scala.MatchError上数据帧映射到RDD

Question

我运行阶2.11.8和火花2.0

notesTokenized.head(1).foreach(println) 
notesTokenized.printSchema() 
println(notesTokenized) 
val lda_countVector = notesTokenized.rdd.map { case Row(id: Long, features: Vector) => (id, features) 
lda_countVector.take(5).foreach(println) 

输出是

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
root 
|-- id: long (nullable = true) 
|-- features: vector (nullable = true) 

[id: bigint, features: vector] 

我在地图获取（其为线116上的错误）是：

scala.MatchError: 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

(of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema) 
    at com.tera.topic.features.FeatureConstruction$$anonfun$1.apply(FeatureConstruction.scala:116) 
    at com.tera.topic.features.FeatureConstruction$$anonfun$1.apply(FeatureConstruction.scala:116) 
    at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) 

数据帧notesTokenized的第一个元素是Long，第二个是Vector，我不知道错误是什么。

Answer 1

这可能是一个命名空间冲突：

的Vector类型的数据帧可能是一个org.apache.spark.mllib.linalg.Vector，而我们正试图在功能匹配Vector是scala.collection.immutable.Vector