I am doing a project of building a file transfer proxy using netty which should efficiently handle high concurrency.
Here is my structure:
Back Server, a normal file server just like Http(File Server) example on netty.io which receive and confirm a request and send out a file either using ChunkedBuffer or zero-copy.
Proxy, with both NioServerSocketChannelFactory and NioClientSocketChannelFactory, both using cachedThreadPool, listening to clients' requests and fetch the file from Back Server back to the clients. Once a new client is accepted, the new accepted Channel(channel1) created by NioServerSocketChannelFactory and waiting for the request. Once the request is received, the Proxy will establish a new connection to Back Server using NioClientSocketChannelFactory, and the new Channel(channel2) will send request to Back Server and deliver the response to the client. Each channel1 and channel2 using its own pipeline.
More simply, the procedure is
channel1 accepted
channel1 receives the request
channel2 connected to Back Server
channel2 send request to Back Server
channel2 receive response(including file) from Back Server
channel1 send the response got from channel2 to the client
once transferring is done, channel2 close and channel1 close on flush.(each client only send one request)
Since the required file can be big(10M), the proxy stops channel2.readable when channel1 is NOT writtable, just like example Proxy Server on netty.io.
With the above structure, each client has one accepted Channel and once it send a request it also corresponds to one client Channel until the transferring is done.
Then I use ab(apache bench) to fire up thousands of requests to the proxy and evaluate the request time. Proxy, Back Server and Client are three boxes on one rack which has no other traffic loaded.
The results are weird:
File Size 10MB, when concurrency is 1, connection delay is very small, but when concurrency increases from 1 to 10, top 1% connection delay becomes incredibly high, up to
3 secs. The other 99% are very small. When concurrency increases to 20, 1% goes to 8 sec. And it even causes ab to be timeout if concurrency is higher than 100. The 90% Processing delay are usually linear with the concurrency but 1% can abnormally goes very high under a random number of concurrency(varies over multiple testing).
File Size 1K, everything is fine at lease with concurrency below 100.
Put them on a single local machine, no connection delay.
Can anyone explain this issue and tell me which part is wrong? I saw many benchmarking online, but they are pure ping-pang testing rather than this large file transferring and proxy stuff. Hope this is interested to you guys :)
Thank you!
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After some source coding reading today, I found one place may prevent the new sockets to be accepted. In NioServerSocketChannelSink.bind(), the boss executor will call Boss.run(), which contains a for loop for accepting the incoming sockets. In each iteration of this loop, after getting the accepted channel, AbstractNioWorker.register() will be called which suppose to add new sockets into the selector running in worker executor. However, in
register(), a mutex called startStopLock has to be checked before worker executor invoked. This startStopLock is also used in AbstractNioWorker.run() and AbstractNioWorker.executeInIoThread(), both of which check the mutex before they invoke the worker thread. In other words, startStopLock is used in 3 functions. If it is locked in AbstractNioWorker.register(), the for loop in Boss.run() will be blocked which can cause incoming accept delay. Hope this ganna help.
Related
I have developed an application that does simple publish-subscrible messages with AWS IOT Core service.
As per the requirement of AWS IoT SDK, I need to call aws_iot_mqtt_yield() frequently.
Following is description of function aws_iot_mqtt_yield
Called to yield the current thread to the underlying MQTT client. This
time is used by the MQTT client to manage PING requests to monitor the
health of the TCP connection as well as periodically check the socket
receive buffer for subscribe messages. Yield() must be called at a
rate faster than the keepalive interval. It must also be called at a
rate faster than the incoming message rate as this is the only way the
client receives processing time to manage incoming messages. This is
the outer function which does the validations and calls the internal
yield above to perform the actual operation. It is also responsible
for client state changes
I am calling this function at a period of 1 second.
As it is sending PING on tcp connection, it creates too much internet data usage in long run when system is IDLE for most of the time.
My system works on LTE as well and paying more money for IDLE time is not acceptable for us.
I tried to extend period from 1 second to 30 seconds to limit our data usage but it adds 30 seconds latency in receiving messages from cloud.
My requirement is to achieve fast connectivity with low additional data usage in maintaining connection with AWS.
I have an async gRPC server for Windows written in C++. I’d like to detect the loss of connection to a client – whether a network connection is lost, or the client crashes, etc. I see references to the keepalive channel arguments, and I’ve tried various combinations of those settings, such as:
builder.AddChannelArgument(GRPC_ARG_KEEPALIVE_TIME_MS, 10000);
builder.AddChannelArgument(GRPC_ARG_KEEPALIVE_TIMEOUT_MS, 10000);
builder.AddChannelArgument(GRPC_ARG_KEEPALIVE_PERMIT_WITHOUT_CALLS, 1);
builder.AddChannelArgument(GRPC_ARG_HTTP2_MIN_RECV_PING_INTERVAL_WITHOUT_DATA_MS, 9000);
builder.AddChannelArgument(GRPC_ARG_HTTP2_BDP_PROBE, 1);
I've done some testing with a streaming RPC method. If I kill the client process and then try to send data to the client, the lost connection is detected. I don't actually even have to send data. I can set an Alarm object to trigger immediately and that causes the call handler to be cancelled. However, if I don't try to send data (or set an alarm) after killing the client process then there's no notification or callback that I've been able to find/enable. I must not have a complete understanding. So:
How does the detection of a lost connection manifest itself for the server? Is there a callback method, or notification of some type? My server doesn’t receive any errors; the completion queue’s ‘Next()’ method never returns, etc.
Does this detection work for both unary (call/response) and streaming methods?
Does the server detection of a lost connection work whether or not the client has implemented lost connection / keepalive logic?
Is there some method besides the keepalive channel arguments that is preferred?
Thanks - any help is appreciated.
You can use ServerContext::AsyncNotifyWhenDone() to get a notification when the request has been cancelled.
https://grpc.github.io/grpc/cpp/classgrpc__impl_1_1_server_context_base.html#a0f1289f31257e6dbef57bc901bd7b5f2
I have a web service that is made using spring, hibernate and c3p0. I also have a service wide cache(which has the results of requests ever made to the service) which can be used to return results when the service isn't able to return(due to whatever reason). The cache might return stale results when the database is out but that's ok.
I recently faced a database outage and my service came to a crashing halt.
I want the clients of my service to survive database outages happening ever again in future.
For that, I need my service to:
Handle new incoming requests like this: quickly say that the database is down and throw some exception(fast-fail).
Requests already being processed: Don't last longer than x seconds. How do I make the thread handling the request be interrupted somehow.
Cache the whole database in memory for read-only purposes(Is this insane?).
There are some observations that I made:
If there is one or more connection(s) with status ESTABLISHED, then an attempt to checkout a new connection is not made. Seems like any one connection with status ESTABLISED is handed over to the thread receiving the request. Now, this thread just hangs till the time the database comes back up.
I would want to make this request fast-fail by knowing before handling over a connection to a thread whether db is up or not. If no, the service should throw exception instead of hanging up.
If there's no connection with status ESTABLISHED, then the request fails in 10 secs with the exception that "Could not checkout a new connection". This is due to my checkout timeout being set for 10s.
If the service was processing some request, now the db goes and then the service makes a call to db, the thread making the call to db gets stuck forever. It resumes execution only after the db comes back.
I would like to interrupt the thread after say x seconds whether or not it was able to complete the request.
Are there ways to accomplish what I seek?
Thanks in advance.
I am using zmq ROUTER and DEALER sockets in my application(C++).
One process is listening on zmq ROUTER socket for clients to connect (a Service).
Clients connect to this service using zmq DEALER socket. From the client I am doing synchronous (blocking) request to the service. To avoid the
infinite wait time for the response, I am setting RCVTIMEO on DEALER socket to let say 5 ms. After setting this timeout I observe un-expected
behaviour on the client.
Here are the details:
Case 1: No RCVTIMEO is set on DEALER (client) socket
In this case, let say client sends 1000 Request to the service. Out of these requests for around 850 requests, client receives responses within 5 ms.
For remaining 150 request it takes more than 5 ms for response to come.
Case 2: RCVTIMEO is set for 5 ms on DEALER (client) socket
In this case, for the first 150-200 request I see valid response received within RCVTIMEO period. For all remaining requests I see RCVTIMEO timeout happening, which is not expected. The requests in both the cases are same.
The expected behiour should be: for 850 requests we should receive valid response (as they are coming within RCVTIMEO). And for remaining 150
requests we should see a timeout happening.
For having the timeout feature, I tried zmq_poll() also instead of setting RCVTIMEO, but results are same. Most of the requests are getting TIMEDOUT.
I went through the zmq documentation for details, but didn't find anything.
Can someone please explain the reason for this behaviour ?
I'm hoping someone can help me with an issue I'm seeing with a Qpid C++ application I'm using. Essentially, we have one application publishing a status to a last_value_queue at about a 10Hz rate and a couple other applications continuously processing this status. The receivers also use the status as a kind of heartbeat and will complain if the status message isn't updated for a certain amount of time (500ms, to be exact.)
This works fine for about a day, after which we start seeing issues. Every couple hours, a single fetch call by a receiver will block for over 500ms (sometimes for up to 900ms.) This behavior will continue until we restart the broker.
I'm no expert, but I don't think I'm doing anything particularly dumb. I've been able to repeat this behavior with a pair of small applications that connect to the broker. Every 100ms the sender sends a std::chrono::time_point object set to the current time. The receiver fetches the message and calculates the delay to the millisecond. The delay is always 0ms or 1ms, except for the single spikes every hour or so after the initial day of everything being happy. The connection is created like so:
qpid::messaging::Connection c("host1:5672","{ reconnect: true}");
and the sender and receiver are both created with the string
"testQueue; { mode: browse, create: always, node: { type: queue, x-declare:{ arguments:{'qpid.last_value_queue_key':'key','qpid.replicate':'none'}}}}"
High availability replication is enabled on the broker, but I have it explicitly disabled for everything for the purpose of my testing. I see no difference in behavior when the broker and apps are running on the same host or different hosts on the LAN. Using qpid-stat, I can see that the broker replication queue is still transmitting quite a bit of data, but its message count is always at 0 so I don't think it's sending more than it can handle. Can anyone think of anything I might be missing that could cause this behavior? We're using the Qpid 0.26 and the C++ broker.