ClassCastException：java.lang.Double 不能转换为 org。 apache.spark.mllib.linalg.Vector 使用 LabeledPoint 时

Question

I am trying to use SVMWithSGD to train my model, but I encounter ClassCastException while trying to access my training. My train_data dataframe schema looks like:

train_data.printSchema
root
 |-- label: string (nullable = true)
 |-- features: vector (nullable = true)
 |-- label_index: double (nullable = false)

I created an LabeledPoint RDD to use it on SVNWithSGD

    val targetInd = train_data.columns.indexOf("label_index")`
    val featInd = Array("features").map(train_data.columns.indexOf(_))  
    val train_lp = train_data.rdd.map(r => LabeledPoint( r.getDouble(targetInd),
    Vectors.dense(featInd.map(r.getDouble(_)).toArray)))

But When I call SVMWithSGD.train(train_lp, numIterations)

it gives me:

Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGSched
uler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGSche
duler.scala:1877)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGSche
duler.scala:1876)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:
59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)

  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.appl
y(DAGScheduler.scala:926)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.appl
y(DAGScheduler.scala:926)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.sc
ala:926)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGSche
duler.scala:2110)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGSchedu
ler.scala:2059)
  at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGSchedu
ler.scala:2048)
  at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
  at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
  at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
  at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1364)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:1
51)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:1
12)
  at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
  at org.apache.spark.rdd.RDD.take(RDD.scala:1337)
  at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1378)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:1
51)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:1
12)
  at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
  at org.apache.spark.rdd.RDD.first(RDD.scala:1377)
  at org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.generateInitia
lWeights(GeneralizedLinearAlgorithm.scala:204)
  at org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.run(Generalize
dLinearAlgorithm.scala:234)
  at org.apache.spark.mllib.classification.SVMWithSGD$.train(SVM.scala:217)
  at org.apache.spark.mllib.classification.SVMWithSGD$.train(SVM.scala:255)
  ... 55 elided
Caused by: java.lang.ClassCastException: java.lang.Double cannot be cast to org.
apache.spark.mllib.linalg.Vector

My train_data was created based on label (file_name) and features (json file representing images features).

Answer 1

Try using this -

Schema

train_data.printSchema
root
 |-- label: string (nullable = true)
 |-- features: vector (nullable = true)
 |-- label_index: double (nullable = false)

Modify your code as-

  val train_lp = train_data.rdd.map(r => LabeledPoint(r.getAs("label_index"), r.getAs("features")))