The first time I skimmed the zeromq docs, I assumed that the sender high watermark was there to ensure that the sender did not get too far ahead of the receiver. Now that I'm looking at it more carefully, it seems that this can't possibly be true, since the wire protocol doesn't have any concept of ACKs so the sender can't know whether the receiver is keeping up or is way behind. After staring at jeromq code in the debugger for way too long, it seems that the watermark is actually a purely "within-same-process" mechanism to ensure that the application thread that's writing to the ZMQ socket does not get too far ahead of the background thread that's responsible for taking messages off the ZMQ socket and writing bytes into the OS's TCP socket.
It seems like a rather fringe thing to worry about, relative to how much attention it's given in the docs. It doesn't even seem like a great way to control memory usage, because if you have a high water mark of 10, then 15 messages of 2kb each is not allowed, but 5 messages of 100 megs each is allowed, so things are still pretty un-predictable.
Am I understanding all this correctly or am I hopelessly confused.
I think that another thing that says it's not to prevent a sender getting too far ahead of the receiver is that if one set the HWM to 0, that's taken as infinity not actually zero. For 0 to mean zero, it'd have to have some too-ing and fro-ing with the receiver to know whether the socket was actually empty throughout the whole connection.
I wish that 0 did mean zero, because then ZeroMQ could implement both Actor Model and Communicating Sequential Processes architectures. But it doesn't, so it can't.
Possible Uses
None the less, a potential useful aspect is related to the fact that ZeroMQ is Actor Model. Suppose one were sending messages, and it kind of mattered whether or not those messages got through. In the situation where the link has collapsed (something that ZeroMQ's heartbeat can tell you, pretty quickly), messages already sent are potentially lost forever. However, if the HWM is being used to throttle the rate of messages being sent by the application, then the number of lost messages when the link breaks is minimised.
Obviously with CSP - the perfect architecture so far as I'm concerned! - you lose no messages (because the acts of sending and receiving are an execution rendezvous; the send won't complete until the receive has also completed).
What I have done in the past is to queue up messages for transmission in the sending application, sending them as and when the socket / connection can ingest them. Having the outbound message queue in the sending application's control (instead of in ZeroMQ's control) means that sender state can potentially get ahead of the transfer of messages, but still recover easily from a network connection fault.
I have written systems where a sender has a choice of two pathways to send messages through - prime and spare - and if the link to prime has collapsed the sender continues to send to spare instead. Having queued the messages inside the application and not in the socket allows the sender's state can get ahead of the actual transfer of messages, knowing that if a link goes down it's still got all the unsent outboud messages that have been generated in the meantime. These can then be directed at spare instead, without having to rewind the sender's internal state (which could be really tricky) to the last known successful transfer.
Something like that, anyway.
"Why not send to both prime and spare anyway?" is a valid question. Well, sometimes things can be complicated...
Related
How would one cancel the last sent message ?
I have this set up
The idea is that the client can ask for different types of large data.
The server reads the request from the client and answers an acknowledgement.
Once its data is ready, it pushes it through the other socket.
This enables queueing task on the server side when multiple clients are connected.
However, if the client decides that it does not need the data anymore, it can send a cancel message to the server.
I'm using asyncio.Queue for queueing messages, so I can easily empty the queue, however, I don't know how to drop a message that is in the push/pull pipe to free up the channel?
The kill switch example (Figure 19 - Parallel Pipeline with Kill Signaling) in https://zguide.zeromq.org/docs/chapter2/ is used to end the process. I just want to cancel it.
My idea was to close the socket on the server side and reopen it, but even with linger set to 0, the messages are not dropped.
EDIT: The messages are indeed dropped, but I feel the solution is wrong.
It doesn't really make any sense for ZeroMQ itself to have such a feature.
Suppose that it did have a cancel message feature. For it to operate as expected, you would be critically dependent on the speed of the network. You might develop on a slow network and their you have the time available to decide to cancel, submit the request and for that to take effect before anything has moved anywhere. But on a fast network you won't.
ZeroMQ is a bit like the post office. Once you have posted a letter, they are going to deliver it.
Other issues for a library developer would include how messages are identified, who can cancel a message, etc? It would get very complex for the library to do it and cater for all possible use cases, so it's not unreasonable that they've left such things as an exercise for the application developers.
Chop the Responses Up
You could divide the responses up into smaller messages, send them at some likely rate (proportionate to the network throughput) and check to see if a cancellation has been received before sending each chunk.
It's a bit fiddly, you'd need to know what kind of rate to send the smaller messages so that you don't starve the network, but don't over do it either.
Or, Convert to CSP
The problem lies in ZeroMQ implementing Actor Model, where the transport buffers messages. What you need is Communicating Sequential Processes, which does not buffer messages. You can implement this quite easily on top of ZeroMQ, basically all you need to do is have a two way message exchange going on basically like:
Peer1->Peer2: I'd like to send you a message
time passes
Peer2->Peer1: Okay send a message
Peer1->Peer2: Here is the message
time passes
Peer2->Peer1: I have received the message
end
And in doing this the peers would block, ie peer 1 does nothing else until it gets peer 2's final response.
This feels clunky, but it's what you have to do to reign in an Actor Model system and control where your messages are at any point in time. It's slower because there's more too-ing and fro-ing going on between the peers (in systems like Transputers, this was all done down at the electronic level, so it wasn't an encumberance on software).
The blocking can be a blessing, if throughput matters. Basically, if you find the sender is being blocked too much, that just means you haven't got enough receivers for the tasks they're performing. Actor Model can deceive, because buffering in the network / actor model implementation can temporarily soak up an excess of messages, adding a bit of latency that goes unnoticed.
Anyway, this way you can have a mechanism whereby the flow of messages is fully managed within the application, and not within the ZeroMQ library. If a client does send a "cancel my last request" message (using the above mechanism to send it), that either arrives before the reponse has started to be sent, or after the response has already been delivered to the client (using the mechanism above to send it). There is no intermediate state where a response is already on the way, but out of control of the applications.
CSP is a mode that I'd dearly like ZeroMQ to implement natively. It nearly does, in that you can control the socket high water marks. Unfortunately, a high water mark of 0 means "inifinite", not zero.
CSP itself is a 1970s idea, that saw some popularity and indeed silicon in the 1980s, early 1990s (Inmos, Transputers, Occam, etc) but has recently made something of a comeback in languages like Rust, Go, Erlang. There's even a MS-supplied library for .NET that does it too (not that they call it CSP).
The really big benefit of CSP is that it is algebraically analysable - a design can be analysed and proven to be free of deadlock, without having to do any testing. However, with Actor model systems you cannot do that, and testing will not confirm a lack of problems either. Complex, circular message flows in Actor model can easily lead to deadlock, but that might not occur until the network between computers becomes just a tiny bit busier. Deadlock can happen in CSP too, but it's basically guaranteed to happen every time, if the system has accidentally been architected to deadlock. This shows up in testing quite readily (so at least you know early on!).
As I alluded to early, CSP also doesn't deceive you into thinking there is enough compute resources in a system. If a sender has a strict schedule to keep, and the recipient(s) aren't keeping up, the sender ends up being blocked trying to send instead of waiting for fresh input. It's easy to detect that the real time requirement has not been met. Whereas with Actor model, the send launches messages off into some buffer, and so long as the receiver(s) on average keeps up, all appears to be OK. However, you have no visibility of whether messages are building up inside the (in this case) ZeroMQ's own buffers, so there is little notice of a trending problem in the overall system.
Since it does not seem to be possible to query/inspect the underlying ZeroMQ queues/buffers sockets to see how much they are utilized, is there some way to detect when a message is dropped due to full buffers in a Publisher socket when sent/queued?
For example, if the publisher queue is full, the zmq_send operation will simply drop the message.
Basically, what I want to achieve is a way to detect situations where the queues are getting stressed and/or full to be able to (later on) tune the solution to work better. One alternative way would be to add a sequence number to each message and do a simple calculation in the subscriber but I can never be sure that a message was lost due to full buffers in the publisher.
There is an example for this in the ZeroMQ Guide (which you should read and digest if you want to use 0MQ happily): http://zguide.zeromq.org/page:all#Slow-Subscriber-Detection-Suicidal-Snail-Pattern
The mechanism is as you answered yourself, to add a sequence number in the message, and allow the subscriber to detect gaps and take appropriate action. For most pubsub scenarios you can raise the default HWM, which is 1,000, to something much higher; it depends on your average message size.
I know this is an old post but here is what I did when recently facing the same issue.
I opted to use a DEALER/ROUTER and set the ZMQ_SNDHWM option to 1. Also I provided the timeout parameter on each zmq_send(). The timeout could be anything between 10 ms to 3 seconds, depending on what your scenario is ( a local or remote send ).
If the message is not sent within the timeout or the send-buffer is full the zmq_send() will return false. That enabled me to set up a retry queue in front of zmq. I know it's not a perfect solution but for me it worked just fine. What puzzles me though is the meaning of true/false returned by the DEALER-socket zmq_send(). I have not been able to find the answer to that question. Whether it indicates that the message has been buffered or that the message has been delivered to the ROUTER has eluded me. In my case I got the results needed anyway.
Just for the record this was done using netmq but I guess it applies to ZeroMQ as well.
I do agree wtih james though. ZeroMQ ( and netmq ) should at least provide a way to inspect the queue ( and get the messages out ) and also a way to tell the various sockets not to drop messages. The best option would be to send messages not delivered in timely fashion according to the configured options to some sort of deadletter queue. The deadletter queue could then be handled separately.
I have created a client/server program, the client starts
an instance of Writer class and the server starts an instance of
Reader class. Writer will then write a DATA_SIZE bytes of data
asynchronously to the Reader every USLEEP mili seconds.
Every successive async_write request by the Writer is done
only if the "on write" handler from the previous request had
been called.
The problem is, If the Writer (client) is writing more data into the
socket than the Reader (server) is capable of receiving this seems
to be the behaviour:
Writer will start writing into (I think) system buffer and even
though the data had not yet been received by the Reader it will be
calling the "on write" handler without an error.
When the buffer is full, boost::asio won't fire the "on write"
handler anymore, untill the buffer gets smaller.
In the meanwhile, the Reader is still receiving small chunks
of data.
The fact that the Reader keeps receiving bytes after I close
the Writer program seems to prove this theory correct.
What I need to achieve is to prevent this buffering because the
data need to be "real time" (as much as possible).
I'm guessing I need to use some combination of the socket options that
asio offers, like the no_delay or send_buffer_size, but I'm just guessing
here as I haven't had success experimenting with these.
I think that the first solution that one can think of is to use
UDP instead of TCP. This will be the case as I'll need to switch to
UDP for other reasons as well in the near future, but I would
first like to find out how to do it with TCP just for the sake
of having it straight in my head in case I'll have a similar
problem some other day in the future.
NOTE1: Before I started experimenting with asynchronous operations in asio library I had implemented this same scenario using threads, locks and asio::sockets and did not experience such buffering at that time. I had to switch to the asynchronous API because asio does not seem to allow timed interruptions of synchronous calls.
NOTE2: Here is a working example that demonstrates the problem: http://pastie.org/3122025
EDIT: I've done one more test, in my NOTE1 I mentioned that when I was using asio::iosockets I did not experience this buffering. So I wanted to be sure and created this test: http://pastie.org/3125452 It turns out that the buffering is there event with asio::iosockets, so there must have been something else that caused it to go smoothly, possibly lower FPS.
TCP/IP is definitely geared for maximizing throughput as intention of most network applications is to transfer data between hosts. In such scenarios it is expected that a transfer of N bytes will take T seconds and clearly it doesn't matter if receiver is a little slow to process data. In fact, as you noticed TCP/IP protocol implements the sliding window which allows the sender to buffer some data so that it is always ready to be sent but leaves the ultimate throttling control up to the receiver. Receiver can go full speed, pace itself or even pause transmission.
If you don't need throughput and instead want to guarantee that the data your sender is transmitting is as close to real time as possible, then what you need is to make sure the sender doesn't write the next packet until he receives an acknowledgement from the receiver that it has processed the previous data packet. So instead of blindly sending packet after packet until you are blocked, define a message structure for control messages to be sent back from the receiver back to the sender.
Obviously with this approach, your trade off is that each sent packet is closer to real-time of the sender but you are limiting how much data you can transfer while slightly increasing total bandwidth used by your protocol (i.e. additional control messages). Also keep in mind that "close to real-time" is relative because you will still face delays in the network as well as ability of the receiver to process data. So you might also take a look at the design constraints of your specific application to determine how "close" do you really need to be.
If you need to be very close, but at the same time you don't care if packets are lost because old packet data is superseded by new data, then UDP/IP might be a better alternative. However, a) if you have reliable deliver requirements, you might ends up reinventing a portion of tcp/ip's wheel and b) keep in mind that certain networks (corporate firewalls) tend to block UDP/IP while allowing TCP/IP traffic and c) even UDP/IP won't be exact real-time.
I am looking looking for a message queue with these requirements. Couldn't find it; maybe the closest was the rabbitmq-lvc plugin (but I need the first value in the line to stick and stay in front).
Would anyone know a technology to support these?
message queue is FIFO
if a duplicate message is being enqueued, the message queue itself either rejects or drops it.
For example, producers put these three messages (each with a discriminator value) into the queue in this sequence: M1(discriminator=7654), M2(discriminator=2435), M3(discriminator=7654).
Now I want the message queue to see that M3 has the same discriminator value as M1 and thus drop/reject M3. Consumers receive only: M1, M2.
Thanks
Tom
I don't know the other transports but I know that WebSphere MQ doesn't do this and I believe that the explanation why would apply broadly across the category. I'd be very surprised to find that any messaging transport actually provides this. Here are a few reasons why:
Async messages are supposed to be atomic. Different vendors make their own accommodations for message affinity (a relationship between two or more messages) but as a rule, message affinity is to be avoided. Your use case not only requires the transport to deal with message affinity, but to do so over an indeterminate interval between related messages.
Message payload is a blob. For performance reasons, WMQ doesn't touch message payloads except for things like compression or code page conversion. Anything that requires parsing the message payload is a job for WebSphere Message Broker, DataPower or WebSphere ESB. I would expect any messaging transport which claims to be performant would face similar issues because parsing payloads results in longer code paths and non-linear performance degradation. The exception is message properties but WMQ uses these for selection only and I expect that is generally the case.
Stateless operation. As a transport, the state of the application may be stored in a persistent message but the state of the transport layer should not depend on the state of the application across different units of work. Again, an ESB type of product is best suited when you want to delegate management of some of the application state to the messaging layer and especially when such management spans many units of work.
Assured delivery. WMQ was designed to never lose your persistent message. If the app explicitly sets expiry the message might go away because the sender said it was OK to do so. If the message is non-persistent it might go away, but only in an exceptional condition and, again, because the sender said it was OK to do so. The use case you describe might result in a message going away not because the sender said it was OK, or even because the recipient said it was OK but because of an interaction with some unrelated 3rd party who happened to beat you to the queue with a duplicate value. What if that first message has an invalid header or code page problem and gets rolled back? What if I as an attacker spew out garbage messages with all possible 4-digit values for discriminator?
As I said, I don't know the other messaging products so there may be something out there which meets your requirement and if so I'll be interested to read about it. However in the event hat nobody replies, this post may shed some light on the reasons why.
I have a problem with a socket library that uses WSAASyncSelect to put the socket into asynchronous mode. In asynchronous mode the socket is placed into a non-blocking mode (WSAWOULDBLOCK is returned on any operations that would block) and windows messages are posted to a notification window to inform the application when the socket is ready to be read, written to etc.
My problem is this - when receiving a FD_READ event I don't know how many bytes to try and recv. If I pass a buffer thats too small, then winsock will automatically post another FD_READ event telling me theres more data to read. If data is arriving very fast, this can saturate the message queue with FD_READ messages, and as WM_TIMER and WM_PAINT messages are only posted when the message queue is empty this means that an application could stop painting if its receiving a lot of data and useing asynchronous sockets with a too small buffer.
How large to make the buffer then? I tried using ioctlsocket(FIONREAD) to get the number of bytes to read, and make a buffer exactly that large, BUT, KB192599 explicitly warns that that approach is fraught with inefficiency.
How do I pick a buffer size thats big enough, but not crazy big?
As far as I could ever work out, the value set using setsockopt with the SO_RVCBUF option is an upper bound on the FIONREAD value. So rather than call ioctlsocket it should be OK to call getsockopt to find out the SO_RCVBUF setting, and use that as the (attempted) value for each recv.
Based on your comment to Aviad P.'s answer, it sounds like this would solve your problem.
(Disclaimer: I have always used FIONREAD myself. But after reading the linked-to KB article I will probably be changing...)
You can set your buffer to be as big as you can without impacting performance, relying on the TCP PUSH flag to make your reads return before filling the buffer if the sender sent a smaller message.
The TCP PUSH flag is set at a logical message boundary (normally after a send operation, unless explicitly set to false). When the receiving end sees the PUSH flag on a TCP packet, it returns any blocking reads (or asynchronous reads, doesn't matter) with whatever's accumulated in the receive buffer up to the PUSH point.
So if your sender is sending reasonable sized messages, you're ok, if he's not, then you limit your buffer size such that even if you read into it all, you don't negatively impact performance (subjective).