Category: HTTP

  • NoSql Sessions with Jetty7 and Jetty8

    When Jetty 7.5.0 is released we will have officially started to dabble in the area of distributed session handling and storage. To start this out we have created a set of abstract classes around the general concept of NoSQL support, and have prepared an initial implementation using MongoDB. We will also be working on Ehcache and perhaps Cassandra implementations over time to round out the offering, but it is overall a pretty exciting time for these sorts of things.

    NoSQL sessions are a good idea for a number of usage scenarios, but as with NoSQL solutions in general, it is not a one-size-fits-all technology. The Jetty NoSQL session implementation should be good for scenarios that require decentralization, highly parallel work loads, and scalability, while also supporting session migration from one machine to the next for load balancing purposes. While we are initially releasing with just the MongoDB session manager, it is important to make clear that all the different distributed NoSQLish solutions out there have there own positives and negatives that you need to balance when choosing a storage medium. This is an interesting and diverse area of development, and since there is little standardization at the moment it is not a simple matter of exporting data from one system to the next if you want to change back ends.

    Before jumping in and embracing this solution for your session management, ask yourself some questions:

    • Do I require a lot of write behavior on my session objects?

    When you’re dealing with anything that touches the network to perform an action, you have an entirely different set of issues than if you can keep all your logic on one machine.  The hash session manager is the fastest solution for this use profile, but the JDBC session manager is not a bad solution if you need to operate with the network.  That in mind, there is an optimization in the NoSQL session managers where tight write loops should queue up a bit before an actual write to the back end MongoDB server occurs.  In general, if you have a session profile that involves a lot of writes all the time, you might want to shy away from this approach.

    • Am I bouncing sessions across lots of machines all the time?

    If you are, then you might be better off to get rid of sessions entirely and be more RESTful, but a networked session manager is going to be difficult to scale to this approach and be consistent.  By consistent I mean writing data into your session on one node and having that same data present within a session on another node.  If you’re looking at using MongoDB to increase the number of sessions you’re able to support, it is vitally important to remember that the network is not an inexhaustable resource, and keeping sessions localized is good practice, especially if you want consistent behavior. But if you want non-sticky sessions or mostly sticky sessions that can scale, this sort of NoSQL session manager is certainly an option, especially for lightweight, mostly read sessions.

    • Do I want to scale to crazy amounts of sessions that are relatively small and largely contain write-once read-often data?

    Great! Use this!  You are the people we had in mind when we developed the distributed session handling.

    On the topic of configuring the new session managers, it is much like other traditional ones: add them to the context.xml or set up with the regular jetty.xml route. There are, however, a couple of important options to keep in mind for the session ID manager.

    • scavengeDelay–How often will a scavenge operation occur looking for sessions to invalidate?
    • scavengePeriod–How much time after a scavenge has completed should you wait before doing it again?
    • purge (Boolean)–Do you want to purge (delete) sessions that are invalid from the session store completely?
    • purgeDelay–How often do you want to perform this purge operation?
    • purgeInvalidAge–How old should an invalid session be before it is eligible to be purged?
    • purgeValidAge–How old should a valid session be before it is eligible to be marked invalid and purged? Should this occur at all?

    A guide for detailed configuration can be found on our wiki at on the Session Clustering with MongoDB page.

    The new MongoDB session manager and session ID manager are located in the jetty-nosql module.  Since we plan to have multiple offerings we have made the mongodb dependency optional, so if you’re planning to use embedded Jetty, make sure you declare a hard dependency in Maven. You can also download the mongodb jar file and place it into a lib/mongodb directory within the jetty distribution itself; then you must add mongodb to the OPTIONS  on the cli or in the start.ini file you’re starting Jetty with.

    There were a number of different ways to go in implementing session ID management. While we are wholly tolerant of a user request being moved from one server to another, we chose to keep normal session operations localized to the machine where the session originates.  If the request bounces from one machine to another, the latest known session is loaded. If it is saved and then bounces back, Jetty notices the change in the version of the session and reloads, but these operations are heavy weight: they require pulling back all data of a session across the network, as opposed to a field or two of MongoDB goodness.  One side effect of this approach is the scavenge operation executes only on the known session IDs of a given node. In this scenario, if your happy cluster of Jetty instances has a problem and one of them crashes (not our fault!), there is potential for previously valid session IDs to remain in your MongoDB session store, never to be seen again, but also never cleaned up. That is where purge comes in: the purge process can perform a passive sweep through the MongoDB cluster to delete really old, valid sessions.  You can also delete the invalid sessions that are over a week old, or a month old, or whatever you like. If you have hoarding instincts, you can turn purge off (it’s true by default), and your MongoDB cluster will grow… and grow.

    We have also added some additional JMX support to the MongoDB session manager. When you enable JMX, you can access all the normal session statistics, but you also have the option to force execution of the purge and scavenge operations on a single node, or purge fully, which executes the purge logic for everything in the MongoDB store.  In this mode you can disable purge on your nodes and schedule the actions for when you are comfortable they will not cause issues on the network.  For tips on configuring JMX support for jetty see our tutorial on JMX.

    Lastly I’ll just mention that MongoDB is really a treat to work with. I love how easy it is to print the data being returned from MongoDB, and it’s in happy JSON.  It has a rich query language that allowed us to easily craft queries for the exact information we were looking for, reducing the footprint on the network the session work imposes.

     

  • Websocket Example: Server, Client and LoadTest

    The websocket protocol specification is approaching final and the Jetty implementation and API have been tracking the draft and is ready when the spec and browsers are available.   More over, Jetty release 7.5.0 now includes a capable websocket java client that can be used for non browser applications or load testing. It is fully asynchronous and can create thousands of connections simultaneously.

    This blog uses the classic chat example to introduce a websocket server, client and load test.

    The project

    The websocket example has been created as a maven project with groupid com.example.  The entire project can be downloaded from here.   The pom.xml defines a dependency on org.eclipse.jetty:jetty-websocket-7.5.0.RC1 (you should update to 7.5.0 when the final release is available), which provides the websocket API and transitively the jetty implementation.  There is also a dependency on org.eclipse.jetty:jetty-servlet which provides the ability to create an embedded servlet container to run the server example.

    While the project implements a Servlet, it is not in a typical webapp layout, as I wanted to provide both client and server in the same project.    Instead of a webapp, this project uses embedded jetty in a simple Main class to provide the server and the static content is served from the classpath from src/resources/com/example/docroot.

    Typically developers will want to build a war file containing a webapp, but I leave it as an exercise for the reader to put the servlet and static content described here into a webapp format.

    The Servlet

    The Websocket connection starts with a HTTP handshake.  Thus the websocket API in jetty also initiated by the handling of a HTTP request (typically) by a Servlet.  The advantage of this approach is that it means that websocket connections are terminated in the same rich application space provided by HTTP servers, thus a websocket enabled web application can be developed in a single environment rather than by collaboration between a HTTP server and a separate websocket server.

    We create the ChatServlet with an init() method that instantiates and configures a WebSocketFactory instance:

    public class ChatServlet extends HttpServlet
    {
      private WebSocketFactory _wsFactory;
      private final Set _members = new CopyOnWriteArraySet();
      @Override
      public void init() throws ServletException
      {
        // Create and configure WS factory
        _wsFactory=new WebSocketFactory(new WebSocketFactory.Acceptor()
        {
          public boolean checkOrigin(HttpServletRequest request, String origin)
          {
            // Allow all origins
            return true;
          }
          public WebSocket doWebSocketConnect(HttpServletRequest request, String protocol)
          {
             if ("chat".equals(protocol))
               return new ChatWebSocket();
             return null;
          }
        });
        _wsFactory.setBufferSize(4096);
        _wsFactory.setMaxIdleTime(60000);
      }
      ...

    The WebSocketFactory is instantiated by passing it an Acceptor instance, which in this case is an anonymous instance. The Acceptor must implement two methods: checkOrigin, which in this case accepts all; and doWebSocketConnect, which must accept a WebSocket connection by creating and returning an instance of the WebSocket interface to handle incoming messages.  In this case, an instance of the nested ChatWebSocket class is created if the protocol is “chat”.   The other WebSocketFactory fields have been initialised with hard coded buffers size and timeout, but typically these would be configurable from servlet init parameters.

    The servlet handles get requests by passing them to the WebSocketFactory to be accepted or not:

      ...
      protected void doGet(HttpServletRequest request,
                           HttpServletResponse response)
        throws IOException
      {
        if (_wsFactory.acceptWebSocket(request,response))
          return;
        response.sendError(HttpServletResponse.SC_SERVICE_UNAVAILABLE,
                           "Websocket only");
      }
      ...

    All that is left for the Servlet, is the ChatWebSocket itself.   This is just a POJO that receives callbacks for events.  For this example we have implemented the WebSocket.OnTextMessage interface to restrict the call backs to only connection management and full messages:

      private class ChatWebSocket implements WebSocket.OnTextMessage
      {
        Connection _connection;
        public void onOpen(Connection connection)
        {
          _connection=connection;
          _members.add(this);
        }
        public void onClose(int closeCode, String message)
        {
          _members.remove(this);
        }
        public void onMessage(String data)
        {
          for (ChatWebSocket member : _members)
          {
            try
            {
              member._connection.sendMessage(data);
            }
            catch(IOException e)
            {
              e.printStackTrace();
            }
          }
        }
      }

    The handling of the onOpen callback is to add the ChatWebSocket to the set of all members (and remembering the Connection object for subsequent sends).  The onClose handling simply removes the member from the set.   The onMessage handling iterates through all the members and sends the received message to them (and prints any resulting exceptions).

     

    The Server

    To run the servlet, there is a simple Main method that creates an embedded Jetty server with a ServletHandler for the chat servlet, as ResourceHandler for the static content needed by the browser client and a DefaultHandler to generate errors for all other requests:

    public class Main
    {
      public static void main(String[] arg) throws Exception
      {
        int port=arg.length>1?Integer.parseInt(arg[1]):8080;
        Server server = new Server(port);
        ServletHandler servletHandler = new ServletHandler();
        servletHandler.addServletWithMapping(ChatServlet.class,"/chat/*");
        ResourceHandler resourceHandler = new ResourceHandler();
        resourceHandler.setBaseResource(Resource.newClassPathResource("com/example/docroot/"));
        DefaultHandler defaultHandler = new DefaultHandler();
        HandlerList handlers = new HandlerList();
        handlers.setHandlers(new Handler[] {servletHandler,resourceHandler,defaultHandler});
        server.setHandler(handlers);
        server.start();
        server.join();
      }
    }

    The server can be run from an IDE or via maven using the following command line:

    mvn
    mvn -Pserver exec:exec

    The Browser Client

    The HTML for the chat room simply imports some CSS and the javascript before creating a few simple divs to contain the chat text, the join dialog and the joined dialog:

    <html>
     <head>
     <title>WebSocket Chat Example</title>
     <script type='text/javascript' src="chat.js"></script>
     <link rel="stylesheet" type="text/css" href="chat.css" />
     </head>
     <body>
      <div id='chat'></div>
      <div id='input'>
       <div id='join' >
        Username:&nbsp;<input id='username' type='text'/>
        <input id='joinB' class='button' type='submit' name='join' value='Join'/>
       </div>
       <div id='joined' class='hidden'>
        Chat:&nbsp;<input id='phrase' type='text'/>
        <input id='sendB' class='button' type='submit' name='join' value='Send'/>
       </div>
      </div>
      <script type='text/javascript'>init();</script>
     </body>
    </html>

    The javascript create a room object with methods to handle the various operations of a chat room.  The first operation is to join the chat room, which is triggered by entering a user name.  This creates a new WebSocket object pointing to the /chat URL path on the same server the HTML was loaded from:

    var room = {
      join : function(name) {
        this._username = name;
        var location = document.location.toString()
          .replace('http://', 'ws://')
          .replace('https://', 'wss://')+ "chat";
        this._ws = new WebSocket(location, "chat");
        this._ws.onopen = this.onopen;
        this._ws.onmessage = this.onmessage;
        this._ws.onclose = this.onclose;
      },
      onopen : function() {
        $('join').className = 'hidden';
        $('joined').className = '';
        $('phrase').focus();
        room.send(room._username, 'has joined!');
      },
      ...

    The javascript websocket object is initialised with call backs for onopen, onclose and onmessage. The onopen callback is handled above by switching the join div to the joined div and sending a “has joined” message.

    Sending is implemented by creating a string of username:message and sending that via the WebSocket instance:

      ...
      send : function(user, message) {
        user = user.replace(':', '_');
        if (this._ws)
          this._ws.send(user + ':' + message);
      },
      ...

    If the chat room receives a message, the onmessage callback is called, which sanitises the message, parses out the username and appends the text to the chat div:

      ...
      onmessage : function(m) {
        if (m.data) {
          var c = m.data.indexOf(':');
          var from = m.data.substring(0, c)
            .replace('<','<')
            .replace('>','>');
          var text = m.data.substring(c + 1)
            .replace('<', '<')
            .replace('>', '>');
          var chat = $('chat');
          var spanFrom = document.createElement('span');
          spanFrom.className = 'from';
          spanFrom.innerHTML = from + ': ';
          var spanText = document.createElement('span');
          spanText.className = 'text';
          spanText.innerHTML = text;
          var lineBreak = document.createElement('br');
          chat.appendChild(spanFrom);
          chat.appendChild(spanText);
          chat.appendChild(lineBreak);
          chat.scrollTop = chat.scrollHeight - chat.clientHeight;
        }
      },
      ...

    Finally, the onclose handling empties the chat div and switches back to the join div so that a new username may be entered:

      ...
      onclose : function(m) {
        this._ws = null;
        $('join').className = '';
        $('joined').className = 'hidden';
        $('username').focus();
        $('chat').innerHTML = '';
      }
    };

    With this simple client being served from the server, you can now point your websocket capable browsers at http://localhost:8080 and interact with the chat room. Of course this example glosses over a lot of detail and complications a real chat application would need, so I suggest you read my blog is websocket chat simpler to learn what else needs to be handled.

    The Load Test Client

    The jetty websocket java client is an excellent tool for both functional and load testing of a websocket based service.  It  uses the same endpoint API as the server side and for this example we create a simple implementation of the OnTextMessage interface that keeps track of the all the open connection and counts the number of messages sent and received:

    public class ChatLoadClient implements WebSocket.OnTextMessage
    {
      private static final AtomicLong sent = new AtomicLong(0);
      private static final AtomicLong received = new AtomicLong(0);
      private static final Set<ChatLoadClient> members = new CopyOnWriteArraySet<ChatLoadClient>();
      private final String name;
      private final Connection connection;
      public ChatLoadClient(String username,WebSocketClient client,String host, int port)
      throws Exception
      {
        name=username;
        connection=client.open(new URI("ws://"+host+":"+port+"/chat"),this).get();
      }
      public void send(String message) throws IOException
      {
        connection.sendMessage(name+":"+message);
      }
      public void onOpen(Connection connection)
      {
        members.add(this);
      }
      public void onClose(int closeCode, String message)
      {
        members.remove(this);
      }
      public void onMessage(String data)
      {
        received.incrementAndGet();
      }
      public void disconnect() throws IOException
      {
        connection.disconnect();
      }

    The Websocket is initialized by calling open on the WebSocketClient instance passed to the constructor.  The WebSocketClient instance is shared by multiple connections and contains the thread pool and other common resources for the client.

    This load test example comes with a main method that creates a WebSocketClient from command line options and then creates a number of ChatLoadClient instances:

    public static void main(String... arg) throws Exception
    {
      String host=arg.length>0?arg[0]:"localhost";
      int port=arg.length>1?Integer.parseInt(arg[1]):8080;
      int clients=arg.length>2?Integer.parseInt(arg[2]):1000;
      int mesgs=arg.length>3?Integer.parseInt(arg[3]):1000;
      WebSocketClient client = new WebSocketClient();
      client.setBufferSize(4096);
      client.setMaxIdleTime(30000);
      client.setProtocol("chat");
      client.start();
      // Create client serially
      ChatLoadClient[] chat = new ChatLoadClient[clients];
      for (int i=0;i<chat.length;i++)
        chat[i]=new ChatLoadClient("user"+i,client,host,port);
      ...

    Once the connections are opened, the main method loops around picking a random client to speak in the chat room

      ...
      // Send messages
      Random random = new Random();
      for (int i=0;i<mesgs;i++)
      {
        ChatLoadClient c = chat[random.nextInt(chat.length)];
        String msg = "Hello random "+random.nextLong();
        c.send(msg);
      }
      ...

    Once all the messages have been sent and all the replies have been received, the connections are closed:

      ...
      // close all connections
      for (int i=0;i<chat.length;i++)
        chat[i].disconnect();

    The project is setup so that the load client can be run with the following maven command:

    mvn -Pclient exec:exec

    And the resulting output should look something like:

    Opened 1000 of 1000 connections to localhost:8080 in 1109ms
    Sent/Received 10000/10000000 messages in 15394ms: 649603msg/s
    Closed 1000 connections to localhost:8080 in 45ms

    Yes that is 649603 messages per second!!!!!!!!!!! This is a pretty simple easy test, but it is still scheduling 1000 local sockets plus generating and parsing all the websocket frames. Real applications on real networks are unlikely to achieve close to this level, but the indications are good for the capability of high throughput and stand by for more rigorous bench marks shortly.

     

     

     

  • Prelim Cometd WebSocket Benchmarks

    I have done some very rough preliminary benchmarks on the latest cometd-2.4.0-SNAPSHOT with the latest Jetty-7.5.0-SNAPSHOT and the results are rather impressive.  The features that these two releases have added are:

    • Optimised Jetty NIO with latest JVMs and JITs considered.
    • Latest websocket draft implemented and optimised.
    • Websocket client implemented.
    • Jackson JSON parser/generator used for cometd
    • Websocket cometd transport for the server improved.
    • Websocket cometd transport for the bayeux client implemented.

    The benchmarks that I’ve done have all been on my notebook using the localhost network, which is not the most realistic of environments, but it still does tell us a lot about the raw performance of the cometd/jetty.  Specifically:

    • Both the server and the client are running on the same machine, so they are effectively sharing the 8 CPUs available.   The client typically takes 3x more CPU than the server (for the same load), so this is kind of like running the server on a dual core and the client on a 6 core machine.
    • The local network has very high throughput which would only be matched by gigabit networks.  It also has practically no latency, which is unlike any real network.  The long polling transport is more dependent on good network latency than the websocket transport, so the true comparison between these transports will need testing on a real network.

    The Test

    The cometd load test is a simulated chat application.  For this test I tried long-polling and websocket transports for 100, 1000 and 10,000 clients that were each logged into 10 randomly selected chat rooms from a total of 100 rooms.   The messages sent were all 50 characters long and were published in batches of 10 messages at once, each to randomly selected rooms.  There was a pause between batches that was adjusted to find a good throughput that didn’t have bad latency.  However little effort was put into finding the optimal settings to maximise throughput.

    The runs were all done on JVM’s that had been warmed up, but the runs were moderately short (approx 30s), so steady state was not guaranteed and the margin of error on these numbers will be pretty high.  However, I also did a long run test at one setting just to make sure that steady state can be achieved.

    The Results

    The bubble chart above plots messages per second against number of clients for both long-polling and websocket transports.   The size of the bubble is the maximal latency of the test, with the smallest bubble being 109ms and the largest is 646ms.  Observations from the results are:

    • Regardless of transport we achieved 100’s of 1000’s messages per second!  These are great numbers and show that we can cycle the cometd infrastructure at high rates.
    • The long-polling throughput is probably a over reported because there are many messages being queued into each HTTP response.   The most HTTP responses I saw was 22,000 responses per second, so for many application it will be the HTTP rate that limits the throughput rather than the cometd rate.  However the websocket throughput did not benefit from any such batching.
    • The maximal latency for all websocket measurements was significantly better than long polling, with all websocket messages being delivered in < 200ms and the average was < 1ms.
    • The websocket throughput increased with connections, which probably indicates that at low numbers of connections we were not generating a maximal load.

    A Long Run

    The throughput tests above need to be redone on a real network and longer runs. However I did do one long run ( 3 hours) of 1,000,013,657 messages at 93,856/sec. T results suggest no immediate problems with long runs. Neither the client nor the server needed to do a old generation collection and all young generation collections took on average only 12ms.

    The output from the client is below:

    Statistics Started at Fri Aug 19 15:44:48 EST 2011
    Operative System: Linux 2.6.38-10-generic amd64
    JVM : Sun Microsystems Inc. Java HotSpot(TM) 64-Bit Server VM runtime 17.1-b03 1.6.0_22-b04
    Processors: 8
    System Memory: 55.35461% used of 7.747429 GiB
    Used Heap Size: 215.7406 MiB
    Max Heap Size: 1984.0 MiB
    Young Generation Heap Size: 448.0 MiB
    - - - - - - - - - - - - - - - - - - - -
    Testing 1000 clients in 100 rooms, 10 rooms/client
    Sending 1000000 batches of 10x50 bytes messages every 10000 µs
    - - - - - - - - - - - - - - - - - - - -
    Statistics Ended at Fri Aug 19 18:42:23 EST 2011
    Elapsed time: 10654717 ms
    	Time in JIT compilation: 57 ms
    	Time in Young Generation GC: 118473 ms (8354 collections)
    	Time in Old Generation GC: 0 ms (0 collections)
    Garbage Generated in Young Generation: 2576746.8 MiB
    Garbage Generated in Survivor Generation: 336.53125 MiB
    Garbage Generated in Old Generation: 532.35156 MiB
    Average CPU Load: 433.23907/800
    ----------------------------------------
    Outgoing: Elapsed = 10654716 ms | Rate = 938 msg/s = 93 req/s =   0.4 Mbs
    All messages arrived 1000013657/1000013657
    Messages - Success/Expected = 1000013657/1000013657
    Incoming - Elapsed = 10654716 ms | Rate = 93856 msg/s = 90101 resp/s(96.00%) =  35.8 Mbs
    Thread Pool - Queue Max = 972 | Latency avg/max = 3/62 ms
    Messages - Wall Latency Min/Ave/Max = 0/8/135 ms

    Note that the client was using 433/800 of the available CPU, while you can see that the server (below) was using only 170/800.  This suggests that the server has plenty of spare capacity if it were given the entire machine.

    Statistics Started at Fri Aug 19 15:44:47 EST 2011
    Operative System: Linux 2.6.38-10-generic amd64
    JVM : Sun Microsystems Inc. Java HotSpot(TM) 64-Bit Server VM runtime 17.1-b03 1.6.0_22-b04
    Processors: 8
    System Memory: 55.27913% used of 7.747429 GiB
    Used Heap Size: 82.58406 MiB
    Max Heap Size: 2016.0 MiB
    Young Generation Heap Size: 224.0 MiB
    - - - - - - - - - - - - - - - - - - - -
    - - - - - - - - - - - - - - - - - - - -
    Statistics Ended at Fri Aug 19 18:42:23 EST 2011
    Elapsed time: 10655706 ms
    	Time in JIT compilation: 187 ms
    	Time in Young Generation GC: 140973 ms (12073 collections)
    	Time in Old Generation GC: 0 ms (0 collections)
    Garbage Generated in Young Generation: 1652646.0 MiB
    Garbage Generated in Survivor Generation: 767.625 MiB
    Garbage Generated in Old Generation: 1472.6484 MiB
    Average CPU Load: 170.20532/800

    Conclusion

    These results are preliminary, but excellent none the less!   The final releases of jetty 7.5.0 and cometd 2.4.0 will be out within a week or two and we will be working to bring you some more rigorous benchmarks with those releases.