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ORM for Cassandra but with distributed cache and analytics utils from package
package com.fnklabs.draenei.analytics;
import com.codahale.metrics.Timer;
import com.fnklabs.draenei.MetricsFactory;
import org.jetbrains.annotations.NotNull;
import java.util.Collection;
import java.util.HashMap;
import java.util.Map;
final class CosineSimilarityAlgorithm implements SimilarityAlgorithm {
private final MetricsFactory metricsFactory;
CosineSimilarityAlgorithm(MetricsFactory metricsFactory) {
this.metricsFactory = metricsFactory;
}
@Override
public double getSimilarity(@NotNull Collection firstVector, @NotNull Collection secondVector) {
Timer.Context time = metricsFactory.getTimer(MetricsType.COSINE_SIMILARITY_GET_SIMILARITY).time();
double firstVectorModule = getVectorModule(firstVector);
double secondVectorModule = getVectorModule(secondVector);
if (firstVectorModule == 0 || secondVectorModule == 0) {
return 0;
}
double scalarVectorComposition = getScalarComposition(firstVector, secondVector);
double similarity = scalarVectorComposition / (firstVectorModule * secondVectorModule);
time.stop();
return similarity;
}
protected double getVectorModule(@NotNull Collection firstVector) {
Timer.Context time = metricsFactory.getTimer(MetricsType.COSINE_SIMILARITY_GET_VECTOR_MODULE).time();
double vectorPointSum = firstVector.stream()
.mapToDouble(entry -> Math.pow(entry.getRank(), 2))
.sum();
double sqrt = Math.sqrt(vectorPointSum);
time.stop();
return sqrt;
}
protected double getScalarComposition(@NotNull Collection firstVector, @NotNull Collection secondVector) {
Timer.Context time = metricsFactory.getTimer(MetricsType.COSINE_SIMILARITY_GET_SCALAR_COMPOSITION).time();
Map secondMap = transformToMap(secondVector);
double sum = 0;
for (T entry : firstVector) {
// if (secondMap.containsKey(entry)) {
K orDefault = secondMap.get(entry.getKey());
if (orDefault != null) {
// K orDefault = secondMap.get(entry);
sum += entry.getRank() * orDefault.getRank();
}
}
time.stop();
return sum;
}
private Map transformToMap(@NotNull Collection vector) {
Timer.Context time = metricsFactory.getTimer(MetricsType.COSINE_SIMILARITY_TRANSFORM_MAP).time();
Map map = new HashMap<>();
for (T item : vector) {
map.putIfAbsent(item.getKey(), item);
}
time.stop();
return map;
}
private enum MetricsType implements MetricsFactory.Type {
COSINE_SIMILARITY_GET_VECTOR_MODULE,
COSINE_SIMILARITY_GET_SCALAR_COMPOSITION,
COSINE_SIMILARITY_TRANSFORM_MAP,
COSINE_SIMILARITY_GET_SIMILARITY
}
}
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