我正在尝试使用IntellijIDEA中的线性回归在Spark ML中构建模型。
在拟合模型之前,我应该创建一个VectorAssembler
列feature
。
import org.apache.spark.ml.feature.VectorAssembler
import org.apache.spark.ml.linalg.Vectors
//creating features column
val assembler = new VectorAssembler()
.setInputCols(Array("col4","col5","col6","col7"))
.setOutputCol("features")
线程“main”中的异常java.lang.NoClassDefFoundError: org / apache / spark / ml / feature / VectorAssembler at energydata $ .main(energydata.scala:35)at energydata.main(energydata.scala)引起: 抛出java.lang.ClassNotFoundException: org.apache.spark.ml.feature.VectorAssembler at java.net.URLClassLoader.findClass(URLClassLoader.java:381)at java.lang.ClassLoader.loadClass(ClassLoader.java:424)at sun.misc.Launcher $ AppClassLoader.loadClass(Launcher.java:335)at at java.lang.ClassLoader.loadClass(ClassLoader.java:357)... 2更多
但这会给Intellij带来错误。当我在火花壳中尝试相同时,它的工作原理。
任何人都可以建议我在哪里出错?
name := "hello"
version := "1.0"
scalaVersion := "2.11.8"
libraryDependencies += "org.apache.spark" % "spark-core_2.11" % "2.1.0"
libraryDependencies += "org.apache.spark" % "spark-sql_2.11" % "2.1.0"
libraryDependencies += "com.datastax.spark" %% "spark-cassandra-connector" % "2.0.6"
libraryDependencies += "org.apache.spark" %% "spark-mllib" % "2.1.0" % "provided"