Answer to the Race Condition in the TCP Stack Challenge
We look at the answer to a challenge posed about an intermittent data-drop issue via TCP. Has this ever happened to you?
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Join For FreeIn my previous post, I discussed a problem in missing data over a TCP connection that happened in a racy manner, only every few hundred runs. As it turns out, there is a simple way to make the code run into the problem every single time.
The full code for the repro can be found here.
Change these lines:
And voila, you will consistently run into the problem. Wait, run that by me again, what is going on here?
As it turns out, the issue is in the server, more specifically, here and here. We use a StreamReader to read the first line from the client, do some processing, and then hand it to the ProcessConnection method, which also uses a StreamReader. More significantly, it uses a different StreamReader.
Why is that significant? Well, because of this, the StreamReader has buffers, by default, that are 1KB in size. So here is what happens in the case above: we send a single packet to the server, and when the first StreamReader reads from the stream, it fills the buffer with the two messages. But since there is a line break between them, when we call ReadLineAsync, we actually only get the first one.
Then, when we get to the ProcessConnection method, we have another StreamReader, which also reads from the stream, but the second message had already been read (and is waiting in the first StreamReader buffer), so we are waiting for more information from the client, which will never come.
So how come it sort of works if we do this in two separate calls? Well, it is all about the speed. In most cases, when we split it into two separate calls, the server socket has only the first message in there when the first StreamReader runs, so the second StreamReader is successful in reading the second line. But in some cases, the client manages being fast enough and sending both messages to the server before the server can read them, and voila, we have the same behavior, only much more unpredictable.
The key problem was that it wasn’t obvious we were reading too much from the stream, and until we figured that one out, we were looking in a completely wrong direction.
Published at DZone with permission of Oren Eini, DZone MVB. See the original article here.
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