Spark 告诉我特征列是错误的答案

【问题标题】：Spark is telling me that the features column is wrongSpark 告诉我特征列是错误的
【发布时间】：2020-10-10 01:24:18
【问题描述】：

什么可能导致此错误。我有点失落。我发现的一切都对我没有帮助。

堆栈跟踪：

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: Column features must be of type struct<type:tinyint,size:int,indices:array<int>,values:array<double>> but was actually struct<type:tinyint,size:int,indices:array<int>,values:array<double>>.
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:43)
at org.apache.spark.ml.PredictorParams$class.validateAndTransformSchema(Predictor.scala:51)
at org.apache.spark.ml.classification.Classifier.org$apache$spark$ml$classification$ClassifierParams$$super$validateAndTransformSchema(Classifier.scala:58)
at org.apache.spark.ml.classification.ClassifierParams$class.validateAndTransformSchema(Classifier.scala:42)
at org.apache.spark.ml.classification.ProbabilisticClassifier.org$apache$spark$ml$classification$ProbabilisticClassifierParams$$super$validateAndTransformSchema(ProbabilisticClassifier.scala:53)
at org.apache.spark.ml.classification.ProbabilisticClassifierParams$class.validateAndTransformSchema(ProbabilisticClassifier.scala:37)
at org.apache.spark.ml.classification.ProbabilisticClassifier.validateAndTransformSchema(ProbabilisticClassifier.scala:53)
at org.apache.spark.ml.Predictor.transformSchema(Predictor.scala:144)
at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:74)
at org.apache.spark.ml.Predictor.fit(Predictor.scala:100)
at classifier.Clasafie.trainModel_MPC(Clasafie.java:46)
at classifier.Clasafie.MPC_Classifier(Clasafie.java:75)
at classifier.Clasafie.main(Clasafie.java:30)

代码部分：

public static MultilayerPerceptronClassificationModel trainModel_MPC(SparkSession session,JavaRDD<LabeledPoint> data)
{

     int[] layers = {784,800};
     MultilayerPerceptronClassifier model = new MultilayerPerceptronClassifier().setLayers(layers)
             .setSeed((long) 42).setBlockSize(128).setMaxIter(1000);

     Dataset<Row> dataset = session.createDataFrame(data.rdd(), LabeledPoint.class);

     return model.fit(dataset);

}

【问题讨论】：

标签： java apache-spark apache-spark-mllib apache-spark-ml

【解决方案1】：

我认为问题在于使用正确包中的LabelPoint 类。

检查完整包并使用来自 ml 包而不是来自 mllib 的 on。

我想，你正在使用 -

org.apache.spark.mllib.regression.LabeledPoint

请使用（spark v2.0.0中引入）-

org.apache.spark.ml.feature.LabeledPoint

【讨论】：