When we use the javax.jms.QueueBrowser.getEnumeration() will it only browse the queue content inside the JVM? Will it significantly affect application memory usage?
Also, when we use queue browser to get the queue itself, then so much data actually takes up memory which will not be the case with getEnumeration(). Please help me understand if I am right.
A certain amount of messages are prefetched when you consume a queue with a QueueBrowser. This limit can be configured in ActiveMQPrefetchPolicy on an ActiveMQConnectionFactory. The property queueBrowserPrefetch regulates number of messages received in a batch, and buffered into memory until all are acknowledged.
Related
I have durable exchanges and queues in my application. The messages are persistent too. Using this configuration i am sure my messages gets stored in physical storage. I want to know if there is any expiry time when rabbitmq delete messages from my physical storage i mean the hard disk as it maintains the message store in it. Also in case i want to read the messages from physical storage then can i do so?
Durable queue + Persistent messages means indeed the messages will be kept.
Exceptions to this statement out of the top of my head:
you would have configured additional properties to your queues, for exemple limits in size
you reach the limit to the underlying filesystem
you delete the queues (this would delete the messages stored in it too)
As to reading the messages stored in the queues, you can typically consume them.
If you want to read them without them being deleted, you'd have few options:
trick the broker (for example by reading all of them but never acknowledging them, which would have them brought back into the queue)
republish them again to the broker for storage after reading them
But if indeed further conservation is desired, I'd seriously consider storing them somewhere else (DB of some kind) at it's clearly outside of the purpose of a message broker.
I want a bunch of several hundred client apps to create and use temporary queues at one instance of the middleware.
Are there some cons regarding performance why I shouldn't use temp queues? Are there limitations, for example on how many temp. queues can be created per HornetQ instance?
On a recent project we have switched from using temporary queues to using static queues on SonicMQ. We had implemented synchronous service calls over JMS where the response of each call would be delivered on a dedicated temporary queue, created by the consumer. During stress testing we noticed that the overhead of temporary queue creation and allocated resources started to play a bigger and bigger part when pushing the maximum throughput of the solution.
We changed the solution so it would use static queues between consumer and provider and use a selector to correlate on the JMSCorrelationID. This resulted in better throughput in our case. If you are planning on each time (re)creating the temporary queues that your client applications will use, it could start to impact performance when higher throughput rates are needed.
Note that selector performance can also start to play when the number of messages in a queue increase. In our case the solution was designed to hand-off the messages as soon as possible and not play the role of a (storage) buffer in between consumer and provider. As such the number of message inside a queue would always be low.
I'm looking for help regarding a strange issue where a slow consumer on a queue causes all the other consumers on the same queue to start consuming messages at 30 second intervals. That is all consumers but the slow one don't consumer messages as fast as they can, instead they wait for some magical 30s barrier before consuming.
The basic flow of my application goes like this:
a number of producers place messages onto a single queue. Messages can have different JMSXGroupIDs
a number of consumers listen to messages on that single queue
as standard practice the JMSXGroupIDs get distributed across the consumers
at some point one of the consumers becomes slow and can't process messages very quickly
the slow consumer ends up filling its prefetch buffer on the broker and AMQ recognises that it is slow (default behaviour)
at that point - or some 'random' but close time later - all consumers except the slow one start to only consume messages at the same 30s intervals
if the slow consumer becomes fast again then things very quickly return to normal operation and the 30s barrier goes away
I'm at a loss for what could be causing this issue, or how to fix it, please help.
More background and findings
I've managed to reliably reproduce this issue on AMQ 5.8.0, 5.9.0 (where the issue was originally noticed) and 5.9.1, on fresh installs and existing ops-managed installs and on different machines some vm and some not. All linux installs, different OSs and java versions.
It doesn't appear to be affected by anything prefetch related, that is: changing the prefetch value from 1 to 10 to 1000 didn't stop the issue from happening
[red herring?] Enabling debug logs on the amq instance shows logs relating to the periodic check for messages that can be expired. The queue doesn't have an expiry policy so I can only think that the scheduled expireMessagesPeriod time is just waking amq up in such a way that it then sends messages to the non-slow consumers.
If the 30s mode is entered then left then entered again the seconds-past-the-minute time is always the same, for example 14s and 44s past the minute. This is true across all consumers and all machines hosting those consumers. Those barrier points do change after restarts of amq.
While not strictly a solution to the problem, further investigation has uncovered the root cause of this issue.
TL;DR - It's known behaviour and won't be fixed before Apollo
More Details
Ultimately this is caused by the maxPageSize property and the fact that AMQ will only apply selection criteria to messages in memory. Generally these are message selectors (property = value), but in my case they are JMSXGroupID=>Consumer assignments.
As messages are received by the queue they get paged into memory and placed into a collection (named pagedInPendingDispatch in the source). To dispatch messages AMQ will scan through this list of messages and try to find a consumer that will accept it. That includes checking the group id, message selector and prefetch buffer space. For our use case we aren't using message selectors but we are using groups. If no consumer can take the message then it is left in the collection and will be checked again at the next tick.
In order to stop the pagedInPendingDispatch collection from eating up all the resources available there is a suggested limit to the size of this queue configured via the maxPageSize property. This property isn't actually a maximum, it's more a hint as to whether, under normal conditions, new message arrivals should be paged in memory or paged to disk.
With these two pieces of information and a slow consumer it turns out that eventually all the messages in the pagedInPendingDispatch collection end up only being consumable by the slow consumer, and hence the collection effectively gets blocked and no other messages get dispatched. This explains why the slow consumer wasn't affected by the 30s interval, it had maxPageSize messages waiting delivery already.
This doesn't explain why I was seeing the non-slow consumers receive messages every 30s though. As it turns out, paging messages into memory has two modes, normal and forced. Normal follows the process outlined above where the size of the collection is compared to the maxPageSize property, when forced, however, messages are always paged into memory. This mode exists to allow you to browse through messages that aren't in memory. As it happens this forced mode is also used by the expiry mechanism to allow AMQ to expire messages that aren't in memory.
So what we have now is a collection of messages in memory that are all targeted for dispatch to the same consumer, a consumer that won't accept them because it is slow or blocked. We also have a backlog of messages awaiting delivery to all consumers. Every expireMessagesPeriod milliseconds a task runs that force pages messages into memory to check if they should be expired or not. This adds those messages onto the pages in collection which now contains maxPageSize messages for the slow consumer and N more messages destined for any consumer. Those messages get delivered.
QED.
References
Ticket referring to this issue but for message selectors instead
Docs relating to the configuration properties
Somebody else with this issue but for selectors
I have console application which connects to activemq topics. Abount 10 messages per second are published on each topic. After some time monitored that the application memory is increasing and when all the memory is used the application crashes.
See the dump below. Why is ActiveMQTopicSubsctiber using so much heap? Also it is not visible but the ListEntries are about~14 000 (which means 14k messages).
http://imageshack.us/photo/my-images/404/amqmemoryproblem.png
A couple of things to possibly check for:
In your subscriber are you positive that the messages from the topic actually being consumed?
What is your prefetchLimit specified as?
If holding messages in memory continues to be a problem, you should consider configuring ActiveMQ to use file cursors. The use of file cursors tells ActiveMQ to spool messages to disk instead of holding them in memory.
Concerning ActiveMQ: I have a scenario where I have one producer which sends small (around 10KB) files to the consumers. Although the files are small, the consumers need around 10 seconds to analyze them and return the result to the producer. I've researched a lot, but I still cannot find answers to the following questions:
How do I make the broker store the files (completely) in a queue?
Should I use ObjectMessage (because the files are small) or blob messages?
Because the consumers are slow processing, should I lower their prefetchLimit or use a round-robin dispatch policy? Which one is better?
And finally, in the ActiveMQ FAQ, I read this - "If a consumer receives a message and does not acknowledge it before closing then the message will be redelivered to another consumer.". So my question here is, does ActiveMQ guarantee that only 1 consumer will process the message (and therefore there will be only 1 answer to the producer), or not? When does the consumer acknowledge a message (in the default, automatic acknowledge settings) - when receiving the message and storing it in a session, or when the onMessage handler finishes? And also, because the consumers are so slow in processing, should I change some "timeout limit" so the broker knows how much to wait before giving the work to another consumer (this is kind of related to my previous questions)?
Not sure about others, but here are some thoughts.
First: I am not sure what your exact concern is. ActiveMQ does store messages in a data store; all data need NOT reside in memory in any single place (either broker or client). So you should actually be good in that regard; earlier versions did require that all ids needed to fit in memory (not sure if that was resolved), but even that memory usage would be low enough unless you had tens of millions of in-queue messages.
As to ObjectMessage vs blob; raw byte array (blob) should be most compact representation, but since all of these get serialized for storage, it only affects memory usage on client. Pre-fetch mostly helps with access latency; but given that they are slow to process, you probably don't need any prefetching; so yes, either set it to 1 or 2 or disable altogether.
As to guarantees: best that distributed message queues can guarantee is either at-least-once (with possible duplicates), or at-most-once (no duplicates, can lose messages). It is usually better to take at-least-once, and make clients to de-duping using client-provided ids. How acknowledgement is sent is defiend by JMS specification so you can read more about JMS; this is not ActiveMQ specific.
And yes, you should set timeout high enough that worker typically can finish up work, including all network latencies. This can slow down re-transmit of dropped messages (if worked dies), but it is probably not a problem for you.