I'm developing a small client-server program in Java.
The client and the server are connected over one tcp-connection. Most parts of the communication are asynchronous (can happen at any time) but some parts I want to be synchronous (like ACKs for a sent command).
I use a Thread that reads commands from the socket's InputStream and raises an onCommand() event. The Command itself is progressed by the Command-Design-Pattern.
What would be a best-practice approach (Java), to enable waiting for an ACK without missing other, commands that could appear at the same time?
con.sendPacket(new Packet("ABC"));
// wait for ABC_ACK
edit1
Think of it like an FTP-Connection but that both data and control-commands are on the same connection. I want to catch the response to a control-command, while data-flow in the background is running.
edit2
Everything is sent in blocks to enable multiple (different) transmissons over the same TCP-Connection (multiplexing)
Block:
1 byte - block's type
2 byte - block's payload length
n byte - block's paylod
In principle, you need a registry of blocked threads (or better, the locks on which they are waiting), keyed with some identifier which will be sent by the remote side.
For asynchronous operation, you simply sent the message and proceed.
For synchronous operation, after sending the message, your sending thread (or the thread which initiated this) create a lock object, adds this with some key to the registry and then waits on the lock until notified.
The reading thread, when it receives some answer, looks in the registry for the lock object, adds the answer to it, and calls notify(). Then it goes reading the next input.
The hard work here is the proper synchronization to avoid dead locks as well as missing a notification (because it comes back before we added ourself to the registry).
I did something like this when I implemented the remote method calling protocol for our Fencing-applet. In principle RMI works the same way, just without the asynchronous messages.
#Paulo's solution is one I have used before. However, there may be a simpler solution.
Say you don't have a background thread reading results in the connection. What you can do instead do is use the current thread to read any results.
// Asynchronous call
conn.sendMessage("Async-request");
// server sends no reply.
// Synchronous call.
conn.sendMessage("Sync-request");
String reply = conn.readMessage();
Related
I am building a server in java that communicates with several clients at the same time, the initial approach we had is the the server listens to connections from the clients, once a connection is received and a socket is created, a new thread is spawned to handle the communication with each client, that is read the request with an ObjectInputStream, do the desired operation (fetch data from the DB, update it, etc.), and send back a response to the client (if needed). While the server itself goes back to listen to more connections.
This works fine for the time being, however this approach is not really scalable, it works great for a small amount of clients connected at the same time, however since every client spawns another thread, what will happen when there are a too many clients connected at once?
So my next idea was to maintain a list of sorts that will hold all connected clients (the socket object and some extra info), use a ThreadPool for to iterate through them and read anything they sent, if a message was received then put it in a queue for execution by another ThreadPool of worker threads, and once the worker has finished with its task if a response is required then send it.
The 2 latter steps are pretty trivial to implement, the problem is that with the original thread per client implementation, I use ObjectInputStream.readObject() to read the message, and this method blocks until there is something to read, which is fine for this approach, but I can't use the same thing for the new approach, since if I block on every socket, I will never get to the ones that are further down the list.
So I need a way to check if I have anything to read before I call readObject(), so far I tried the following solutions:
Solution 1:
use ObjectInputStream.available() to check if there is anything available to read, this approach failed since this method seems to always return 0, regardless of whether there is an object in the stream or not. So this does not help at all.
Solution 2:
Use PushbackInputStream to check for the existence of the first unread byte in the stream, if it exists then push it back and read the object using the ObjectInputStream, and if it doesn't move on:
boolean available;
int b = pushbackinput.read();
if (b==-1)
available = false;
else
{
pushbackinput.unread(b);
available = true;
}
if (available)
{
Object message= objectinput.readObject();
// continue with what you need to do with that object
}
This turned out to be useless too, since read() blocks also if there is no input to read. It seems to only return the -1 option if the stream was closed. If the stream is still open but empty it just blocks, so this is no different than simply using ObjectInputStream.readObject();
Can anyone suggest an approach that will actually work?
This is a good question, and you've done some homework.... but it involves going through some history to get things right. Note, your issue is actually more to do with the socket-level communication rather than the ObjectInputStream:
The easiest way to do things in the past was to have a separate thread per socket. This was scalable to a point but threads were expensive and slow to create.
In response, for large systems, people created thread pools and would service the sockets on threads when there was work to do. This was complicated.
The Java language was then changed with the java.nio package which introduced the Selector together with non-blocking IO. This created a reliable (although sometimes confusing) way to service multiple sockets with fewer threads. In your case through, it would not help fully/much because you want to know when a full Object is ready to be read, not when there's just 'some' object.
In the interim the 'landscape' changed, and Java is now able to more efficiently create and manage threads. 'Current' thinking is that it is better/faster and easier to allocate a single thread per socket again.... see Java thread per connection model vs NIO
In your case, I would suggest that you stick with the thread-per-socket model, and you'll be fine. Java can scale and handle more threads than sockets, so you'll be fine.
I'm the main developer of an online game.
Players use a specific client software that connects to the game server with TCP/IP (TCP, not UDP)
At the moment, the architecture of the server is a classic multithreaded server with one thread per connection.
But in peak hours, when there are often 300 or 400 connected people, the server is getting more and more laggy.
I was wondering, if by switching to a java.nio.* asynchronous I/O model with few threads managing many connections, if the performances would be better.
Finding example codes on the web that cover the basics of such a server architecture is very easy. However, after hours of googling, I didn't find the answers to some more advanced questions:
1 - The protocol is text-based, not binary-based. The clients and the server exchanges lines of text encoded in UTF-8. A single line of text represents a single command, each lines are properly terminated by \n or \r\n.
For the classic multithreaded server, I have that kind of code :
public Connection (Socket sock) {
this.in = new BufferedReader( new InputStreamReader( sock.getInputStream(), "UTF-8" ));
this.out = new BufferedWriter( new OutputStreamWriter(sock.getOutputStream(), "UTF-8"));
new Thread(this) .start();
}
And then in run, data are read line by line with readLine.
In the doc, I found an utilitiy class Channels that can create a Reader out of a SocketChannel. But it is said that the produced Reader wont work if the Channel is in non-blocking mode, what contradicts the fact that non-blocking mode is mandatory to use the highly performant channel selection API I'm willing to use. So, I suspect that it isn't the right solution for what I would like to do.
The first question is therefore the following: if I can't use that, how to efficiently and properly take care of breaking lines and converting native java strings from/to UTF-8 encoded data in the nio API, with buffers and channels?
Do I have to play with get/put or inside the wrapped byte array by hand? How to go from ByteBuffer to strings encoded in UTF-8 ? I admit to don't understand very well how to use classes in the charset package and how it works to do that.
2 - In the asynchronous/non-blocking I/O world, what about the handling of consecutive read/write that have by nature to be executed sequencially one after the other?
For example, the login procedure, which is typicly challenge-response-based: the server sends a question (a particular computation), the client sends the response, and then the server checks the response given by the client.
The answer is, I think, certainly not to make a single task to send to worker threads for the whole login process, as it is quite long, with the risk to freeze worker threads for too much time (Imagine that scenario: 10 pool threads, 10 players try to connect at the same time; tasks related to players already online are delayed until one thread is again ready).
3 - What happens if two different threads simultaneously call Channel.write(ByteBuffer) on the same Channel?
Do the client might receive mixed up lines ? For example if a thread sends "aaaaa" and another sends "bbbbb", could the client receive "aaabbbbbaa", or am I ensured that everyting is sent in a consist order? Am I allowed to modify the buffer used right after the call returned?
Or asked differently, do I need additional synchronization to avoid this sort of situation?
If I need additionnal synchronization, how to know when release locks and so on, upon write finishes?
I'm afraid that the answer isn't as simple as registering for OP_WRITE in the selector. By trying that, I noticed that I get the write-ready event all the time and always for all clients, exiting Selector.select early mostly for nothing, since there are only 3 or 4 messages to send pers second per client, while the selection loop is performed hundreds of times per second. So, potentially, active wait in perspective, what is very bad.
4 - Can multiple threads call Selector.select on the same selector simultaneously without any concurrency problems such as missing an event, scheduling it twice, etc?
5 - In fact, is nio as good as it is said to be ? Would it be interesting to stay to classic multithreaded model, but unstead of creating a thread per connection, use fewer threads and loop over the connections to look for data availability using InputStream.isAvailable ? Is that idea stupid and/or inefficient?
1) Yes. I think that you need to write your own nonblocking readLine method. Note also that a nonblocking read may be signaled when there are several lines in the buffer, or when there is an incomplete line:
Example: (first read)
USER foo
PASS
(second read)
bar
You will need to store (see 2) the data that was not consumed, until enough information is ready to process it.
//channel was select for OP_READ
read data from channel
prepend data from previous read
split complete lines
save incomplete line
execute commands
2) You will need to keep the state of each client.
Map<SocketChannel,State> clients = new HashMap<SocketChannel,State>();
when a channel is connected, put a fresh state into the map
clients.put(channel,new State());
Or store the current state as the attached object of the SelectionKey.
Then, when executing each command, update the state. You may write it as a monolithic method, or do something more fancy such as polymorphic implementations of State, where each state knows how to deal with some commands (e.g. LoginState expects USER and PASS, then you change the state into a new AuthorizedState).
3) I don't recall using NIO with many asynchronous writers per channel, but the documentation says it is thread safe (I won't elaborate, since I have no proof of this). About OP_WRITE, note that it signals when the write buffer is not full. In other words, as said here: OP_WRITE is almost always ready, i.e. except when the socket send buffer is full, so you will just cause your Selector.select() method to spin mindlessly.
4) Yes. Selector.select() performs a blocking selection operation.
5) I think that the most difficult part is switching from a thread-per-client architecture, to a different design where reads and writes are decoupled from processing. Once you have done that, it is easier to work with channels than working your own way with blocking streams.
I have a client end (say Customer) that sends request (with RequestID 1) to server end and receives ack for the sent request. My server end (say SomeStore) processes the request 1 and sends to Customer and receives ack (or resends three times). I have another thread listening at Customer. Upon receiving the Customer's listener thread should update HashMap at key 1. All I need is to wait and retrieve this updated value at key 1.
I have a thread from a threadpool to send request and recieve ack on both ends. I see that both threads do the process of sending. I also have a threadpool for listener. After receiving ack, if I make my main thread wait in a while loop, I don't see the listener's update. (Here I cannot make it with wait()). I don't understand this behavior. Shouldn't both threads be working?
I tried changing my implementation and created a separate class upon receiving and synchroned with this.wait() on myHashMap.get(key) and this.notify() on myHashMap.set(key, value). It works a couple of times and not always. My understanding is that it depends on which thread gets the lock first.
How else do I wait and listen at the same time? Maybe I am overseeing something obvious...
It is easy to receive reply instead of ack but my request gets lost in the network. Therefore using ack. I am already using Callable<> for ack. Any idea is appreciated...
I suspect you are not using thread safe access to the map.
If it's not a ConcurrentHashMap and you are not using synchronization, there is no guarentee you will ever see a change in a HashMap.
Instead of using wait/notify and your own threads, I suggest you use ConcurrentHashMap and ExecutorService and add tasks to perform the update. This will ensure you process and see every update.
My system consists of a "proxy" class that receives "request" packets, marshals them and sends them over the network to a server, which unmarshals them, processes, and returns some "response packet".
My "submit" method on the proxy side should block until a reply is received to the request (packets have ids for identification and referencing purposes) or until a timeout is reached.
If I was building this in early versions of Java, I would likely implement in my proxy a collection of "pending messages ids", where I would submit a message, and wait() on the corresponding id (with a timeout). When a reply was received, the handling thread would notify() on the corresponding id.
Is there a better way to achieve this using an existing library class, perhaps in java.util.concurrency?
If I went with the solution described above, what is the correct way to deal with the potential race condition where a reply arrives before wait() is invoked?
The simple way would be to have a Callable that talks to the server and returns the Response.
// does not block
Future<Response> response = executorService.submit(makeCallable(request));
// wait for the result (blocks)
Response r = response.get();
Managing the request queue, assigning threads to the requests, and notifying the client code is all hidden away by the utility classes.
The level of concurrency is controlled by the executor service.
Every network call blocks one thread in there.
For better concurrency, one could look into using java.nio as well (but since you are talking to same server for all requests, a fixed number of concurrent connections, maybe even just one, seems to be sufficient).
A little help please.
I am designing a stateless server that will have the following functionality:
Client submits a job to the server.
Client is blocked while the server tries to perform the job.
The server will spawn one or multiple threads to perform the job.
The job either finishes, times out or fails.
The appropriate response (based on the outcome) is created, the client is unblocked and the response is handed off to the client.
Here is what I have thought of so far.
Client submits a job to the server.
The server assigns an ID to the job, places the job on a Queue and then places the Client on an another queue (where it will be blocked).
Have a thread pool that will execute the job, fetch the result and appropriately create the response.
Based on ID, pick the client out of the queue (thereby unblocking it), give it the response and send it off.
Steps 1,3,4 seems quite straight forward however any ideas about how to put the client in a queue and then block it. Also, any pointers that would help me design this puppy would be appreciated.
Cheers
Why do you need to block the client? Seems like it would be easier to return (almost) immediately (after performing initial validation, if any) and give client a unique ID for a given job. Client would then be able to either poll using said ID or, perhaps, provide a callback.
Blocking means you're holding on to a socket which obviously limits the upper number of clients you can serve simultaneously. If that's not a concern for your scenario and you absolutely need to block (perhaps you have no control over client code and can't make them poll?), there's little sense in spawning threads to perform the job unless you can actually separate it into parallel tasks. The only "queue" in that case would be the one held by common thread pool. The workflow would basically be:
Create a thread pool (such as ThreadPoolExecutor)
For each client request:
If you have any parts of the job that you can execute in parallel, delegate them to the pool.
And / or do them in the current thread.
Wait until pooled job parts complete (if applicable).
Return results to client.
Shutdown the thread pool.
No IDs are needed per se; though you may need to use some sort of latch for 2.1 / 2.3 above.
Timeouts may be a tad tricky. If you need them to be more or less precise you'll have to keep your main thread (the one that received client request) free from work and have it signal submitted job parts (by flipping a flag) when timeout is reached and return immediately. You'll have to check said flag periodically and terminate your execution once it's flipped; pool will then reclaim the thread.
How are you communicating to the client?
I recommend you create an object to represent each job which holds job parameters and the socket (or other communication mechanism) to reach the client. The thread pool will then send the response to unblock the client at the end of job processing.
The timeouts will be somewhat tricky, and will have hidden gotcha's but the basic design would seem to be to straightforward, write a class that takes a Socket in the constructor. on socket.accept we just do a new socket processing instantiation, with great foresight and planning on scalability or if this is a bench-test-experiment, then the socket processing class just goes to the data processing stuff and when it returns you have some sort of boolean or numeric for the state or something, handy place for null btw, and ether writes the success to the Output Stream from the socket or informs client of a timeout or whatever your business needs are
If you have to have a scalable, effective design for long-running heavy-haulers, go directly to nio ... hand coded one-off solutions like I describe probably won't scale well but would provide fundamental conceptualizing basis for an nio design of code-correct work.
( sorry folks, I think directly in code - design patterns are then applied to the code after it is working. What does not hold up gets reworked then, not before )