Implements MovieRecommender class

pom.xml

@@ -26,5 +26,10 @@
           <version>4.7</version>
           <scope>test</scope>
       </dependency>
+      <dependency>
+          <groupId>com.google.guava</groupId>
+          <artifactId>guava</artifactId>
+          <version>21.0</version>
+      </dependency>
   </dependencies>
 </project>

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

@@ -0,0 +1,71 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import org.apache.mahout.cf.taste.common.TasteException;
+import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
+import org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood;
+import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
+import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
+import org.apache.mahout.cf.taste.model.DataModel;
+import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
+import org.apache.mahout.cf.taste.recommender.RecommendedItem;
+import org.apache.mahout.cf.taste.recommender.UserBasedRecommender;
+import org.apache.mahout.cf.taste.similarity.UserSimilarity;
+
+import java.util.LinkedList;
+import java.util.List;
+import java.io.*;
+
+public class MovieRecommender {
+    private ReviewInfo reviewInfo;
+
+    public MovieRecommender(String filePath) {
+        ReviewDataReader reader = new ReviewDataReader();
+
+        this.reviewInfo = new ReviewInfo();
+        reader.readData(filePath, this.reviewInfo);
+    }
+
+    /**
+     * @return Total number of reviews.
+     */
+    public int getTotalReviews() {
+        return this.reviewInfo.getTotalReviews();
+    }
+
+    /**
+     * @return Total number of products.
+     */
+    public int getTotalProducts() {
+        return this.reviewInfo.getProducts().size();
+    }
+
+    /**
+     * @return Total number of users.
+     */
+    public int getTotalUsers() {
+        return this.reviewInfo.getUsers().size();
+    }
+
+    /**
+     * Gets 3 recommendations for a given user.
+     *
+     * @param userID The ID of the user.
+     * @return List of IDs of the recommended products.
+     */
+    public List<String> getRecommendationsForUser(String userID) throws IOException, TasteException {
+        DataModel model = new FileDataModel(new File("movies.csv"));
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+
+        List<String> recommendedTitles = new LinkedList<String>(); // List of alphanumeric product IDs.
+        List<RecommendedItem> recommendations = recommender.recommend(this.reviewInfo.getUserIndex(userID), 3);
+
+        for (RecommendedItem recommendation : recommendations) {
+            recommendedTitles.add(this.reviewInfo.getProducts().get(recommendation.getItemID()));
+        }
+
+        return recommendedTitles;
+    }
+
+}

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

@@ -13,9 +13,10 @@
 public class MovieRecommenderTest {
     @Test
     public void testDataInfo() throws IOException, TasteException {
-        //download movies.txt.gz from 
-        //    http://snap.stanford.edu/data/web-Movies.html
-        MovieRecommender recommender = new MovieRecommender("/path/to/movies.txt.gz");
+        // download movies.txt.gz from
+        // http://snap.stanford.edu/data/web-Movies.html
+        // file must be placed in the root directory of this repository
+        MovieRecommender recommender = new MovieRecommender("movies.txt.gz");
         assertEquals(7911684, recommender.getTotalReviews());
         assertEquals(253059, recommender.getTotalProducts());
         assertEquals(889176, recommender.getTotalUsers());
@@ -24,7 +25,6 @@ public void testDataInfo() throws IOException, TasteException {
         assertThat(recommendations, hasItem("B0002O7Y8U"));
         assertThat(recommendations, hasItem("B00004CQTF"));
         assertThat(recommendations, hasItem("B000063W82"));
-
     }
 
 }

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

@@ -0,0 +1,58 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import java.io.*;
+import java.util.zip.GZIPInputStream;
+
+public class ReviewDataReader {
+
+    /**
+     * Reads the "movies.txt.gz" file.
+     * Generates a .csv file with the relevant information in the correct format.
+     * Loads the users, products and reviews info.
+     */
+    public void readData(String filePath, ReviewInfo info) {
+        File file = new File(filePath);
+
+        try {
+            InputStream in = new GZIPInputStream(new FileInputStream(file));
+            Reader decoder = new InputStreamReader(in, "US-ASCII");
+            BufferedReader br = new BufferedReader(decoder);
+            String line;
+            String productID = "";
+            String userID = "";
+
+            File fout = new File("movies.csv");
+            FileOutputStream fos = new FileOutputStream(fout);
+            BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(fos));
+            String newLine;
+
+            int productCounter = 0;
+            int userCounter = 0;
+
+            while ((line = br.readLine()) != null) {
+                if (line.startsWith("product/productId")) {
+                    productID = line.split(": ")[1];
+                    if (!info.containsProduct(productID)) {
+                        info.putProduct(new Long(productCounter), productID);
+                        productCounter++;
+                    }
+                } else if (line.startsWith("review/userId")) {
+                    userID = line.split(": ")[1];
+                    if (!info.containsUser(userID)) {
+                        info.putUser(new Long(userCounter), userID);
+                        userCounter++;
+                    }
+                } else if (line.startsWith("review/score")) {
+                    newLine = info.getUserIndex(userID) + "," + info.getProductIndex(productID) + "," + line.split(": ")[1];
+                    bw.write(newLine);
+                    bw.newLine();
+                    info.setTotalReviews(info.getTotalReviews() + 1);
+                }
+            }
+            bw.close();
+
+        } catch (IOException e) {
+            e.printStackTrace();
+        }
+    }
+}

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

@@ -0,0 +1,104 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import com.google.common.collect.BiMap;
+import com.google.common.collect.HashBiMap;
+
+/**
+ * Stores the Amazon movie reviews information
+ */
+public class ReviewInfo {
+
+    private BiMap<Long, String> users; // Collection of distinct users present in the reviews
+    private BiMap<Long, String> products; // Collection of distinct products present in the reviews
+    private int totalReviews; // Number of total reviews
+
+    public ReviewInfo() {
+        this.users = HashBiMap.create();
+        this.products = HashBiMap.create();
+        this.totalReviews = 0;
+    }
+
+    public BiMap<Long, String> getUsers() {
+        return users;
+    }
+
+    public void setUsers(BiMap<Long, String> users) {
+        this.users = users;
+    }
+
+    /**
+     * Checks if the specified user exists in the reviews
+     *
+     * @param userID Alphanumeric user ID
+     * @return TRUE if the user is found, FALSE otherwise
+     */
+    public boolean containsUser(String userID) {
+        return this.users.containsValue(userID);
+    }
+
+    /**
+     * Adds a new user to the users collection
+     *
+     * @param key    BiMap key
+     * @param userID Alphanumeric user ID
+     */
+    public void putUser(Long key, String userID) {
+        this.users.put(key, userID);
+    }
+
+    /**
+     * Finds the index of the specified user in the users collection
+     *
+     * @param userID Alphanumeric user ID
+     * @return Index position of the user
+     */
+    public Long getUserIndex(String userID) {
+        return this.users.inverse().get(userID);
+    }
+
+    public BiMap<Long, String> getProducts() {
+        return products;
+    }
+
+    public void setProducts(BiMap<Long, String> products) {
+        this.products = products;
+    }
+
+    /**
+     * Checks if the specified product exists in the reviews
+     *
+     * @param productID Alphanumeric product ID
+     * @return TRUE if the product is found, FALSE otherwise
+     */
+    public boolean containsProduct(String productID) {
+        return this.products.containsValue(productID);
+    }
+
+    /**
+     * Adds a new product to the products collection
+     *
+     * @param key       BiMap key
+     * @param productID Alphanumeric product ID
+     */
+    public void putProduct(Long key, String productID) {
+        this.products.put(key, productID);
+    }
+
+    /**
+     * Finds the index of the specified product in the product collection
+     *
+     * @param productID Alphanumeric product ID
+     * @return Index position of the product
+     */
+    public Long getProductIndex(String productID) {
+        return this.products.inverse().get(productID);
+    }
+
+    public int getTotalReviews() {
+        return totalReviews;
+    }
+
+    public void setTotalReviews(int totalReviews) {
+        this.totalReviews = totalReviews;
+    }
+}