"main" java.lang.NoSuchMethodError: org.apache.spark.rdd.ShuffledRDD

[mindcrusher11]

whenever i try to run KNN regression using direct main method I am getting this error "main" java.lang.NoSuchMethodError: org.apache.spark.rdd.ShuffledRDD but when I try to run text cases it is working fine.as I read different articles i m getting most of suggestion as different versions but i tried by adding main class in
actual code itself after cloning

[mindcrusher11]

name := "SparkKnn"

version := "1.0"

scalaVersion := "2.10.5"

libraryDependencies ++= Seq(
"org.apache.spark" %% "spark-core" % "1.6.0",
"org.apache.spark" %% "spark-sql" % "1.6.0",
"org.apache.spark" %% "spark-mllib" % "1.6.0",
"io.snappydata" % "snappy-spark-mllib_2.10" % "1.6.2-1",
"saurfang"%"spark-knn"%"0.1.0"
)

spDependencies += "saurfang/spark-knn:0.1.0"

sparkComponents +="mllib"

sparkVersion := "1.6.0"

my sbt configuration

[mindcrusher11]

object SparkKnn {

def main(args:Array[String]) :Unit={

//val conf = new SparkConf().set("spark.serializer", "org.apache.spark.serializer.KryoSerializer").setMaster("local[4]")
val conf = configure("Popularity")
val sc = new SparkContext(conf)

val sqlContext = new org.apache.spark.sql.SQLContext(sc)

// this is used to implicitly convert an RDD to a DataFrame.
import sqlContext.implicits._
val training = MLUtils.loadLibSVMFile(sc, "/home/gaur/svmdata").toDF().select("features","label")

training.show()

val knn = new KNNRegression().setTopTreeSize(500 / 5).setK(3)

val knnModel = knn.fit(training)

//val predicted = knnModel.transform(training)

//predicted.show()

}

def configure(appName: String = "Sparkling Water Demo"): SparkConf = {
val conf = new SparkConf().setAppName(appName)
conf.setIfMissing("spark.master", sys.env.getOrElse("spark.master", "local[*]"))
conf
}
}

[mindcrusher11]

till show it is working fine it may be version issue but which version shall I use I checked in project folder 1.6.0 spark-core dependency is being used so i changed it to 1.6.0 but still iam getting same issue

[mindcrusher11]

with spark submit jar option it is working fine