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spark:spark-introduction [2014/11/03 20:31]
straka 		spark:spark-introduction [2014/11/03 20:37]
straka
Line 70: Line 70:
     return min((np.sum((point - centers[i]) ** 2), i) for i in range(len(centers)))[1]     return min((np.sum((point - centers[i]) ** 2), i) for i in range(len(centers)))[1]
  
-lines = sc.textFile("/net/projects/hadoop/examples/inputs/points-small/points.txt")+lines = sc.textFile("/net/projects/hadoop/examples/inputs/points-small/points.txt", sc.defaultParallelism)
 data = lines.map(lambda line: np.array([float(x) for x in line.split()])).cache() data = lines.map(lambda line: np.array([float(x) for x in line.split()])).cache()
  
Line 76: Line 76:
 epsilon = 1e-3 epsilon = 1e-3
  
-centers = data.takeSample(False, K   )    # Sample K random points+centers = data.takeSample(False, K)       # Sample K random points
 for i in range(5):                        # Perform 5 iterations for i in range(5):                        # Perform 5 iterations
     old_centers = sc.broadcast(centers)     old_centers = sc.broadcast(centers)
Line 89: Line 89:
                .map(lambda (index, (sum, count)): sum / count)                .map(lambda (index, (sum, count)): sum / count)
                .collect())                .collect())
- 
     # If the change in center positions is less than epsilon, stop.     # If the change in center positions is less than epsilon, stop.
     centers_change = sum(np.sqrt(np.sum((a - b)**2)) for (a, b) in zip(centers, old_centers.value))     centers_change = sum(np.sqrt(np.sum((a - b)**2)) for (a, b) in zip(centers, old_centers.value))
Line 112: Line 111:
   centers.map(center => (center-point).norm(2)).zipWithIndex.min._2   centers.map(center => (center-point).norm(2)).zipWithIndex.min._2
  
-val lines = sc.textFile("/net/projects/hadoop/examples/inputs/points-small/points.txt")+val lines = sc.textFile("/net/projects/hadoop/examples/inputs/points-small/points.txt", sc.defaultParallelism)
 val data = lines.map(line => Vector(line.split("\\s+").map(_.toDouble))).cache() val data = lines.map(line => Vector(line.split("\\s+").map(_.toDouble))).cache()
  

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