斯卡拉星火 - 调用createDataFrame

-1

当超载方法我尝试从双阵列像下面的Array（数组[数组[双]）创建一个数据框：斯卡拉星火 - 调用createDataFrame

val points : ArrayBuffer[Array[Double]] = ArrayBuffer(
Array(0.19238990024216676, 1.0, 0.0, 0.0), 
Array(0.2864319929878242, 0.0, 1.0, 0.0), 
Array(0.11160349352921925, 0.0, 2.0, 1.0), 
Array(0.3659220026496052, 2.0, 2.0, 0.0), 
Array(0.31809629470827383, 1.0, 1.0, 1.0)) 

val x = Array("__1", "__2", "__3", "__4") 
val myschema = StructType(x.map(fieldName ⇒ StructField(fieldName, DoubleType, true))) 

points.map(e => Row(e(0), e(1), e(2), e(3))) 
val newDF = sqlContext.createDataFrame(points, myschema)

但得到这个错误：

<console>:113: error: overloaded method value createDataFrame with alternatives: 
(data: java.util.List[_],beanClass: Class[_])org.apache.spark.sql.DataFrame <and> 
(rdd: org.apache.spark.api.java.JavaRDD[_],beanClass: Class[_])org.apache.spark.sql.DataFrame <and> 
(rdd: org.apache.spark.rdd.RDD[_],beanClass: Class[_])org.apache.spark.sql.DataFrame <and> 
(rows: java.util.List[org.apache.spark.sql.Row],schema: org.apache.spark.sql.types.StructType)org.apache.spark.sql.DataFrame <and> 
(rowRDD: org.apache.spark.api.java.JavaRDD[org.apache.spark.sql.Row],schema: org.apache.spark.sql.types.StructType)org.apache.spark.sql.DataFrame <and> 
(rowRDD: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row],schema: org.apache.spark.sql.types.StructType)org.apache.spark.sql.DataFrame 
cannot be applied to (scala.collection.mutable.ArrayBuffer[Array[Double]], org.apache.spark.sql.types.StructType) 
val newDF = sqlContext.createDataFrame(points, myschema)

我在互联网上搜索，但无法找到如何解决它！所以如果有人对此有任何想法，请帮助我！

来源

2017-02-13 zock king

-1

这个工作对我来说：

import org.apache.spark.sql._ 
import org.apache.spark.sql.types._ 
import scala.collection.mutable.ArrayBuffer 

val sqlContext = new org.apache.spark.sql.SQLContext(sc) 

val points : ArrayBuffer[Array[Double]] = ArrayBuffer(
    Array(0.19238990024216676, 1.0, 0.0, 0.0), 
    Array(0.2864319929878242, 0.0, 1.0, 0.0), 
    Array(0.11160349352921925, 0.0, 2.0, 1.0), 
    Array(0.3659220026496052, 2.0, 2.0, 0.0), 
    Array(0.31809629470827383, 1.0, 1.0, 1.0)) 

val x = Array("__1", "__2", "__3", "__4") 
val myschema = StructType(x.map(fieldName ⇒ StructField(fieldName, DoubleType, true))) 

val rdd = sc.parallelize(points.map(e => Row(e(0), e(1), e(2), e(3)))) 
val newDF = sqlContext.createDataFrame(rdd, myschema) 

newDF.show

来源

2017-02-13 15:16:55 semsorock

为什么downvoted我会欣赏一个解释。谢谢 – semsorock

谢谢！这适用于我！ –

接受ArrayBuffer[Array[Double]]实例的方法createDataFrame没有超载。您拨打points.map的电话没有被分配给任何内容，它将返回一个新实例，而不是在原地进行操作。尝试：

val points : List[Array[Double]] = List(
    Seq(0.19238990024216676, 1.0, 0.0, 0.0), 
    Seq(0.2864319929878242, 0.0, 1.0, 0.0), 
    Seq(0.11160349352921925, 0.0, 2.0, 1.0), 
    Seq(0.3659220026496052, 2.0, 2.0, 0.0), 
    Seq(0.31809629470827383, 1.0, 1.0, 1.0)) 

val x = Array("__1", "__2", "__3", "__4") 
val myschema = StructType(x.map(fieldName ⇒ StructField(fieldName, DoubleType, true))) 

val newDF = sqlContext.createDataFrame(
    points.map(Row.fromSeq(_), myschema)

来源

2017-02-13 14:53:53 ImDarrenG

斯卡拉星火 - 调用createDataFrame

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