Implemented MovieRecommender class, All Junit tests passed

src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java

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+
+package nearsoft.academy.bigdata.recommendation;
+
+import java.io.BufferedInputStream;
+import java.io.BufferedReader;
+import java.io.FileReader;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+
+
+import org.apache.mahout.cf.taste.impl.model.GenericPreference;
+import org.apache.mahout.cf.taste.impl.common.*;
+import org.apache.mahout.cf.taste.impl.model.GenericUserPreferenceArray;
+import org.apache.mahout.cf.taste.impl.model.GenericDataModel;
+import org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood;
+import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender; 
+import org.apache.mahout.cf.taste.model.PreferenceArray;
+import org.apache.mahout.cf.taste.similarity.UserSimilarity;
+import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
+import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
+import org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem;
+import org.apache.mahout.cf.taste.recommender.RecommendedItem;
+
+
+
+
+
+
+public class MovieRecommender {
+
+    private FastByIDMap<PreferenceArray> usersPreferences; 
+    private HashMap<String,Long> userIDs;
+    private HashMap<String,Long> productIDs;
+    private long userCount;
+    private long productCount;
+    private long reviewCount;
+    private GenericDataModel model;
+    private GenericUserBasedRecommender recommender;
+
+
+    public MovieRecommender(String filePath) {
+
+        productIDs = new HashMap<String,Long>();
+        userIDs = new HashMap<String,Long>();
+        usersPreferences = new FastByIDMap<PreferenceArray>();
+        userCount = 0;
+        productCount =0;
+        reviewCount= 0;
+
+
+
+        System.out.println("Hello Java Again :(\n");
+        getPreference(filePath);
+        buildRecomender();
+        // printPreferences();
+
+    }
+
+
+    GenericPreference getPreference(String filePath) {
+        String productID = "";
+        String userID = "";
+        Float score = 0.0f;
+
+        BufferedReader reader;
+
+
+        try {
+            reader = new BufferedReader(new FileReader(filePath));
+            String line = reader.readLine();
+            while (line != null) {
+
+
+                if(line.startsWith("product/productId:") )
+                    productID = line.split(" ")[1];
+                if(line.startsWith("review/userId:") )
+                    userID = line.split(" ")[1];
+                if(line.startsWith("review/score:") ){
+
+                    score = Float.parseFloat( line.split(" ")[1]); 
+                    addPreference(userID, productID,score);
+
+
+                }
+                line = reader.readLine();
+            }
+            reader.close();
+
+        } catch (IOException e) {
+            e.printStackTrace();
+        }
+        return null;
+    }
+
+    void addPreference( String userID,String productID, float score)
+    {
+        reviewCount++;
+        System.out.println("Reviews Processed: "+ reviewCount);
+        if(!userIDs.containsKey(userID) )
+            userIDs.put(userID,++userCount);
+
+
+        if(!productIDs.containsKey(productID) )
+            productIDs.put(productID,++productCount);
+
+        Long longUserID = userIDs.get(userID);
+        Long longProductID = productIDs.get(productID);
+
+        GenericUserPreferenceArray preferencesArray = (GenericUserPreferenceArray)usersPreferences.get(longUserID);
+        ArrayList preferencesList = new ArrayList();
+
+        // Checking if there was previous preferences for this user
+        if(preferencesArray != null)
+        {
+            // Move the preferences from the array to a list
+            for(Integer i =0; i< preferencesArray.length();i ++ )
+                preferencesList.add(preferencesArray.get(i));
+        }
+
+        // Add the new preference to the list
+        preferencesList.add(new GenericPreference(longUserID, longProductID, score));
+
+        // Get preferences back to the array inside the FastByIDMap
+        usersPreferences.put(longUserID, new GenericUserPreferenceArray(preferencesList));
+
+    }
+
+    void printPreferences()
+    {
+        for (int i = 1; i <= usersPreferences.size();i++) 
+        {
+            GenericUserPreferenceArray preferences= (GenericUserPreferenceArray)usersPreferences.get(i);
+            System.out.println("UserID: " + i + "\n" );
+
+            for(int p =0;p < preferences.length();p ++)
+            {
+                System.out.println("\tUser: " + preferences.get(p).getUserID() + " Product: " + preferences.get(p).getItemID() + " Score: " + preferences.get(p).getValue()  );
+
+            }
+        }
+    }
+
+
+    void buildRecomender()
+    {   
+        model= new GenericDataModel(usersPreferences);
+        try{
+            UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+            UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+            recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);    
+        }catch(Exception e)
+        {
+
+        }
+
+
+    }
+
+    public int getTotalReviews() {
+
+        return (int)reviewCount;
+    }
+
+    public int getTotalProducts() {
+        // return 253059;
+        return model.getNumItems();
+    }
+
+    public int getTotalUsers() {
+        // return 889176;
+        return model.getNumUsers();
+    }
+
+    List<String> getRecommendationsForUser(String user) {
+
+        List<String> result = new ArrayList<String>();
+        System.out.println("user: "+ userIDs);
+        long longUserID = userIDs.get(user);
+        System.out.println("user: " + userIDs);
+
+        try{
+
+            List<RecommendedItem>recomendations =  recommender .recommend(longUserID,10);
+            for(RecommendedItem item: recomendations )
+            {
+                result.add((String)productIDs.keySet().toArray()[(int)item.getItemID()]);
+            }
+        }
+        catch(Exception e)
+        {
+
+        }
+
+        //  result.add("B0002O7Y8U");
+        //  result.add("B00004CQTF");
+        //  result.add("B000063W82");
+        return result;
+    }
+
+
+
+}