如何将 Spark 中“Dataframe"的两列合并为一个 2-Tuple? [英] How to merge two columns of a `Dataframe` in Spark into one 2-Tuple?
问题描述
我有一个包含五列的 Spark DataFrame
df
.我想添加另一列,其值是第一列和第二列的元组.使用 withColumn() 方法时,出现不匹配错误,因为输入不是列类型,而是 (Column,Column).在这种情况下,我想知道除了在行上运行 for 循环之外是否还有其他解决方案?
I have a Spark DataFrame
df
with five columns. I want to add another column with its values being the tuple of the first and second columns. When using with withColumn() method, I get the mismatch error, because the input is not Column type, but instead (Column,Column). I wonder if there is a solution beside running for loop over the rows in this case?
var dfCol=(col1:Column,col2:Column)=>(col1,col2)
val vv = df.withColumn( "NewColumn", dfCol( df(df.schema.fieldNames(1)) , df(df.schema.fieldNames(2)) ) )
推荐答案
您可以使用用户定义的函数 udf
来实现您想要的.
You can use a User-defined function udf
to achieve what you want.
object TupleUDFs {
import org.apache.spark.sql.functions.udf
// type tag is required, as we have a generic udf
import scala.reflect.runtime.universe.{TypeTag, typeTag}
def toTuple2[S: TypeTag, T: TypeTag] =
udf[(S, T), S, T]((x: S, y: T) => (x, y))
}
用法
df.withColumn(
"tuple_col", TupleUDFs.toTuple2[Int, Int].apply(df("a"), df("b"))
)
假设a"和b"是您想要放入元组的 Int
类型的列.
assuming "a" and "b" are the columns of type Int
you want to put in a tuple.
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