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[SPARK-4710] [mllib] Eliminate MLlib compilation warnings #3568

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[SPARK-4710] [mllib] Eliminate MLlib compilation warnings #3568

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2 changes: 2 additions & 0 deletions examples/src/main/scala/org/apache/spark/examples/mllib/DecisionTreeRunner.scala
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Expand Up @@ -17,6 +17,8 @@

package org.apache.spark.examples.mllib

import scala.language.reflectiveCalls

import scopt.OptionParser

import org.apache.spark.{SparkConf, SparkContext}
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16 changes: 8 additions & 8 deletions ...park/examples/mllib/StreamingKMeans.scala → ...amples/mllib/StreamingKMeansExample.scala
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Expand Up @@ -17,10 +17,10 @@

package org.apache.spark.examples.mllib

import org.apache.spark.SparkConf
import org.apache.spark.mllib.clustering.StreamingKMeans
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.regression.LabeledPoint
import org.apache.spark.mllib.clustering.StreamingKMeans
import org.apache.spark.SparkConf
import org.apache.spark.streaming.{Seconds, StreamingContext}

/**
Expand All @@ -36,28 +36,28 @@ import org.apache.spark.streaming.{Seconds, StreamingContext}
* `(y,[x1,x2,x3,...,xn])`
* Where y is some identifier. n must be the same for train and test.
*
* Usage: StreamingKmeans <trainingDir> <testDir> <batchDuration> <numClusters> <numDimensions>
* Usage:
* StreamingKMeansExample <trainingDir> <testDir> <batchDuration> <numClusters> <numDimensions>
*
* To run on your local machine using the two directories `trainingDir` and `testDir`,
* with updates every 5 seconds, 2 dimensions per data point, and 3 clusters, call:
* $ bin/run-example \
* org.apache.spark.examples.mllib.StreamingKMeans trainingDir testDir 5 3 2
* $ bin/run-example mllib.StreamingKMeansExample trainingDir testDir 5 3 2
*
* As you add text files to `trainingDir` the clusters will continuously update.
* Anytime you add text files to `testDir`, you'll see predicted labels using the current model.
*
*/
object StreamingKMeans {
object StreamingKMeansExample {

def main(args: Array[String]) {
if (args.length != 5) {
System.err.println(
"Usage: StreamingKMeans " +
"Usage: StreamingKMeansExample " +
"<trainingDir> <testDir> <batchDuration> <numClusters> <numDimensions>")
System.exit(1)
}

val conf = new SparkConf().setMaster("local").setAppName("StreamingLinearRegression")
val conf = new SparkConf().setMaster("local").setAppName("StreamingKMeansExample")
val ssc = new StreamingContext(conf, Seconds(args(2).toLong))

val trainingData = ssc.textFileStream(args(0)).map(Vectors.parse)
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