如何从Scala的Iterables列表创建DataFrame? [英] How to create DataFrame from Scala's List of Iterables?

问题描述

我有以下Scala值:

I have the following Scala value:

val values: List[Iterable[Any]] = Traces().evaluate(features).toList

，我想将其转换为DataFrame.

and I want to convert it to a DataFrame.

当我尝试以下操作时:

sqlContext.createDataFrame(values)

我收到此错误:

error: overloaded method value createDataFrame with alternatives:

[A <: Product](data: Seq[A])(implicit evidence$2: reflect.runtime.universe.TypeTag[A])org.apache.spark.sql.DataFrame 
[A <: Product](rdd: org.apache.spark.rdd.RDD[A])(implicit evidence$1: reflect.runtime.universe.TypeTag[A])org.apache.spark.sql.DataFrame
cannot be applied to (List[Iterable[Any]])
          sqlContext.createDataFrame(values)

为什么?

推荐答案

正如 zero323 所述，我们需要先进行转换List[Iterable[Any]]到List[Row]，然后将行放在RDD中，并为spark数据框准备架构.

As zero323 mentioned, we need to first convert List[Iterable[Any]] to List[Row] and then put rows in RDD and prepare schema for the spark data frame.

要将List[Iterable[Any]]转换为List[Row]，我们可以说

To convert List[Iterable[Any]] to List[Row], we can say

val rows = values.map{x => Row(x:_*)}

然后使用类似schema的架构，我们可以制作RDD

and then having schema like schema, we can make RDD

val rdd = sparkContext.makeRDD[RDD](rows)

最后创建一个火花数据框

and finally create a spark data frame

val df = sqlContext.createDataFrame(rdd, schema)

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