I am currently using a non-blocking SocketChannel (Java 1.6) to act as a client to a Redis server. Redis accepts plain-text commands directly over a socket, terminated by CRLF and responds in-like, a quick example:
SEND: 'PING\r\n'
RECV: '+PONG\r\n'
Redis can also return huge replies (depending on what you are asking for) with many sections of \r\n-terminated data all as part of a single response.
I am using a standard while(socket.read() > 0) {//append bytes} loop to read bytes from the socket and re-assemble them client side into a reply.
NOTE: I am not using a Selector, just multiple, client-side SocketChannels connected to the server, waiting to service send/receive commands.
What I'm confused about is the contract of the SocketChannel.read() method in non-blocking mode, specifically, how to know when the server is done sending and I have the entire message.
I have a few methods to protect against returning too fast and giving the server a chance to reply, but the one thing I'm stuck on is:
Basically, can I trust that the server is done responding to me if I have received at least 1 byte and eventually read() returns 0 then I know I'm done, or is it possible the server was just busy and might sputter back some more bytes if I wait and keep trying?
If it can keep sending bytes even after a read() has returned 0 bytes (after previous successful reads) then I have no idea how to tell when the server is done talking to me and in-fact am confused how java.io.* style communications would even know when the server is "done" either.
As you guys know read never returns -1 unless the connection is dead and these are standard long-lived DB connections, so I won't be closing and opening them on each request.
I know a popular response (atleast for these NIO questions) have been to look at Grizzly, MINA or Netty -- if possible I'd really like to learn how this all works in it's raw state before adopting some 3rd party dependencies.
Thank you.
Bonus Question:
I originally thought a blocking SocketChannel would be the way to go with this as I don't really want a caller to do anything until I process their command and give them back a reply anyway.
If that ends up being a better way to go, I was a bit confused seeing that SocketChannel.read() blocks as long as there aren't bytes sufficient to fill the given buffer... short of reading everything byte-by-byte I can't figure out how this default behavior is actually meant to be used... I never know the exact size of the reply coming back from the server, so my calls to SocketChannel.read() always block until a time out (at which point I finally see that the content was sitting in the buffer).
I'm not real clear on the right way to use the blocking method since it always hangs up on a read.
Look to your Redis specifications for this answer.
It's not against the rules for a call to .read()
to return 0 bytes on one call and 1 or more bytes on a subsequent call. This is perfectly legal. If anything were to cause a delay in delivery, either because of network lag or slowness in the Redis server, this could happen.
The answer you seek is the same answer to the question: "If I connected manually to the Redis server and sent a command, how could I know when it was done sending the response to me so that I can send another command?"
The answer must be found in the Redis specification. If there's not a global token that the server sends when it is done executing your command, then this may be implemented on a command-by-command basis. If the Redis specifications do not allow for this, then this is a fault in the Redis specifications. They should tell you how to tell when they have sent all their data. This is why shells have command prompts. Redis should have an equivalent.
In the case that Redis does not have this in their specifications, then I would suggest putting in some sort of timer functionality. Code your thread handling the socket to signal that a command is completed after no data has been received for a designated period of time, like five seconds. Choose a period of time that is significantly longer than the longest command takes to execute on the server.