This two images are from http://zguide.zeromq.org/page:all.
What is the difference between this two pattern if we ignore sink in push-pull pattern ?
Is there a difference in how a message gets transfer, if yes what is the difference ?
The difference is that a PUB socket sends the same message to all subscribers, whereas PUSH does a round-robin amongst all its connected PULL sockets.
In your example, if you send just a single message from the root, then all the subscribers will receive it (barring slow subscribers, etc.) but only 1 worker.
The pub/sub pattern is used for wide message distribution according to topics. The push/pull pattern is really a pipelining mechanism. Your push/pull example seems to be attempting to do load-balancing, which is fine, but req/rep might be better suited to that due to other issues.
It looks like the "issues" here are described in the same part of the 0MQ guide you got the image from : push/pull ventilator example
Related
I am working for a while with ZeroMQ. I read already some whitepapers and a lot from the guide, but one question remained open to me:
Lets say we use PUB-SUB.
Where or on which system are the messaging queues? On the publisher system side, on the subscriber system side or something in between?
Sorry for the maybe stupid question.
This picture is from the Broker vs. Brokerless whitepaper.
Every zeromq socket has both send and recv queues (The limits are set via high water mark).
In the case of a brokerless PUB/SUB the messages could be queued on the sender or the receiver.
Example:
If there is network congestion the sender may queue on its send queue
If the receiver is consuming messages slower than they arrive they will be queued on the receiver recv queue
If the queues reach the high water mark the messages will be lost.
Q : Where or on which system are the messaging queues?
The concept of the Zen-of-Zero, as built-into ZeroMQ uses smart and right enough approches, on a case by case principle.
There cases, where there are no-Queues, as you know them, at all :
for example, the inproc:// transport-class has no Queue, as one may know 'em, as there are just memory-regions, across which the messages are put and read-from. The whole magic thus appears inside the special component - the Context()-instance. There the message-memory-mapping takes place. The inproc:// case is a special case, where no I/O-thread(s) are needed at all, as the whole process is purely memory-mapping based and the Context()-instance manipulates its internal states, so as to emulate both an externally provided abstraction of the Queue-alike behaviour and also the internal "Queue"-management.
Others, similarly, operate localhost-located internal Queue(s) endpoints :
for obvious reason, as the ZeroMQ is a broker-less system, there is no "central"-place and all the functionality is spread across the participating ( coordinated and cooperating ) nodes.
Either one of the Queue-ends reside inside the Context()-instances, one in the one-side's localhost-itself, the other in the "remote"-host located Context()-instance, as was declared and coordinated during building of the ZMTP/RFC-specified socket-archetype .bind()/.connect() construction. Since a positive acknowledgement was made for such a ZMTP-specific-socket, the Queue-abstraction ( implemented in a distributed-system-manner ) holds till such socket does not get .close()-ed or the Context()-instance did not get forcefully or by a chance .term()-ed.
For these reasons, the proper capacity sizings are needed, as the messages may reside inside the Context()-operated memory before it gets transported across the { network | ipc-channel }-mediated connection ( on the .send()-side ) or before being .recv()-ed ( from inside the remote Context()-instance ) by the remote application-code for any further use of the message-payload data ( a Zero-copy message-data management is possible, yet not all use-cases indeed use this mode for avoiding replicated memory-allocations and data-transfer costs ).
I'm thinking about system that will notify multiple consumers about events happening to a population of objects. Every subscriber should be able to subscribe to events happening to zero or more of the objects, multiple subscribers should be able to receive information about events happening to a single object.
I think that some message queuing system will be appropriate in this case but I'm not sure how to handle the fact that I'll have millions of the objects - using separate topic for every of the objects does not sound good [or is it just fine?].
Can you please suggest approach I should should take and maybe even some open source message queuing system that would be reasonable?
Few more details:
there will be thousands of subscribers [meaning not plenty of them],
subscribers will subscribe to tens or hundreds of objects each,
there will be ~5-20 million of the objects,
events themselves dont have to carry any message. just information that that object was changed is enough,
vast majority of objects will never be subscribed to,
events occur at the maximum rate of few hundreds per second,
ideally the server should run under linux, be able to integrate with the rest of the ecosystem via http long-poll [using node js? continuations under jetty?].
Thanks in advance for your feedback and sorry for somewhat vague question!
I can highly recommend RabbitMQ. I have used it in a couple of projects before and from my experience, I think it is very reliable and offers a wide range of configuraions. Basically, RabbitMQ is an open-source ( Mozilla Public License (MPL) ) message broker that implements the Advanced Message Queuing Protocol (AMQP) standard.
As documented on the RabbitMQ web-site:
RabbitMQ can potentially run on any platform that Erlang supports, from embedded systems to multi-core clusters and cloud-based servers.
... meaning that an operating system like Linux is supported.
There is a library for node.js here: https://github.com/squaremo/rabbit.js
It comes with an HTTP based API for management and monitoring of the RabbitMQ server - including a command-line tool and a browser-based user-interface as well - see: http://www.rabbitmq.com/management.html.
In the projects I have been working with, I have communicated with RabbitMQ using C# and two different wrappers, EasyNetQ and Burrow.NET. Both are excellent wrappers for RabbitMQ but I ended up being most fan of Burrow.NET as it is easier and more obvious to work with ( doesn't do a lot of magic under the hood ) and provides good flexibility to inject loggers, serializers, etc.
I have never worked with the amount of amount of objects that you are going to work with - I have worked with thousands ( not millions ). However, no matter how many objects I have been playing around with, RabbitMQ has always worked really stable and has never been the source to errors in the system.
So to sum up - RabbitMQ is simple to use and setup, supports AMQP, can be managed via HTTP and what I like the most - it's rock solid.
Break up the topics to carry specific events for e.g. "Object updated topic" "Object deleted"...So clients need to only have to subscribe to the "finite no:" of event based topics they are interested in.
Inject headers into your messages when you publish them and put intelligence into the clients to use these headers as message selectors. For eg, client knows the list of objects he is interested in - and say you identify the object by an "id" - the id can be the header, and the client will use the "id header" to determine if he is interested in the message.
Depending on whether you want, you may also want to consider ensuring guaranteed delivery to make sure that the client will receive the message even if it goes off-line and comes back later.
The options that I would recommend top of the head are ActiveMQ, RabbitMQ and Redis PUB SUB ( Havent really worked on redis pub-sub, please use your due diligance)
Finally here are some performance benchmarks for RabbitMQ and Redis
Just saw that you only have few 100 messages getting pushed out / sec, this is not a big deal for activemq, I have been using Amq on a system that processes 240 messages per second , and it just works fine. I use a thread pool of workers to asynchronously process the messages though . Look at a framework like akka if you are in the java land, if not stick with nodejs and the cool Eco system around it.
If it has to be open source i'd go for ActiveMQ, and an application server to provide the JMS functionality for topics and it has Ajax Support so you can access them from your client
So, you would use the JMS infrastructure to publish the topics for the objects, and you can create topis as you need them
Besides, by using an java application server you may be able to take advantages from clustering, load balancing and other high availability features (obviously based on the selected product)
Hope that helps!!!
Since your messages are very small might want to consider MQTT, which is designed for small devices, although it works fine on powerful devices as well. Key consideration is the low overhead - basically a 2 byte header for a small message. You probably can't use any simple or open source MQTT server, due to your volume. You probably need a heavy duty dedicated appliance like a MessageSight to handle your volume.
Some more details on your application would certainly help. Also you don't mention security at all. I assume you must have some needs in this area.
Though not sure about your work environment but here are my bits. Can you identify each object with unique ID in your system. If so, you can have a topic per each event type. for e.g. you want to track object deletion event, object updation event and so on. So you can have topic for each event type. These topics would be published with Ids of object whenever corresponding event happened to the object. This will limit the no of topics you needed.
Second part of your problem is different subscribers want to subscribe to different objects. So not all subscribers are interested in knowing events of all objects. This problem statement scoped to message selector(filtering) mechanism provided by messaging framework. So basically you need to seek on what basis a subscriber interested in particular object. Have that basis as a message filtering mechanism. It could be anything: object type, object state etc. So ultimately your system would consists of one topic for each event type with someone publishing event messages : {object-type:object-id} information. Subscribers could subscribe to any topic and with an filtering criteria.
If above solution satisfy, you can use any messaging solution: activeMQ, WMQ, RabbitMQ.
How can we distribute work via RabbitMQ such that worker pools can subscribe to work messages based on differing (but frequently overlapping) criteria from each other but such that when a message is routed that matches to multiple worker pools, only one worker will pick up the job?
Simplified example:
We have host1 and host2.
Host1 handles jobs of classA and classB; host2 handles jobs of classB and classC.
If we route a job of
classA, only host1 will pick it up; if we route a job of classB,
either host1 or host2 will pick it up (based on their current load /
first available) but never both.
It would seem that we need to use a topic exchange, as our routing criteria is complex and using wildcards gives us the type of flexible matching we want.
However:
If we use the same name for the worker pool queue (say “worker-jobs”) we get the desired work splitting out to arbitrary matching workers, but every worker subscribing to the named queue seems to infect the other workers with each other’s routing criteria as they bind it. I.e. the binding of the routing key seems to be at the central queue name level not on a connection-to-queue basis.
If we use different queue names for each worker pool connection (say “poolA-jobs” and “poolB-jobs”) to the same exchange then we get the desired behavior with the different routing criteria maintained between pools but a job coming in that can match to both poolA and poolB gets routed to both of them (albeit only to one worker in each).
Notes:
I’ve spared you the details of why but suffice to say we have an existing multi-petabyte distributed search application that needs response times < 50ms. We already achieve this with our own custom routing hub but we’d like to replace this with RabbitMQ as its performance is attractive (as is retiring homemade code that overlaps with general purpose community projects) if we can get the sophisticated routing we need.
We use Python
Disco isn’t viable for many reasons, too numerous to go into.
It doesn’t have to be RabbitMQ but the performance needs to be as good. ØMQ looks very interesting and like it might provide both the flexibility and the performance but we’re already using RabbitMQ and after wading through the first half of the colorfully written ØMQ guide I’m still not sure if it will support the routing we need but it does look like we’ll have to pretty much write a broker to do it.
We actually have the luxury of knowing which hosts are capable of serving which jobs, so we can do something like have host1 subscribe to #.host1.# and host2 to #.host2.#. Then when we route a classB message, we can give it a key of host1.host2 to indicate which backends are acceptable for service. This simplifies the routing rules but still doesn’t overcome the problem described.
I've been evaluating messaging technologies for my company but I've become very confused by the conceptual differences between a few terms:
Pub/Sub vs Multicast vs Fan Out
I am working with the following definitions:
Pub/Sub has publishers delivering a separate copy of each message to
each subscriber which means that the opportunity to guarantee delivery exists
Fan Out has a single queue pushing to all listening
clients.
Multicast just spams out data and if someone is listening
then fine, if not, it doesn't matter. No possibility to guarantee a client definitely gets a message.
Are these definitions right? Or is Pub/Sub the pattern and multicast, direct, fanout etc. ways to acheive the pattern?
I'm trying to work the out-of-the-box RabbitMQ definitions into our architecture but I'm just going around in circles at the moment trying to write the specs for our app.
Please could someone advise me whether I am right?
I'm confused by your choice of three terms to compare. Within RabbitMQ, Fanout and Direct are exchange types. Pub-Sub is a generic messaging pattern but not an exchange type. And you didn't even mention the 3rd and most important Exchange type, namely Topic. In fact, you can implement Fanout behavior on a Topic exchange just by declaring multiple queues with the same binding key. And you can define Direct behavior on a Topic exchange by declaring a Queue with * as the wildcard binding key.
Pub-Sub is generally understood as a pattern in which an application publishes messages which are consumed by several subscribers.
With RabbitMQ/AMQP it is important to remember that messages are always published to exchanges. Then exchanges route to queues. And queues deliver messages to subscribers. The behavior of the exchange is important. In Topic exchanges, the routing key from the publisher is matched up to the binding key from the subscriber in order to make the routing decision. Binding keys can have wildcard patterns which further influences the routing decision. More complicated routing can be done based on the content of message headers using a headers exchange type
RabbitMQ doesn't guarantee delivery of messages but you can get guaranteed delivery by choosing the right options(delivery mode = 2 for persistent msgs), and declaring exchanges and queues in advance of running your application so that messages are not discarded.
Your definitions are pretty much correct. Note that guaranteed delivery is not limited to pub/sub only, and it can be done with fanout too. And yes, pub/sub is a very basic description which can be realized with specific methods like fanout, direct and so on.
There are more messaging patterns which you might find useful. Have a look at Enterprise Integration Patterns for more details.
From an electronic exchange point of view the term “Multicast” means “the message is placed on the wire once” and all client applications that are listening can read the message off the “wire”. Any solution that makes N copies of the message for the N clients is not multicast. In addition to examining the source code one can also use a “sniffer” to determine how many copies of the message is sent over the wire from the messaging system. And yes, multicast messages are a form the UDP protocol message. See: http://en.wikipedia.org/wiki/Multicast for a general description. About ten years ago, we used the messaging system from TIBCO that supported multicast. See: https://docs.tibco.com/pub/ems_openvms_c_client/8.0.0-june-2013/docs/html/tib_ems_users_guide/wwhelp/wwhimpl/common/html/wwhelp.htm#context=tib_ems_users_guide&file=EMS.5.091.htm
We've been using SysV Message Queue for our distributed data processing system for over 15 years. For some reason, we want to replace it with newer Message Queue mechanism. Is there any suggestions?
Requirements:
Fast response, minimizing message queue system overhead
Multiple client language library support, mainly c, c# and java
Can do some HA configuration to prevent SPOF
Have logging ability to check who sends message and who receives message
I've found Apache ActiveMQ and RabbitMQ, but it seems RabbitMQ lacks of stable C client library support?
While I have not used it personally, the toolkit from 0MQ is quite impressive.
It seems to meet all of your criteria, although #4 you would have to implement yourself, but that seems straightforward.
My question back would be why you are moving away from SysV Message Queue? The "for some reason" is a disconcerting statement.
That said, there are many excellent messaging products out there, having a useful set of selection criteria is key.
I would suggest extending your requirements list a bit, then doing website bench-marking against that list. Take the top two or three only, and do some real-world project spikes (or a bake-off if you prefer the term) to give you some actual feedback on which to base your final decision.
Good Luck