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
Related
How do you sync data between two processes (say client and server) in real time over network?
I have various documents/datasets constructed on the server, which are downloaded and displayed by clients. Once downloaded, the document receives continuous updates in order to remain fresh.
It seems to be a simple and commonly occurring concept, but I cannot find any tools that provide this level of abstraction. I am not even sure what I am looking for. Perhaps there is a similar concept with solid tool support? Perhaps there is a chain of different tools that must be put together? Here's what I have considered so far:
I am required to propagate every change in a single hop (0.5 RTT), which rules out polling (typically >10 RTT) and cache invalidation techniques (1.5 RTT).
Data replication and simple notification broadcasts are not an option, because there is too much data and too many changes. Clients must be able to select specific documents to download and monitor for changes.
I am currently using message passing pattern, which does the job, but it is hopelessly unproductive. It works at way too low level of abstraction. It is laborious, error-prone, and it doesn't scale well with increasing application complexity.
HTTP and other RPC-like techniques are good for the initial fetch, but they encourage polling for subsequent synchronization. When performing reverse requests (from data source to data consumer), change notifications are possible, but it's even more complicated than message passing.
Combining RPC (for the initial fetch) with message passing (for updates) turned out to be a nightmare due to the complexity involved in coordinating communication over the two parallel connections as well as due to the impedance mismatch between the two paradigms. I need something unified.
WebSocket & Comet are popular methods to implement change notification, but they need additional libraries to be productive and I am not aware of any libraries suitable for my application.
Message queues merely put an intermediary on the network while maintaining the basic message passing pattern. Custom message filters/routers allow me to get closer to the live document concept, but I feel like I am implementing custom middleware layer on top of the MQ.
I have tons of additional requirements (native observable data structure API on both ends, incremental updates, custom message filters, custom connection routing, cross-platform, robustness & scalability), but before considering those requirements, I need to find some tools that at least attempt to do what I need. I am trying to avoid in-house frameworks for the standard reasons - cost, time to market, long-term maintenance, and keeping developers happy.
My conclusion at the moment is that there is no such live document synchronization framework. In-house solution is the way to go, but many existing components can be used as part of the solution.
It is pretty simple to layer live document logic on top of WebSocket or any other message passing platform. Server just sends the document as a separate message when the connection is initiated and then after every change. Automated reconnection and some connection monitoring must be added to handle network failures.
Serialization at both ends is a separate problem targeted by many existing libraries. Detecting changes in server-side data structures (needed to initiate push) is yet another separate problem that has its own set of patterns and tools. Incremental updates and many other issues can be solved by intermediaries intercepting the connection.
This approach will work with current technology at the cost of extensive in-house glue code. It can be incrementally substituted with standard components as they become available.
WebSocket already includes resource URIs, routing, and a few other nice features. Useful intermediaries and libraries will likely emerge in the future. HTTP with text/event-stream MIME type is a possible future alternative to WebSocket. The advantage of HTTP is that existing tools can be reused with little modification.
I've completely thrown away the pattern of combining RPC pull with separate push channel despite rich tool support. Pushing everything in 0.5 RTT requires the push channel to use exactly the same technology as the pull channel, i.e. reverse RPC. Reverse RPC is like message passing except it introduces redundant returns, throws away useful connection semantics, and makes it hard to insert content-agnostic intermediaries into the stream.
I am looking for any authoritative articles on Service Broker best practices.
In particular, I am looking for the following topics (I know the answers, but have to find documents that support the knowledge):
queues in the same database
message
size
systems where the message is just a pointer and data is retrieved from tables
instrumentation - auditing Service Broker applications
TIA
systems where the message is just a pointer and data is retrieved from tables
This is not a Service Broker application, is just a queueing application. Service Broker was designed primarily for distributed applications, communication (networking, security, routing, retries) is a major component. If you only send messages as pointers and the data is in tables the distributed nature of SSB falls apart. The litmus test is "can I move my service onto another server and the application continues to work after I fix the routing?". If the answer is Yes then you're using SSB the way it was designed. If is No it meas you're only interested in queues.
The problem with using SSB as a 'dumb queue' is that is a very expensive queue (just think at the extra writes required on each message due to conversations and conversation groups). RECEIVE statement is expensive and basically a black box from optimization pov. You could optimize a table used as a queue a lot better than what you can do with an SSB service/queue. I reckon that SSB has an ace up its sleeves which makes it attractive even when used as a local queue, namely the internal activation capabilities. One may say that activation cannot be replaced with anything else (I agree, it cannot), but one must be aware of the cost and balance the pros and cons.
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.
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
I am currently evaluating message queue systems and RabbitMq seems like a good candidate, so I'm digging a little more into it.
To give a little context I'm looking to have something like one exchange load balancing the message publishing to multiple queues. I don't want to replicate the messages, so a fanout exchange is not an option.
Also the reason I'm thinking of having multiple queues vs one queue handling the round-robin w/ the consumers, is that I don't want our single point of failure to be at the queue level.
Sounds like I could add some logic on the publisher side to simulate that behavior by editing the routing key and having the appropriate bindings in place. But that's kind of a passive approach that wouldn't take the pace of the message consumption on each queue into account, potentially leading to fill up one queue if the consumer applications for that queue are dead.
I was looking for a more pro-active way from the exchange entity side, that would decide where to send the next message based on each queue size or something of that nature.
I read about Alice and the available RESTful APIs but that seems kind of a heavy duty solution to implement fast routing decisions.
Anyone knows if round-robin between the exchange the queues is feasible w/ RabbitMQ then? Thanks.
Exchanges are generally stateless in the AMQP model, though there have been some recent experiments in stateful exchanges now that there's both a system for managing RabbitMQ plugins and for providing new experimental exchange types.
There's nothing that does quite what you want, I don't think, though I'm not completely sure I understand the requirement. Aside from the single-point-of-failure point, would having a single queue with workers reading from it solve your problem? If so, then your problem reduces to configuring RabbitMQ in an HA configuration that permits you to use that solution. There are a couple of approaches to doing that: either use HALinux and a shared store to get active/passive HA with quick failover, or set up more than one parallel broker and deduplicate on the client, perhaps using redis or similar to do so.
I suggest asking your question again on the rabbitmq-discuss mailing list, where more people will be able to offer suggestions, and where the discussion can be archived for posterity.
Agree with Tony on the approach.
Here is a 'mashup' of RabbitMQ, Redis that you could use instead of rolling your own -
http://xing.github.com/beetle/
One built in way you can do a form of sharing a form exchange to queues, but not exactly round robin, is Consistent Hashing. rabbitmq_consistent_hash_exchange
How too
https://medium.com/#eranda/rabbitmq-x-consistent-hashing-with-wso2-esb-27479b8d1d21
Paper to explain, it puts queues at a weighted distribution on a circle and then by sending random routing key it will send to the closest queue.
http://www8.org/w8-papers/2a-webserver/caching/paper2.html