can get out of the box with RabbitMQ.
Here are some general architecture/reliability ideas for your scenario. Responses to your 3 specific questions are at the end.
General Architecture Ideas
I'm not sure that the declare-response-queues-on-server approach yields performance/stability benefits; you'd have to benchmark that. I think the simplest topology to achieve what you want is the following:
Each client, when it connects, declares an exclusive and/or autodelete anonymous queue. If the clients' network connectivity is so sketchy that holding open a direct connection is undesirable, so something similar to Alex's proposed "Web App" above, and have clients hit an endpoint that declares an exclusive/autodelete queue on their behalf, and closes the connection (automatically deleting the queue upon consumer departure) when a client doesn't get in touch regularly enough. This should only be done if you can't tune the RabbitMQ heartbeats from the clients to work in the face of network unreliability, or if you can prove that you need queue-creation rate limiting inside the web app layer.
Each client's queue is bound to a broadcast topic exchange, which the server uses to communicate broadcast messages (wildcarded routing key) or specifically targeted messages (routing key that only matches one client's queue name).
When the server needs to get a reply back from the clients, you could either have the server declare the response queue before sending the "response-needed" message, and encode the response queue in the message (basically what you're doing now), or you could build semantics in your clients in which they stop consuming from their broadcast queue for a fixed amount of time before attempting an exclusive (mutex) consume again, publish their responses to their own queue, and ensure that the server consumes those responses within the allotted time, before closing the server consume and restoring normal broadcast semantics. That second approach is much more complicated and likely not worth it, though.
Preventing Clients Overwhelming RabbitMQ
Things that can reduce the server load and help prevent clients DoSing your server with RMQ operations include:
Setting appropriate, low max-length thresholds on all the queues, so the amount of messages stored by the server will never exceed a certain multiple of the number of clients.
Setting per-queue expirations, or per-message expirations, to make sure that stale messages do not accumulate.
Rate-limiting specific RabbitMQ operations is quite tricky, but you can rate-limit at the TCP level (using e.g. HAProxy or other router/proxy stacks), to ensure that your clients don't send too much data, or open too many connections, at a time. In my experience (just one data point; if in doubt, benchmark!) RabbitMQ cares less about the count of messages ingested per time than it does the data volume and largest possible per-message size ingested. Lots of small messages are usually OK; a few huge ones can cause latency spikes, otherwise, rate-limiting the bytes at the TCP layer will probably allow you to scale such a system very far before you have to re-assess.
Specific Answers
In light of the above, my answers to your specific questions would be:
Q: Should you create reply queues on the server in response to received messages?
A: Yes, probably. If you're worried about the queue-creation rate
that happens as a result of that, you can rate-limit per server instance. It looks like you're using Node, so you should be able to use one of the existing solutions for that platform to have a single queue-creation rate limiter per node server instance, which, unless you have many thousands of servers (not clients), should allow you to reach a very, very large scale before re-assessing.
Q: Are there performance implications to declaring queues based on client actions? Or re-declaring queues?
A: Benchmark and see! Re-declares are probably OK; if you rate-limit properly you may not need to worry about this at all. In my experience, floods of queue-declare events can cause latency to go up a bit, but don't break the server. But that's just my experience! Everyone's scenario/deployment is different, so there's no substitute for benchmarking. In this case, you'd fire up a publisher/consumer with a steady stream of messages, tracking e.g. publish/confirm latency or message-received latency, rabbitmq server load/resource usage, etc. While some number of publish/consume pairs were running, declare a lot of queues in high parallel and see what happens to your metrics. Also in my experience, the redeclaration of queues (idempotent) doesn't cause much if any noticeable load spikes. More important to watch is the rate of establishing new connections/channels. You can also rate-limit queue creations very effectively on a per-server basis (see my answer to the first question), so I think if you implement that correctly you won't need to worry about this for a long time. Whether RabbitMQ's performance suffers as a function of the number of queues that exist (as opposed to declaration rate) would be another thing to benchmark though.
Q: Can you kick clients based on misbehavior? Message rates?
A: Yes, though it's a bit tricky to set up, this can be done in an at least somewhat elegant way. You have two options:
Option one: what you proposed: keep track of message rates on your server, as you're doing, and "kick" clients based on that. This has coordination problems if you have more than one server, and requires writing code that lives in your message-receive loops, and doesn't trip until RabbitMQ actually delivers the messages to your server's consumers. Those are all significant drawbacks.
Option two: use max-length, and dead letter exchanges to build a "kick bad clients" agent. The length limits on RabbitMQ queues tell the queue system "if more messages than X are in the queue, drop them or send them to the dead letter exchange (if one is configured)". Dead-letter exchanges allow you to send messages that are greater than the length (or meet other conditions) to a specific queue/exchange. Here's how you can combine those to detect clients that publish messages too quickly (faster than your server can consume them) and kick clients:
Each client declares it's main $clientID_to_server queue with a max-length of some number, say X that should never build up in the queue unless the client is "outrunning" the server. That queue has a dead-letter topic exchange of ratelimit or some constant name.
Each client also declares/owns a queue called $clientID_overwhelm, with a max-length of 1. That queue is bound to the ratelimit exchange with a routing key of $clientID_to_server. This means that when messages are published to the $clientID_to_server queue at too great a rate for the server to keep up, the messages will be routed to $clientID_overwhelm, but only one will be kept around (so you don't fill up RabbitMQ, and only ever store X+1 messages per client).
You start a simple agent/service which discovers (e.g. via the RabbitMQ Management API) all connected client IDs, and consumes (using just one connection) from all of their *_overwhelm queues. Whenever it receives a message on that connection, it gets the client ID from the routing key of that message, and then kicks that client (either by doing something out-of-band in your app; deleting that client's $clientID_to_server and $clientID_overwhelm queues, thus forcing an error the next time the client tries to do anything; or closing that client's connection to RabbitMQ via the /connections endpoint in the RabbitMQ management API--this is pretty intrusive and should only be done if you really need to). This service should be pretty easy to write, since it doesn't need to coordinate state with any other parts of your system besides RabbitMQ. You'll lose some messages from misbehaving clients with this solution, though: if you need to keep them all, remove the max-length limit on the overwhelm queue (and run the risk of filling up RabbitMQ).
Using that approach, you can detect spamming clients as they happen according to RabbitMQ, not just as they happen according to your server. You could extend it by also adding a per-message TTL to messages sent by the clients, and triggering the dead-letter-kick behavior if messages sit in the queue for more than a certain amount of time--this would change the pseudo-rate-limiting from "when the server consumer gets behind by message count" to "when the server consumer gets behind by message delivery timestamp".
Q: Why do messages get redelivered on each run, and how do I get rid of them?
A: Use acknowledgements or noack (but probably acknowledgements). Getting a message in "receive" just pulls it into your consumer, but doesn't pop it from the queue. It's like a database transaction: to finally pop it you have to acknowledge it after you receive it. Altnernatively, you could start your consumer in "noack" mode, which will cause the receive behavior to work the way you assumed it would. However, be warned, noack mode imposes a big tradeoff: since RabbitMQ is delivering messages to your consumer out-of-band (basically: even if your server is locked up or sleeping, if it has issued a consume, rabbit is pushing messages to it), if you consume in noack mode those messages are permanently removed from RabbitMQ when it pushes them to the server, so if the server crashes or shuts down before draining its "local queue" with any messages pending-receive, those messages will be lost forever. Be careful with this if it's important that you don't lose messages.
From my understanding RabbitMQ producers require acknowledgment when sending messages to the broker which provides a delivery-guarantee. Kafka producers does not require acknowledgement from the broker. Does that mean there’s no delivery-guarantee with Kafka? If not, how does Kafka provide delivery guarantee without acknowledgement?
Is my understanding correct? Please correct any misunderstandings that I have as I’m still learning about these systems.
Kafka is actually flexible about this.
The number of acknowledgements for producers is configurable. The configuration is called RequiredAcks. In fact, required acks is set on ProduceRequest level, but I've never seen implementations where a single producer instance allows producing messages with different required acks settings.
RequiredAcks is an integer value which means "how many acknowledgements the broker should wait before responding to a produce request".
Having RequiredAcks set to 0 (VERY not recommended for production) means "fire and forget", e.g. broker will respond immediately without waiting until data is written to log. This is the case where you could lose messages without even knowing about that.
Having RequiredAcks set to 1 means "wait until data is written to local log", where local log is log of the broker that received the request. Once your data is written to local log, broker responds.
Having RequiredAcks set to -1 means "wait until the data is written to local log AND replicated by all ISRs".
Each ProduceRequest also has a Timeout field, which means "maximum time to wait for necessary amount of acknowledgements".
So Kafka supports acknowledging requests but allows turning acknowledgements off.
In 0.9.0.0 and above, the producer#send has a return value Future you can get the offset of the message in the broker's partition. Meantime, you can implement Callback, if there is no exception, it's mean that the message has been sent to the correct broker.
I'm using NServiceBus 4.x with RabbitMQ 3.2.x as my transport.
I made the assumption that by using RabbitMQ as my transport I would be given the competing consumer model as an option. I understand that NServiceBus employs the "Fannout" exchange type for all exchanges and does not support round robin at this time. However is there a way to configure NServiceBus to take advantage of the levels of indirection via Exchanges and channels that RabbitMQ offers.
I have several consumers I would like to compete for messages from a given queue. What I am observing is subscribers' blocking access to further message retrieval from the queue until the message is consumed. So having more then one consumer at this point does me no good other then redundancy.
After reading some documentation on RabbitMQ I'm assuming that it's normal to block until the Ack receipt is sent from the subscriber. But I had assumed that subscriber #2 would have free access to the queue to fetch another message.
There is mention of increasing the prefetch count on RabbitMQ channel.
Example:
channel.BasicQos(0,prefetchcount,false)
I don't see anywhere that I can change this setting via configuration in NServiceBus. Furthermore as I read what prefetch does I'm really not sure this what i'm looking for.
Is it possible to use RabbitMQ with out a distirbutor type pattern used with MSMQ? Or should I move to MassTransit or Rebus?
Put prefetchcount=2 in your connection string. Any value above 1 will tell the broker to allow more than X unacked message to go out. You need to fiddle with this setting to find the optimum for your scenario.
Is it possible to bind a single queue to many topics using RabbitMQ STOMP client?
Each time a client sending SUBSCRIBE frame server creates a new queue for it, it makes usage of "prefetch-count" useless for me, because it applies to each subscription individually.
I am just looking for any way to get messages with many topics in the single queue via RabbitMQ Web-STOMP. Any ideas?
See Documentation:User generated queue names for Topic and Exchange destinations
The header x-queue-name specified queue name should binding to same queue if there exist, but will exist multiple subscription on client.
The different between AMQP and STOMP concept not compatible in some ways.