org.apache.mahout.cf.taste.impl.common.FastByIDMap Java Examples

@Test
public void testBuildDefaultRecommender() {

    RecommenderBuilder rb = new GenericRecommenderBuilder();
    FastByIDMap<PreferenceArray> userData = new FastByIDMap<PreferenceArray>();
    userData.put(1, new GenericUserPreferenceArray(Arrays.asList(new GenericPreference(1, 1, 1),
            new GenericPreference(1, 2, 1), new GenericPreference(1, 3, 1))));
    userData.put(2, new GenericUserPreferenceArray(Arrays.asList(new GenericPreference(2, 1, 1),
            new GenericPreference(2, 2, 1), new GenericPreference(2, 4, 1))));
    DataModel dm = new GenericDataModel(userData);

    Recommender rec = null;
    try {
        rec = rb.buildRecommender(dm);
    } catch (TasteException e) {
        e.printStackTrace();
    }
    assertTrue(rec instanceof RandomRecommender);
}
 

public DataModel loadInMemory() {
	// In-memory DataModel - GenericDataModels
	FastByIDMap<PreferenceArray> preferences = new FastByIDMap<PreferenceArray>();

	PreferenceArray prefsForUser1 = new GenericUserPreferenceArray(10);
	prefsForUser1.setUserID(0, 1L);
	prefsForUser1.setItemID(0, 101L);
	prefsForUser1.setValue(0, 3.0f);
	prefsForUser1.setItemID(1, 102L);
	prefsForUser1.setValue(1, 4.5F);
	preferences.put(1L, prefsForUser1); // use userID as the key
	
	//TODO: add others users

	
	// Return preferences as new data model
	DataModel dataModel = new GenericDataModel(preferences);
	
	return dataModel;

}
 

/**
 * Constructs the wrapper using the provided model.
 *
 * @param model the model to be used to create the wrapped model
 */
public DataModelWrapper(final net.recommenders.rival.core.TemporalDataModelIF<Long, Long> model) {
    FastByIDMap<Collection<Preference>> data = new FastByIDMap<Collection<Preference>>();
    FastByIDMap<FastByIDMap<Long>> timestampData = new FastByIDMap<FastByIDMap<Long>>();
    for (Long u : model.getUsers()) {
        List<Preference> prefs = new ArrayList<Preference>();
        FastByIDMap<Long> userTimestamps = new FastByIDMap<Long>();
        timestampData.put(u, userTimestamps);
        for (Long i : model.getUserItems(u)) {
            Iterable<Long> timestamps = model.getUserItemTimestamps(u, i);
            long t = -1;
            if (timestamps != null) {
                for (Long tt : timestamps) {
                    t = tt;
                    break;
                }
            }
            userTimestamps.put(i, t);
            prefs.add(new GenericPreference(u, i, model.getUserItemPreference(u, i).floatValue()));
        }
        data.put(u, prefs);
    }

    FastByIDMap<PreferenceArray> userData = GenericDataModel.toDataMap(data, true);
    wrapper = new GenericDataModel(userData, timestampData);
}
 

@Test
public void testBuildKNNRecommender() {
    GenericRecommenderBuilder rb = new GenericRecommenderBuilder();
    FastByIDMap<PreferenceArray> userData = new FastByIDMap<PreferenceArray>();
    userData.put(1, new GenericUserPreferenceArray(Arrays.asList(new GenericPreference(1, 1, 1),
            new GenericPreference(1, 2, 1), new GenericPreference(1, 3, 1))));
    userData.put(2, new GenericUserPreferenceArray(Arrays.asList(new GenericPreference(2, 1, 1),
            new GenericPreference(2, 2, 1), new GenericPreference(2, 4, 1))));
    DataModel dm = new GenericDataModel(userData);

    Recommender rec = null;
    String recommenderType = "org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender";
    String similarityType = "org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity";
    try {
        rec = rb.buildRecommender(dm, recommenderType, similarityType);
    } catch (RecommenderException e) {
        e.printStackTrace();
    }
    assertTrue(rec instanceof GenericUserBasedRecommender);
}
 

public MemoryUserClusterStore(String client,int entries)
{
	logger.info("MemoryUserClusterStore for "+client+" of size "+entries);
	this.store = new FastByIDMap<>(entries);
	this.client = client;
	this.clusterGroups = new ConcurrentHashMap<>();
	this.transientClusters = new ConcurrentHashMap<>();
}
 

@Override
public void addTimestamp(Long u, Long i, Long t) {
    if (model != null) {
        throw new IllegalArgumentException("DataModel already generated. It is not possible to add more information.");
    }
    FastByIDMap<Long> prefs = null;
    if (!timestampData.containsKey(u)) {
        prefs = new FastByIDMap<Long>();
        timestampData.put(u, prefs);
    } else {
        prefs = timestampData.get(u);
    }
    prefs.put(i, t);
}
 

public ItemMemIDMigrator() {
	this.longToString = new FastByIDMap<String>(10000);
}
 

private void generateDatamodel() {
    FastByIDMap<PreferenceArray> userData = GenericDataModel.toDataMap(data, true);
    model = new GenericDataModel(userData, timestampData);
    data = null;
    timestampData = null;
}
 

@Override
public void clear() {
    model = null;
    data = new FastByIDMap<Collection<Preference>>();
    timestampData = new FastByIDMap<FastByIDMap<Long>>();
}