Minor refractoring

Author: mohammadzainabbas

src/main/java/exercise_2/Exercise_2.java

@@ -141,5 +141,4 @@ public static void shortestPaths(JavaSparkContext ctx) {
                 Utils.print("Minimum cost to get from '" + srcLabel + "' to '" + descLabel + "' is " + cost);
             });
 	}
-	
 }

src/main/java/exercise_3/Exercise_3.java

@@ -13,7 +13,6 @@
 import scala.runtime.AbstractFunction1;
 import scala.runtime.AbstractFunction2;
 import scala.runtime.AbstractFunction3;
-import shapeless.Tuple;
 
 import java.io.Serializable;
 import java.util.ArrayList;
@@ -27,7 +26,6 @@
 public class Exercise_3 {
 
     // Initial value for pregel execution
-    // static final Tuple2<Integer, List<String>> INITIAL_VALUE = new Tuple2<Integer, List<String>>(Integer.MAX_VALUE, new ArrayList<String>());
     static final Vertex INITIAL_VALUE = new Vertex(Integer.MAX_VALUE);
 
     // Nodes' Labels 

src/main/java/exercise_4/Exercise_4.java

@@ -3,8 +3,6 @@
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.sql.Dataset;
-import org.apache.spark.sql.Encoder;
-import org.apache.spark.sql.Encoders;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
 import org.apache.spark.sql.SQLContext;
@@ -15,12 +13,7 @@
 import org.apache.spark.rdd.RDD;
 import org.graphframes.GraphFrame;
 import java.util.stream.IntStream;
-import java.io.IOException;
-import java.nio.file.Files;
-import java.nio.file.Path;
-import java.nio.file.Paths;
 import java.util.ArrayList;
-import java.util.Arrays;
 import java.util.List;
 import utils.Utils;
 
@@ -51,14 +44,7 @@ public static void wikipedia(JavaSparkContext ctx, SQLContext sqlCtx) {
 
 		Utils.line_separator();
 
-		// graphFrame.edges().show();
-		// graphFrame.vertices().show();
-		
-		// @todo: Benchmark with multiple dumping factor and numIterations
-		// --- Ideas ---
-		// 1. Define some dumping factors and numIterations and run & time pagerank algo. and select the best
 		// For dumping factor
-		// List<String> time = new ArrayList<String>(Arrays.asList(new String[120]));
 		List<Row> timeList = new ArrayList<Row>();
 		StructType outputSchema = new StructType(new StructField[] {
 			new StructField("dumping_factor", DataTypes.DoubleType, false, new MetadataBuilder().build()),
@@ -84,7 +70,6 @@ public static void wikipedia(JavaSparkContext ctx, SQLContext sqlCtx) {
 				Utils.print(log);
 				topVertices.show(10);
 				Utils.line_separator();
-				// time.add(log);
 			});
 		});
 
@@ -93,24 +78,5 @@ public static void wikipedia(JavaSparkContext ctx, SQLContext sqlCtx) {
 		Long count = output.count();
 		output.show(count.intValue());
 		Utils.line_separator();
-		
-		// try {
-		// 	Files.write(Paths.get("/root/SDM-Lab-2/src/main/java/exercise_4/output.txt"), time);
-		// } catch (IOException e) {
-		// 	Utils.print("Unable to save file" + e);
-		// }
-		
-		// GraphFrame gf = graphFrame.pageRank().tol(0.01).resetProbability(0.15).run();
-		// GraphFrame gf = graphFrame.pageRank().resetProbability(0.15).maxIter(10).run();
-		
-		// Utils.line_separator();
-		
-		// gf.edges().show();
-		// gf.vertices().show();
-		
-		// Utils.line_separator();
-		// Dataset<Row> topVertices = gf.vertices().sort(org.apache.spark.sql.functions.desc("pagerank"));
-		// topVertices.show(10);
-
 	}
 }