minor cleanup

Author: haoyuan

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -40,9 +40,6 @@ import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.serializer.{DeserializationStream, SerializationStream, SerializerInstance}
 
 
-
-
-
 /**
  * Various utility methods used by Spark.
  */
@@ -164,7 +161,7 @@ private[spark] object Utils extends Logging {
       shutdownDeletePaths += absolutePath
     }
   }
-  
+
   // Register the tachyon path to be deleted via shutdown hook
   def registerShutdownDeleteDir(tachyonfile: TachyonFile) {
     val absolutePath = tachyonfile.getPath()
@@ -180,7 +177,7 @@ private[spark] object Utils extends Logging {
       shutdownDeletePaths.contains(absolutePath)
     }
   }
-  
+
   // Is the path already registered to be deleted via a shutdown hook ?
   def hasShutdownDeleteTachyonDir(file: TachyonFile): Boolean = {
     val absolutePath = file.getPath()
@@ -204,7 +201,7 @@ private[spark] object Utils extends Logging {
     }
     retval
   }
-  
+
   // Note: if file is child of some registered path, while not equal to it, then return true;
   // else false. This is to ensure that two shutdown hooks do not try to delete each others
   // paths - resulting in Exception and incomplete cleanup.
@@ -573,7 +570,7 @@ private[spark] object Utils extends Logging {
       }
     }
   }
-  
+
   /**
    * Delete a file or directory and its contents recursively.
    */

core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala

@@ -411,6 +411,7 @@ class BlockManagerSuite extends FunSuite with BeforeAndAfter with PrivateMethodT
   }
 
   test("tachyon storage") {
+    // TODO Make the spark.test.tachyon.enable true after using tachyon 0.5.0 testing jar.
     val tachyonUnitTestEnabled = conf.getBoolean("spark.test.tachyon.enable", false)
     if (tachyonUnitTestEnabled) {
       store = new BlockManager("<driver>", actorSystem, master, serializer, 1200, conf, securityMgr)

examples/src/main/scala/org/apache/spark/examples/SparkTachyonHdfsLR.scala

@@ -26,7 +26,7 @@ import org.apache.spark.scheduler.InputFormatInfo
 import org.apache.spark.storage.StorageLevel
 
 /**
- * Logistic regression based classification. 
+ * Logistic regression based classification.
  * This example uses Tachyon to persist rdds during computation.
  */
 object SparkTachyonHdfsLR {
@@ -36,8 +36,6 @@ object SparkTachyonHdfsLR {
   case class DataPoint(x: Vector, y: Double)
 
   def parsePoint(line: String): DataPoint = {
-    //val nums = line.split(' ').map(_.toDouble)
-    //return DataPoint(new Vector(nums.slice(1, D+1)), nums(0))
     val tok = new java.util.StringTokenizer(line, " ")
     var y = tok.nextToken.toDouble
     var x = new Array[Double](D)
@@ -56,7 +54,7 @@ object SparkTachyonHdfsLR {
     val inputPath = args(1)
     val conf = SparkHadoopUtil.get.newConfiguration()
     val sc = new SparkContext(args(0), "SparkTachyonHdfsLR",
-      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass), Map(), 
+      System.getenv("SPARK_HOME"), SparkContext.jarOfClass(this.getClass), Map(),
       InputFormatInfo.computePreferredLocations(
         Seq(new InputFormatInfo(conf, classOf[org.apache.hadoop.mapred.TextInputFormat], inputPath))
       ))