Converting a string to double in a dataframe

问题:

I have built a dataframe using concat which produces a string.

import sqlContext.implicits._

val df = sc.parallelize(Seq((1.0, 2.0), (3.0, 4.0))).toDF("k", "v")
df.registerTempTable("df")

val dfConcat = df.select(concat($"k", lit(","), $"v").as("test"))

dfConcat: org.apache.spark.sql.DataFrame = [test: string]

+-------------+
|         test|
+-------------+
|      1.0,2.0|
|      3.0,4.0|
+-------------+

How can I convert it back to double?

I have tried casting to DoubleType but I get null

import org.apache.spark.sql.types._
 intterim.features.cast(IntegerType))

val testDouble = dfConcat.select( dfConcat("test").cast(DoubleType).as("test"))

+----+
|test|
+----+
|null|
|null|
+----+

and udf return number format exception at run time

import org.apache.spark.sql.functions._

val toDbl    = udf[Double, String]( _.toDouble)

val testDouble = dfConcat
.withColumn("test",      toDbl(dfConcat("test")))              
.select("test")

回答1:

You cannot convert it to double because it is simply not a valid double representation. If you want an array just use array function:

import org.apache.spark.sql.functions.array

df.select(array($"k", $"v").as("test"))

You can also try to split and convert but it is far from optimal:

import org.apache.spark.sql.types.{ArrayType, DoubleType}
import org.apache.spark.sql.functions.split

dfConcat.select(split($"test", ",").cast(ArrayType(DoubleType)))