sorted the import following Spark coding convention

Author: Ken Takagiwa

streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala

@@ -19,42 +19,28 @@ package org.apache.spark.streaming.api.python
 
 import java.util.{List => JList, ArrayList => JArrayList, Map => JMap, Collections}
 
-import org.apache.spark.api.java.{JavaSparkContext, JavaPairRDD, JavaRDD}
-import org.apache.spark.broadcast.Broadcast
+import scala.reflect.ClassTag
+
 import org.apache.spark._
-import org.apache.spark.util.Utils
-import java.io._
-import scala.Some
-import org.apache.spark.streaming.Duration
-import scala.util.control.Breaks._
-import org.apache.spark.broadcast.Broadcast
-import scala.Some
-import org.apache.spark.streaming.Duration
 import org.apache.spark.rdd.RDD
-import org.apache.spark.api.python.PythonRDD
-
-
+import org.apache.spark.api.python._
+import org.apache.spark.broadcast.Broadcast
 import org.apache.spark.streaming.{Duration, Time}
 import org.apache.spark.streaming.dstream._
 import org.apache.spark.streaming.api.java._
-import org.apache.spark.rdd.RDD
-import org.apache.spark.api.python._
-import org.apache.spark.api.python.PairwiseRDD
-
 
-import scala.reflect.ClassTag
 
 
 class PythonDStream[T: ClassTag](
-                                  parent: DStream[T],
-                                  command: Array[Byte],
-                                  envVars: JMap[String, String],
-                                  pythonIncludes: JList[String],
-                                  preservePartitoning: Boolean,
-                                  pythonExec: String,
-                                  broadcastVars: JList[Broadcast[Array[Byte]]],
-                                  accumulator: Accumulator[JList[Array[Byte]]]
-                                  ) extends DStream[Array[Byte]](parent.ssc) {
+    parent: DStream[T],
+    command: Array[Byte],
+    envVars: JMap[String, String],
+    pythonIncludes: JList[String],
+    preservePartitoning: Boolean,
+    pythonExec: String,
+    broadcastVars: JList[Broadcast[Array[Byte]]],
+    accumulator: Accumulator[JList[Array[Byte]]])
+  extends DStream[Array[Byte]](parent.ssc) {
 
   override def dependencies = List(parent)
 
@@ -70,84 +56,4 @@ class PythonDStream[T: ClassTag](
     }
   }
   val asJavaDStream  = JavaDStream.fromDStream(this)
-
-  /**
-   * Print the first ten elements of each PythonRDD generated in this PythonDStream. This is an output
-   * operator, so this PythonDStream will be registered as an output stream and there materialized.
-   * Since serialized Python object is readable by Python, pyprint writes out binary data to
-   * temporary file and run python script to deserialized and print the first ten elements
-   */
-  private[streaming] def ppyprint() {
-    def foreachFunc = (rdd: RDD[Array[Byte]], time: Time) => {
-      val iter = rdd.take(11).iterator
-
-      // make a temporary file
-      val prefix = "spark"
-      val suffix = ".tmp"
-      val tempFile = File.createTempFile(prefix, suffix)
-      val tempFileStream = new DataOutputStream(new FileOutputStream(tempFile.getAbsolutePath))
-      //write out serialized python object
-      PythonRDD.writeIteratorToStream(iter, tempFileStream)
-      tempFileStream.close()
-
-      // This value has to be passed from python
-      //val pythonExec = new ProcessBuilder().environment().get("PYSPARK_PYTHON")
-      val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME")
-      //val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/streaming/pyprint.py", tempFile.getAbsolutePath())) // why this fails to compile???
-      //absolute path to the python script is needed to change because we do not use pysparkstreaming
-      val pb = new ProcessBuilder(pythonExec, sparkHome + "/python/pysparkstreaming/streaming/pyprint.py", tempFile.getAbsolutePath)
-      val workerEnv = pb.environment()
-
-      //envVars also need to be pass
-      //workerEnv.putAll(envVars)
-      val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH")
-      workerEnv.put("PYTHONPATH", pythonPath)
-      val worker = pb.start()
-      val is = worker.getInputStream()
-      val isr = new InputStreamReader(is)
-      val br = new BufferedReader(isr)
-
-      println ("-------------------------------------------")
-      println ("Time: " + time)
-      println ("-------------------------------------------")
-
-      //print value from python std out
-      var line = ""
-      breakable {
-        while (true) {
-          line = br.readLine()
-          if (line == null) break()
-          println(line)
-        }
-      }
-      //delete temporary file
-      tempFile.delete()
-      println()
-
-    }
-    new ForEachDStream(this, context.sparkContext.clean(foreachFunc)).register()
-  }
-}
-
-/*
-private class PairwiseDStream(prev:DStream[Array[Byte]]) extends
-DStream[(Long, Array[Byte])](prev.ssc){
-  override def dependencies = List(prev)
-
-  override def slideDuration: Duration = prev.slideDuration
-
-  override def compute(validTime:Time):Option[RDD[(Long, Array[Byte])]]={
-    prev.getOrCompute(validTime) match{
-      case Some(rdd)=>Some(rdd)
-        val pairwiseRDD = new PairwiseRDD(rdd)
-        Some(pairwiseRDD.asJavaPairRDD.rdd)
-      case None => None
-    }
-  }
-  val asJavaPairDStream : JavaPairDStream[Long, Array[Byte]] = JavaPairDStream(this)
 }
-*/
-
-
-
-