Example usage for io.vertx.core.shareddata LocalMap size

List of usage examples for io.vertx.core.shareddata LocalMap size

Introduction

In this page you can find the example usage for io.vertx.core.shareddata LocalMap size.

Prototype

int size();

Source Link

Document

Get the size of the map

Usage

From source file:net.kuujo.vertigo.deployment.impl.LocalDeploymentManager.java

License:Apache License

@Override
public DeploymentManager undeployNetwork(NetworkContext network, Handler<AsyncResult<Void>> doneHandler) {
    LocalMap<String, String> deploymentIds = vertx.sharedData().getLocalMap(network.name());

    CountingCompletionHandler<Void> counter = new CountingCompletionHandler<Void>(deploymentIds.size())
            .setHandler(result -> {//from www.  j av a  2  s  .  c o  m
                if (result.succeeded()) {
                    vertx.sharedData().<String, NetworkContext>getLocalMap(NETWORKS_KEY).remove(network.name());
                    vertx.sharedData().<String, String>getLocalMap(network.name()).clear();
                }
                doneHandler.handle(result);
            });

    for (ComponentContext component : network.components()) {
        String deploymentId = deploymentIds.get(component.address());
        if (deploymentId != null) {
            vertx.undeploy(deploymentId, counter);
        }
    }
    return this;
}

From source file:org.azrul.langmera.QLearningAnalytics.java

@Override
public void learn(DecisionFeedback currentFeedback, Vertx vertx, Runnable responseAction) {

    LocalMap<String, DetailDecisionFeedback> decisionFeedbackMap = vertx.sharedData()
            .getLocalMap("DECISION_FEEDBACK");
    LocalMap<String, DecisionRequest> decisionRequestMap = vertx.sharedData().getLocalMap("DECISION_REQUEST");
    LocalMap<String, DecisionResponse> decisionResponseMap = vertx.sharedData()
            .getLocalMap("DECISION_RESPONSE");
    LocalMap<String, Double> q = vertx.sharedData().getLocalMap("Q");
    LocalMap<Long, String> trackers = vertx.sharedData().getLocalMap("FEEDBACK_TRACKER");

    int feedbackCount = decisionFeedbackMap.size();
    boolean skipLearning = false;
    if (decisionRequestMap.get(currentFeedback.getDecisionId()) == null) {
        skipLearning = true;//from  w w  w . j a va 2s.  c  om
    }
    if (decisionResponseMap.get(currentFeedback.getDecisionId()) == null) {
        skipLearning = true;
    }
    if (skipLearning == false) {
        String context = decisionRequestMap.get(currentFeedback.getDecisionId()).getContext();
        String decision = decisionResponseMap.get(currentFeedback.getDecisionId()).getDecision();

        DetailDecisionFeedback detailFB = new DetailDecisionFeedback();
        detailFB.setFeedback(currentFeedback);
        detailFB.setContext(context);
        detailFB.setDecision(decision);
        decisionFeedbackMap.put(currentFeedback.getDecisionId(), detailFB);

        Long trackerKey = (new Date()).getTime();
        trackers.put(trackerKey, currentFeedback.getDecisionId());

        int feedbackCountByDecision = 0;
        List<Double> rewards = new ArrayList<>();
        for (DetailDecisionFeedback fb : decisionFeedbackMap.values()) {
            if (context.equals(decisionFeedbackMap.get(fb.getFeedback().getDecisionId()).getContext())
                    && decision
                            .equals(decisionFeedbackMap.get(fb.getFeedback().getDecisionId()).getDecision())) {
                feedbackCountByDecision++;
                rewards.add(fb.getFeedback().getScore());
            }
        }

        Double w = 0.0;
        Double alpha = config.getProperty("alpha", Double.class);

        //if no step parameter is configured, calculate it
        if (alpha == null) {
            alpha = 1.0 / (feedbackCountByDecision);
        }

        //non-stationary q-learning
        int i = 0;
        for (Double ri : rewards) {
            i++;
            w = w + alpha * (Math.pow(1 - alpha, feedbackCountByDecision - i)) * ri;
        }
        Double newQ = w;

        //System.out.println(feedbackCount+" Q:["+context + ":" + decision+"]"+newQ);
        //save what we learn
        if (newQ.isInfinite() || newQ.isNaN()) {
            //skip
        } else {
            String key = context + ":" + decision;
            q.put(key, newQ);
        }

        //Limit the number of history taken into account - prevents memory leak
        if (feedbackCount > config.getProperty("maxHistoryRetained", Integer.class)) {
            Long tk = Collections.min(trackers.keySet());
            String decisionIDWithMinTracker = trackers.get(tk);
            decisionFeedbackMap.remove(decisionIDWithMinTracker);
            trackers.remove(tk);
        }

        //clear cached req/resp once the feedback has come back
        decisionRequestMap.remove(currentFeedback.getDecisionId());
        decisionResponseMap.remove(currentFeedback.getDecisionId());

        //Get maxQ
        Double maxQ = Double.NEGATIVE_INFINITY;
        String decisionWithMaxQ = null;
        for (String contextDecision : q.keySet()) {
            if (q.get(contextDecision) > maxQ) {
                decisionWithMaxQ = contextDecision;
                maxQ = q.get(contextDecision);
            }
        }

        //keep traces
        if (Boolean.TRUE.equals(config.getProperty("collect.traces", Boolean.class))) {
            Date now = new Date();
            for (String contextDecision : q.keySet()) {
                List<Double> qtrace = traces.get(contextDecision);
                if (qtrace == null) {
                    qtrace = new ArrayList<Double>();
                    qtrace.add(q.get(contextDecision));
                    traces.put(contextDecision, qtrace);
                } else {
                    qtrace.add(q.get(contextDecision));
                }
                String[] c = contextDecision.split(":");
                Trace trace = new Trace(currentFeedback.getDecisionId(), c[0], q.get(contextDecision), maxQ,
                        now, c[1], currentFeedback.getScore());
                vertx.eventBus().publish("SAVE_TRACE_TO_TRACE",
                        SerializationUtils.serialize((Serializable) trace));
            }
        }

        //            //put in in-memory DB
        //            
        //            
        //            String[] c = decisionWithMaxQ.split(":");
        //            if (InMemoryDB.store.get(0)==null){
        //                List<Object> imContext = new ArrayList<Object>();
        //                imContext.add(c[0]);
        //                InMemoryDB.store.add(0,imContext);
        //            }else{
        //                InMemoryDB.store.get(0).add(c[0]);
        //            }
        //            
        //            if (InMemoryDB.store.get(1)==null){
        //                List<Object> imDecision = new ArrayList<Object>();
        //                imDecision.add(c[1]);
        //                InMemoryDB.store.add(1,imDecision);
        //            }else{
        //                InMemoryDB.store.get(1).add(c[1]);
        //            }
        //            
        //            if (InMemoryDB.store.get(2)==null){
        //                List<Object> imMaxQ = new ArrayList<Object>();
        //                imMaxQ.add(maxQ);
        //                InMemoryDB.store.add(2,imMaxQ);
        //            }else{
        //                InMemoryDB.store.get(2).add(maxQ);
        //            }
        //            
        //            if (InMemoryDB.store.get(3)==null){
        //                List<Object> imTime= new ArrayList<Object>();
        //                imTime.add(new Date());
        //                InMemoryDB.store.add(3,imTime);
        //            }else{
        //                InMemoryDB.store.get(3).add(new Date());
        //            }

        responseAction.run();
        if (Boolean.TRUE.equals(currentFeedback.getTerminal())) {
            long delta = (new Date()).getTime() - startTime;
            System.out.println("Time taken to process " + feedbackCount + " msgs:" + delta + " ms");
            System.out.println("Time taken per msg: " + (delta / feedbackCount) + " ms");
            System.out
                    .println("Msgs per s: " + ((1000.0 * (double) feedbackCount) / ((double) delta)) + " msgs");
            if (Boolean.TRUE.equals(config.getProperty("collect.traces", Boolean.class))
                    && Boolean.TRUE.equals(config.getProperty("display.desktop.chart", Boolean.class))) {
                final LineChart demo = new LineChart(chartDesc, traces);
                demo.pack();
                demo.setVisible(true);
            }
        }
    } else {
        logger.log(Level.WARNING, "Attempt to learn from a feedback with no corresponding request/response");
        responseAction.run();
    }
    //
    //select qmovies,qsports,qconcerts from 
    //   (select t1.qvalue as qsports,t1.decisionid from trace t1 where t1.decision='SPORTS' order by t1.decisiontime) as A1 
    //   join (select t2.qvalue as qmovies,t2.decisionid from trace t2 where t2.decision='MOVIES' order by t2.decisiontime) as A2 on A1.decisionid = A2.decisionid
    //   join (select t3.qvalue as qconcerts,t3.decisionid from trace t3 where t3.decision='CONCERTS' order by t3.decisiontime) as A3 on A1.decisionid = A3.decisionid

}