Esempio n. 1
0
  public static Seq next(String name) {
    Datastore ds = MorphiaPlugin.ds();
    Query<Seq> q = ds.find(Seq.class, "_id", name);
    UpdateOperations<Seq> o = ds.createUpdateOperations(Seq.class).inc("value");
    Seq newId = ds.findAndModify(q, o);
    if (null == newId) {
      newId = new Seq(name);
      ds.save(newId);
    }

    return newId;
  }
Esempio n. 2
0
  @PostConstruct
  public void init() {
    try {
      System.out.println("UMIGON - semantic analyzer for large twitter accounts");
      Mongo m;
      Morphia morphia;
      Mongo mLocal;
      Morphia morphiaLocal;
      mLocal = new Mongo();
      morphiaLocal = new Morphia();
      setTweets = new ArrayList();

      if (dev) {
        ExcelToCsv.load();
      }

      if (!dev) {
        saveOnDisk = false;
        analyzeNewlyArrivedTweets = false;
        analyzeAllFromDisk = false;
        loadTweetsFromLocal = false;
        loadFromTrainingFile = false;
        bigTrainingFile = false;
        clementTests = false;
      }

      // loads the heuristics from the csv files just created
      Hloader = new HeuristicsLoader();
      Hloader.load();

      // loads Categories
      Categories.populate();

      if (saveOnDisk || analyzeNewlyArrivedTweets) {
        m = new Mongo("alex.mongohq.com", 10056);
        morphia = new Morphia();
        ds =
            morphia.createDatastore(
                m, APIkeys.getMongoHQAPIkey(), "seinecle", APIkeys.getMongoHQPass().toCharArray());
        if (ds != null) {
          System.out.println("Morphia datastore on CloudBees / MongoHQ created!!!!!!!");
        }
        morphia.map(Tweet.class);
        listTweets = ds.find(Tweet.class).asList();
        setTweets.addAll(listTweets);
      }

      if (saveOnDisk || analyzeAllFromDisk || loadTweetsFromLocal) {
        dsLocal = morphiaLocal.createDatastore(mLocal, "hp");
        morphiaLocal.map(Tweet.class);
      }

      if (saveOnDisk) {
        Iterator<Tweet> setTweetsIterator = setTweets.iterator();
        while (setTweetsIterator.hasNext()) {
          Tweet tweet = setTweetsIterator.next();
          dsLocal.save(tweet);
        }
        ds.delete(ds.createQuery(Tweet.class));
        System.out.println("------------------------------------------------");
        System.out.println(
            "saved " + setTweets.size() + " on disk and deleted them fromm the cloud");
      }
      if (analyzeAllFromDisk) {
        listTweets = dsLocal.find(Tweet.class).asList();
        setTweets.addAll(listTweets);
        System.out.println("------------------------------------------------");
        System.out.println(
            "retrieving all tweets from disk (collected since Dec. 02, 2012): " + setTweets.size());
        hl1 = new TweetLooper(setTweets);
        setTweets = hl1.applyLevel1(loadFromTrainingFile);
        for (Tweet tweet : setTweets) {
          updateQuery = dsLocal.createQuery(Tweet.class).field("text").equal(tweet.getText());
          ops =
              dsLocal
                  .createUpdateOperations(Tweet.class)
                  .set("setCategories", tweet.getSetCategories());
          dsLocal.update(updateQuery, ops, true);
        }
      }

      if (loadTweetsFromLocal) {
        listTweets = dsLocal.find(Tweet.class).asList();
        setTweets.addAll(listTweets);
        System.out.println("------------------------------------------------");
        System.out.println(
            "retrieved all tweets from disk (collected since Dec. 02, 2012): " + setTweets.size());
      }

      if (analyzeNewlyArrivedTweets) {
        listTweets = ds.find(Tweet.class).asList();
        setTweets.addAll(listTweets);
        System.out.println("------------------------------------------------");
        System.out.println("retrieving newly arrived tweets from the cloud: " + setTweets.size());
        hl1 = new TweetLooper(setTweets);
        hl1.applyLevel1(loadFromTrainingFile);
      }

      if (loadFromTrainingFile) {
        ExternalSourceTweetLoader comp = new ExternalSourceTweetLoader();
        if (bigTrainingFile) {
          setTweets = comp.sentimentBigSetLoader(maxTweets, termFilter);
        } else if (clementTests) {
          setTweets = comp.clementTestTweetsLoader(maxTweets);
        } else {
          setTweets = comp.sentiment140Loader();
        }
        System.out.println("------------------------------------------------");
        System.out.println("tweets from training file: " + setTweets.size());
        hl1 = new TweetLooper(setTweets);
        hl1.applyLevel1(loadFromTrainingFile);
      }

    } catch (LangDetectException ex) {
      Logger.getLogger(ControllerBean.class.getName()).log(Level.SEVERE, null, ex);
    } catch (FileNotFoundException ex) {
      Logger.getLogger(ControllerBean.class.getName()).log(Level.SEVERE, null, ex);
    } catch (IOException ex) {
      Logger.getLogger(ControllerBean.class.getName()).log(Level.SEVERE, null, ex);
    } catch (InvalidFormatException ex) {
      Logger.getLogger(ControllerBean.class.getName()).log(Level.SEVERE, null, ex);
    } catch (MongoException ex) {
      Logger.getLogger(ControllerBean.class.getName()).log(Level.SEVERE, null, ex);
    }
  }