Java Spark告诉我功能栏是错的

是什么导致了这个错误。我有点迷路了。 我所发现的一切都帮不了我

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)

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);

}

线程“main”java.lang.IllegalArgumentException中的异常：要求失败：列功能必须是struct类型，但实际上是struct。
在scala.Predef$.require处（Predef.scala:224）
位于org.apache.spark.ml.util.SchemaUtils$.checkColumnType（SchemaUtils.scala:43）
位于org.apache.spark.ml.Predictor参数$class.validateAndTransferorMschema（Predictor.scala:51）
在org.apache.spark.ml.classification.Classifier.org$apache$spark$ml$classification$classification$classificationparams$$super$validateandtransferormschema（Classifier.scala:58）
位于org.apache.spark.ml.classification.ClassifierParams$class.ValidateAndTransferorMschema（Classifier.scala:42）
在org.apache.spark.ml.classification.ProbabilisticClassifier.org$apache$spark$ml$classification$ProbabilisticClassifier参数$$super$validateAndTransferorMschema（ProbabilisticClassifier.scala:53）
在org.apache.spark.ml.classification.ProbabilisticClassifierParams$class.ValidateAndTransferorMschema（ProbabilisticClassifier.scala:37）上
位于org.apache.spark.ml.classification.ProbabilisticClassifier.ValidateAndTransferorMschema（ProbabilisticClassifier.scala:53）
位于org.apache.spark.ml.Predictor.transformSchema（Predictor.scala:144）
位于org.apache.spark.ml.PipelineStage.transformSchema（Pipeline.scala:74）
位于org.apache.spark.ml.Predictor.fit（Predictor.scala:100）
在classifier.Clasafie.trainModel\u MPC（Clasafie.java:46）上
MPC_分类器（Clasafie.java:75）
main（Clasafie.java:30）

代码部分：

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)

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);

}

公共静态多层PerceptronClassificationModel trainModel_MPC（SparkSession会话，JavaRDD数据）
{
int[]层={784800}；
MultilayerPerceptronClassifier模型=新的MultilayerPerceptronClassifier（）。设置层（层）
.setSeed（（长）42）、立根锁尺寸（128）、setMaxIter（1000）；
Dataset数据集=session.createDataFrame（data.rdd（），LabeledPoint.class）；
returnmodel.fit（数据集）；
}

我认为问题在于使用正确包中的

LabelPoint

类

检查完整的包并使用on from ml包而不是从mllib

我想，你正在使用-

org.apache.spark.mllib.regression.LabeledPoint

请使用（spark v2.0.0中介绍）-

org.apache.spark.ml.feature.LabeledPoint