我正在运行scala 2.11.8和spark 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
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root
|-- id: long (nullable = true)
|-- features: vector (nullable = true)
[id: bigint, features: vector]
我在地图上遇到的错误(第116行)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)
数据框notesTokenized的第一个元素是Long,第二个是Vector,我不确定错误是什么。
答案 0 :(得分:1)
这可能是名称空间冲突:
DataFrame中的Vector
类型可能是org.apache.spark.mllib.linalg.Vector
,而我们在该函数中尝试匹配的Vector
是scala.collection.immutable.Vector