Lets say I have 100 physical servers. Each of them runs a java process. And we have one global rabbitMQ queue. This queue is shared between all 100 processes. In other words I need every of 100 JVMs listen this global queue.
The first question is is it possible to do it?
The second question is if it`s possible, how to dispatch messages from the global queue to 100 nodes and make sure that loading will be distributed proportionally, so we will not get the situation when one node loaded up to 100% and other 99 to 0.0005%.
Each node has minimum and maximum capacity. So ideally, one JVM should ask the queue how many items it has. And then grab needed number of items up to it`s maximum capacity. And every JVM from mentioned 100 should do the same. So how to synchronize the queue? How it will let spring amqp on certain machine know that item is ready for procession? How to balance the loading? Thank you
This sounds like sharding to me. I haven't used it, but there's a plugin for sharding on RabbitMQ now. https://github.com/rabbitmq/rabbitmq-sharding
The first question is is it possible to do it?
Yes, there is no issue.
how to dispatch messages from the global queue to 100 nodes and make
sure that loading will be distributed proportionally, so we will not
get the situation when one node loaded up to 100% and other 99 to
0.0005%.
RabbitMQ does round robin between consumer on the same queue: RabbitMQ will send each message to the next consumer, in sequence. To limit the number of messages sent to a consumer, you can use consumer prefetch and set the QoS according to the maximum capacity of the node. Thus, RabbitMQ will push message to a node as long as the node has not reach its QoS ie. its maximum capacity ie. the number of unacked message is below this threshold.
So the node does not need to know that the queue contains messages, messages will be pushed to the node:
Messages are pushed to the node as long as the QoS threshold is not reach.
Messages are put in a local queue
Once a worker is available, worker takes the message, processes it
Worker ackes the message when it finished the process
Because the message is acked, the current unacked message is below the QoS threshold, loop to 1).
See:
The worker tutorial about round robin and fair dispatching.
How to set wisely the prefetch Some queuing theory: throughput, latency and bandwidth
Related
I am new to Apache Kafka and I am trying to configure Apache Kafka that it receives messages from the producer as much as possible but it only sends to the consumer configured number of messages per specific time.
In other words How to configure Apache Kafka to send only "50 messages for example" per "30 seconds"
to the consumer regardless of the number of the messages, and in the next 30 seconds it takes another 50 messages from the cashed messages and so on.
If you have control over the consumer
You could use max.poll.records property to limit max number of records per poll() method call. And then you only need to ensure that poll() is called once in 30 seconds.
In general you can take a look at all available configuration properties here.
If you cannot control consumer
Then the only option for you is to write messages as per your demand - write at most 50 messages in 30 seconds. There are no configuration options available. Only your application logic can achieve that.
updated - how to control ensure call to poll
The simplest way is to:
while (true) {
consumer.poll()
// .. do your stuff
Thread.sleep(30000);
}
You can make things more complex with measuring time for processing (i.e. starting after poll call up to Thread.sleep() to not wait more then 30 seconds at all.
The problem that producer really doesn't send messages to the consumer. There is that persistent Kafka topic in between where producer places its messages. And it really doesn't care if there is any consumer on the other side. Same from the consumer perspective: it just subscribers for data from the topic and doesn't care if there is some producer on the other side. So, thinking about a back-pressure from the consumer down to producer where there is a messaging middle ware is wrong direction.
On the other hand it is not clear how those consumed messages may impact your third party service. The point is that Kafka consumer is single-threaded per partition. So, all the messages from one partition is going to be (must) processed one by one in the same thread. This way you cannot send more than one messages to your service: the next one can be sent only when the previous has been replied. So, think about it: how it is even possible in your consumer application to excess rate limit?
However if you have enough partitions and high concurrency on the consumer side, so you really may end up with several requests to your service in parallel from different threads. For this purpose I would suggest to take a look into a Rate Limiter pattern. This library provides a good implementation: https://resilience4j.readme.io/docs/ratelimiter. It is much better to keep messages in the topic then try to limit producer somehow.
To conclude: even if the consumer side is not your project, it is better to discuss with that team how to improve their consumer. You did your part well: the producer sends messages to Kafka topic. What else you can do over here?
Interesting use case and not sure why you need it, but two possible solutions: 1. To protect the cluster, you could use quotas, not for amount of messages but for bandwidth throughput: https://kafka.apache.org/documentation/#design_quotas . 2. If you need an exact amount of messages per time frame, you could put a buffering service (rate limiter) in between where you consume and pause, publishing messages to the consumed topic. Rate limiter could consume next 50 then pause until minute passes. This will increase space used on your cluster because of duplicated messages. You also need to be careful of how to pause the consumer, hearbeats need to be sent else you will rebalance your consumer continuously, ie you can't just sleep till next minute. This is obviously if you can't control the end consumer.
I´m using activemq(5.14.5) with camel(2.13.4) because I still need java 6.
I have a queue and 15 consumers. The messages sent to them are request reply.
When I start the consumers, the messages are distributed one per consumer as soon as the messages arrive but, after some time, only one consumer receives the messages, the others stay idle and a lot of messages stay pending.
The consumers have this configuration:
concurrentConsumers=15&maxMessagesPerTask=1&destination.consumer.prefetchSize=0&transferException=true
The time spent to process each message can varies a lot because of our business rule so, I don´t know if activemq has some rule that manage slow consumers and redirect to only one that is more "efficient".
The behaviour that I was expecting is that all the messages that arrives, start to process until all the consumers are full, but it is not what is happening.
Anybody knows what is happening?
Following is an image about what is happening:
Your configuration has two eye-catching settings:
maxMessagesPerTask=1
If you did not intend to configure auto-scaling the threadpool, you should remove this setting completely. Is is by default unlimited and it sets how long to keep threads for processing (scaling up/down threadpool).
See also the Spring Docs about this setting
prefetchSize=0
Have you tried setting this to 1 so that every consumer just gets 1 message at a time?
The AMQ docs say about the prefetchSize:
Large prefetch values are recommended for high performance with high message volumes. However, for lower message volumes, where each message takes a long time to process, the prefetch should be set to 1. This ensures that a consumer is only processing one message at a time. Specifying a prefetch limit of zero, however, will cause the consumer to poll for messages, one at a time, instead of the message being pushed to the consumer.
I have below configuration for rabbitmq
prefetchCount:1
ack-mode:auto.
I have one exchange and one queue is attached to that exchange and one consumer is attached to that queue. As per my understanding below steps will be happening if queue has multiple messages.
Queue write data on a channel.
As ack-mode is auto,as soon as queue writes message on channel,message is removed from queue.
Message comes to consumer,consumer start performing on that data.
As Queue has got acknowledgement for previous message.Queue writes next data on Channel.
Now,my doubt is,Suppose consumer is not finished with previous data yet.What will happen with that next data queue has written in channel?
Also,suppose prefetchCount is 10 and I have just once consumer attached to queue,where these 10 messages will reside?
The scenario you have described is one that is mentioned in the documentation for RabbitMQ, and elaborated in this blog post. Specifically, if you set a sufficiently large prefetch count, and have a relatively small publish rate, your RabbitMQ server turns into a fancy network switch. When acknowledgement mode is set to automatic, prefetch limiting is effectively disabled, as there are never unacknowledged messages. With automatic acknowledgement, the message is acknowledged as soon as it is delivered. This is the same as having an arbitrarily large prefetch count.
With prefetch >1, the messages are stored within a buffer in the client library. The exact data structure will depend upon the client library used, but to my knowledge, all implementations store the messages in RAM. Further, with automatic acknowledgements, you have no way of knowing when a specific consumer actually read and processed a message.
So, there are a few takeaways here:
Prefetch limit is irrelevant with automatic acknowledgements, as there are never any unacknowledged messages, thus
Automatic acknowledgements don't make much sense when using a consumer
Sufficiently-large prefetch when auto-ack is off, or any use of autoack = on will result in the message broker not doing any queuing, and instead doing routing only.
Now, here's a little bit of expert opinion. I find the whole notion of a message broker that "pushes" messages out to be a little backwards, and for this very reason- it's difficult to configure properly, and it is unclear what the benefit is. A queue system is a natural fit for a pull-based system. The processor can ask the broker for the next message when it is done processing the current message. This approach will ensure that load is balanced naturally and the messages don't get lost when processors disconnect or get knocked out.
Therefore, my recommendation is to drop the use of consumers altogether and switch over to using basic.get.
I have a producer which sends persistent messages in batches to a queue leveraging JMS transaction.
I have tested and found that Producer Flow Control is applied when using a batch size of 1. I could see my producer being throttled as per the memory limit I have configured for the queue. Here's my Producer Flow Control configuration:
<policyEntry queue="foo" optimizedDispatch="true"
producerFlowControl="true" memoryLimit="1mb">
</policyEntry>
The number of pending messages in the queue are in control which I see as the evidence for Producer Flow Control in action.
However, when the batch size is increased to 2, I found that this memory limit is not respected and the producer is NOT THROTTLED at all. The evidence being the number of pending messages in the queue continue to increase till it hits the storeUsage limit configured.
I understand this might be because the messages are sent in asynchronous fashion when the batch size is more than 1 even though I haven't explicitly set useAsyncSend to true.
ActiveMQ's Producer Flow Control documentation mentions that to throttle asynchronous publishers, we need to configure Producer Window Size in the producer which shall force the Producer to wait for acknowledgement once the window limit is reached.
However, when I configured Producer Window Size in my producer and attempted to send messages in batches, an exception is thrown and no messages were sent.
This makes me think and ask this question, "Is it possible to configure Producer Window Size while sending persistent messages in batches?".
If not, then what is the correct way to throttle the producers who send persistent messages in batches?
There is not really a way to throttle "max msgs per second" or similar. What you would do is to enable producer flow control and vm cursor, then set the memory limit on that queue (or possibly all queues if you wish) to some reasonable level.
You can decide in the configuration if the producer should hang or throw an exception if the queue memory limit has been reached.
<policyEntry queue="MY.BATCH.QUEUE" memoryLimit="100mb" producerFlowControl="true">
<pendingQueuePolicy>
<vmQueueCursor/>
</pendingQueuePolicy>
</policyEntry>
I found this problem in v5.8.0 but found this to be resolved in v5.9.0 and above.
From v5.9.0 onwards I found PFC is applied out of the box even for producers who send messages asynchronously.
Since batch send (where batch size > 1) is essentially an asynchronous operation, this applies there as well.
But the PFC wiki was confusing as it mentions that one should configure ProducerWindowSize for async producers if PFC were to be applied. However, I tested and verified that this was not needed.
I basically configured a per-destination limit of 1mb and sent messages in batches (with batch size of 100).
My producer was throttled out of the box without any additional configuration. The number of pending messages in the queue didn't increase and was under control.
With a simple Camel consumer consuming the messages (and appending them to a file), I found that with v5.8.0 (where I faced the problem), I could send 100k messages with the payload being 2k in 36 seconds. But most of them ended up as Pending messages.
But with v5.9.0, it took 176 seconds to send the same set of messages testifying the role played by PFC. And the number of pending messages never increased beyond 1000 in my case.
I also tested with v5.10.0 and v5.12.0 (the latest version at the time of writing) which worked as expected.
So if you are facing this problem, chances are that you are running ActiveMQ v5.8.0 or earlier. Simply upgrading to the latest version should solve this problem.
I thank the immensely helpful ActiveMQ mailing list folks for all their suggestions and help.
Thanks #Petter for your answer too. Sorry I didn't mention the version I was using in my question, otherwise I believe you could have spotted the problem straight away.
I am setting up an application which needs to be scaled. I post messages to Active MQ and read messages from there.
Till now , I have used maximum upto 3 concurrent consumers pointing to a queue( Each consumer operating from a different physical machine ).
I need to know maximum how many consumers I can point to a Queue in Active MQ.
Is there a maximum limit to it ?
I found this link:
http://activemq.apache.org/multiple-consumers-on-a-queue.html
But it does not state anything about Maximum connections / Sessions / consumers. It only says One session per connection.
The JMS specification does not state any limit on the number of consumers. You can add as many consumers as you want for a given Queue or Topic.
The question is how many consumers you really need. Increasing the number of consumers will allow you to do more parallel processing but you will face memory issues. For e.g. If you start thousands of consumers on a single machine it is simply going to start thousands of threads which will consume memory.
Also if you are having multiple consumers for a single Queue it is a good idea to have selectors to filter out messages from the queue so that you can have some control on messages and which listeners should consume them.
Any number of consumer can point to that queue. But only 1 consumer will be able to access the object inside that queue. Once it retrieves the object, that particular consumer will be disconnected and other consumer will get connected to your queue.
You can specify the size of queue in your xml file. You can find it easily in some search engine. I dont remember the tag name exactly.