All test cases pass

pom.xml

@@ -12,19 +12,32 @@
 
   <properties>
     <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+
   </properties>
 
   <dependencies>
       <dependency>
           <groupId>org.apache.mahout</groupId>
-          <artifactId>mahout-core</artifactId>
-          <version>0.9</version>
+          <artifactId>mahout-mr</artifactId>
+          <version>0.10.0</version>
       </dependency>
+
       <dependency>
           <groupId>junit</groupId>
           <artifactId>junit</artifactId>
           <version>4.7</version>
           <scope>test</scope>
       </dependency>
+      <dependency>
+          <groupId>org.junit.jupiter</groupId>
+          <artifactId>junit-jupiter</artifactId>
+          <version>RELEASE</version>
+          <scope>test</scope>
+      </dependency>
   </dependencies>
+
 </project>
+
+
+
+

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

@@ -0,0 +1,142 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import com.google.common.collect.BiMap;
+import com.google.common.collect.HashBiMap;
+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.Recommender;
+import org.apache.mahout.cf.taste.similarity.UserSimilarity;
+
+import java.io.*;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.zip.GZIPInputStream;
+
+
+public class MovieRecommender {
+
+    private static final String OUTPUT_FILEPATH = "movies.csv";
+    private static final String PRODUCT_KEY = "product/productId: ";
+    private static final String USER_KEY = "review/userId: ";
+    private static final String SCORE_KEY = "review/score: ";
+    private int totalReviews;
+    private HashMap<String, Integer> HMusers;
+    private HashBiMap<String, Integer> HMproducts;
+    private Recommender recommender;
+
+
+
+
+  public MovieRecommender (String filePath) throws IOException, TasteException {
+      this.HMusers = new HashMap<String, Integer>();
+      this.HMproducts = HashBiMap.create();
+      File csvFile = generateCSV(filePath);
+      createRecommender(csvFile);
+  }
+
+  private File generateCSV(String filePath) throws IOException {
+
+      BufferedReader reader = getGzipReader(new File(filePath));
+      FileWriter writer = new FileWriter(OUTPUT_FILEPATH);
+      String currentLine;
+      String csvLine = "";
+      int currentProduct = 0;
+
+      while((currentLine = reader.readLine()) != null) {
+          if (currentLine.startsWith(PRODUCT_KEY)) {
+              String productId = currentLine.substring(19);
+              if (!this.HMproducts.containsKey(productId)) {
+                  this.HMproducts.put(productId, this.HMproducts.size());
+              }
+              currentProduct = this.HMproducts.get(productId);
+          }
+
+          else if (currentLine.startsWith(USER_KEY)) {
+              String userId = currentLine.substring(15);
+              if (!this.HMusers.containsKey(userId)){
+                  this.HMusers.put(userId, HMusers.size());
+              }
+              this.totalReviews++;
+              csvLine = this.HMusers.get(userId) + "," + currentProduct + ",";
+          }
+
+          else if (currentLine.startsWith(SCORE_KEY)) {
+              double score = Double.parseDouble(currentLine.substring(14));
+              csvLine += score + "\n";
+              writer.write(csvLine);
+              writer.flush();
+          }
+
+
+
+      }
+
+      reader.close();
+      writer.close();
+
+
+
+      return new File(OUTPUT_FILEPATH);
+  }
+
+
+
+  public void createRecommender(File csvFile) throws TasteException, IOException {
+      DataModel model = new FileDataModel(csvFile);
+      UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+      UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+      this.recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+  }
+
+  public List<String> getRecommendationsForUser (String userId) throws TasteException {
+      int userIdInt = this.HMusers.get(userId);
+      List recommendations = this.recommender.recommend(userIdInt, 3);
+      return getRecommendationsIds(recommendations);
+  }
+
+private List<String> getRecommendationsIds(List<RecommendedItem> recommendations){
+    BiMap<Integer, String> invertedProducts = this.HMproducts.inverse();
+    ArrayList<String> productsIds = new ArrayList<String>();
+     for (RecommendedItem recommendation : recommendations){
+       int recommendationId = (int) recommendation.getItemID();
+       productsIds.add(invertedProducts.get(recommendationId));
+     }
+     return  productsIds;
+}
+
+
+
+
+  public int getTotalReviews(){
+      return totalReviews;
+  }
+
+  public int getTotalProducts(){
+      return HMproducts.size();
+  }
+
+  public int getTotalUsers(){
+      return HMusers.size();
+  }
+
+
+
+    private BufferedReader getGzipReader(File filePath) throws IOException {
+        InputStream fileStream = new FileInputStream(filePath);
+        InputStream gzipStream = new GZIPInputStream(fileStream);
+        Reader decoder = new InputStreamReader(gzipStream, "UTF-8");
+
+        return new BufferedReader(decoder);
+    }
+
+
+
+}

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

@@ -15,7 +15,7 @@ public class MovieRecommenderTest {
     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");
+        MovieRecommender recommender = new MovieRecommender("/Users/hzamorano/big-data-exercises/src/test/java/nearsoft/academy/bigdata/recommendation/movies.txt.gz");
         assertEquals(7911684, recommender.getTotalReviews());
         assertEquals(253059, recommender.getTotalProducts());
         assertEquals(889176, recommender.getTotalUsers());