Bd-ex

.gitignore

@@ -0,0 +1,5 @@
+.idea/
+*.iml
+*.cvc
+target/
+*.DS_Store

MovieRecommender.java

@@ -0,0 +1,96 @@
+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.io.*;
+import java.util.*;
+
+
+public class MovieRecommender {
+    private final String TEMP_FILE = "/Users/anarobles/Desktop/dataset.csv";
+    private int usersCount = 0, productsCount = 0, reviewsCount = 0, u=0, n=0;
+    private HashMap<String, Integer> users = new HashMap();
+            HashMap<String, Integer> products = new HashMap();
+            HashMap<Integer, String> inverseHash = new HashMap();
+    //private Set<String> users = new HashSet<>(); Set<String> products = new HashSet<>();
+
+    public MovieRecommender(String sourcePath) throws IOException {
+
+
+            String userId = "", productId = "", score = "";
+            String line;
+
+            BufferedReader bufferedReader = new BufferedReader(new FileReader(sourcePath));
+            File outputFileStream = new File(TEMP_FILE);
+            BufferedWriter bufferedWriter = new BufferedWriter(new FileWriter(outputFileStream));
+            System.out.println("Buffers inicializados");
+
+            while ((line = bufferedReader.readLine()) != null) {
+
+                if (line.contains("product/productId")) {
+                    productId = line.substring(19, 29);
+                    if (!products.containsKey(productId)) {
+                        productsCount++;
+                        products.put(productId, productsCount);
+                        inverseHash.put(productsCount, productId);
+                        n = productsCount;
+                    } else{
+                        n = products.get(productId);
+                    }
+                }
+
+                if (line.contains("review/userId")) {
+                    userId = line.substring(15);
+                    if (!users.containsKey(userId)) {
+                        usersCount++;
+                        users.put(userId, usersCount);
+                        u=usersCount;
+                    }else{
+                        u=users.get(userId);
+                    }
+
+                }
+                if (line.contains("review/score")) {
+                    score = line.substring(14);
+                    reviewsCount++;
+                    bufferedWriter.write(u + "," + n + "," + score + "\n");
+                }
+            }
+            bufferedWriter.close();
+            bufferedReader.close();
+            System.out.println("Archivo creado");
+
+    }
+
+    List<String> getRecommendationsForUser(String UserId) throws IOException, TasteException {
+        DataModel model = new FileDataModel(new File(TEMP_FILE));
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+        //System.out.println(Integer.parseInt(userId));
+        List<RecommendedItem> recommendations = recommender.recommend(users.get(UserId),3);
+        List<String> recommendationsForUser = new ArrayList<String>();
+        for (RecommendedItem recommendation : recommendations) {
+            recommendationsForUser.add(inverseHash.get((int)recommendation.getItemID()));
+        }
+        return recommendationsForUser;
+    }
+
+    public int getTotalUsers(){
+        return usersCount;
+    }
+    public int getTotalProducts(){
+        return productsCount;
+    }
+    public int getTotalReviews(){
+        return reviewsCount;
+    }
+
+}

pom.xml

@@ -1,17 +1,16 @@
 <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
   xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
   <modelVersion>4.0.0</modelVersion>
-
   <groupId>nearsoft.academy</groupId>
   <artifactId>big-data</artifactId>
   <version>1.0-SNAPSHOT</version>
   <packaging>jar</packaging>
-
   <name>big-data</name>
   <url>http://maven.apache.org</url>
-
   <properties>
     <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+    <maven.compiler.source>14</maven.compiler.source>
+    <maven.compiler.target>14</maven.compiler.target>
   </properties>
 
   <dependencies>
@@ -20,11 +19,17 @@
           <artifactId>mahout-core</artifactId>
           <version>0.9</version>
       </dependency>
+      <dependency>
+          <groupId>org.apache.mahout</groupId>
+          <artifactId>mahout-mr</artifactId>
+          <version>0.13.0</version>
+      </dependency>
       <dependency>
           <groupId>junit</groupId>
           <artifactId>junit</artifactId>
           <version>4.7</version>
           <scope>test</scope>
       </dependency>
   </dependencies>
-</project>
+
+</project>

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

@@ -13,9 +13,9 @@
 public class MovieRecommenderTest {
     @Test
     public void testDataInfo() throws IOException, TasteException {
-        //download movies.txt.gz from 
+        //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/anarobles/Downloads/movies.txt");
         assertEquals(7911684, recommender.getTotalReviews());
         assertEquals(253059, recommender.getTotalProducts());
         assertEquals(889176, recommender.getTotalUsers());
@@ -27,4 +27,4 @@ public void testDataInfo() throws IOException, TasteException {
 
     }
 
-}
+}