Spark Dataframe - 获取所有对列表（Scala）

Question

I have the following situation: I have a dataframe with an 'array' as the schema. Now I want to get for each array, all lists of pairs and save it again in a dataframe. So for example:

This is the original dataframe:

+---------------+
|  candidateList|
+---------------+
|         [1, 2]|
|      [2, 3, 4]|
|      [1, 3, 5]|
|[1, 2, 3, 4, 5]|
|[1, 2, 3, 4, 5]|
+---------------+

And that is how it have to look like after the computation:

+---------------+
|  candidates   |
+---------------+
|         [1, 2]|
|         [2, 3]|
|         [2, 4]|
|         [3, 4]|
|         [1, 3]|
|         [1, 5]|
|         [3, 5]|
|and so on...   |
+---------------+

I really don't know how this is possible in spark, maybe someone has a tip for me.

Kind regards

Answer 1

您需要创建一个 UDF（用户定义函数）并将其与explode函数一起使用。由于 Scala 集合的combinations方法，UDF 本身很简单：

import scala.collection.mutable
import org.apache.spark.sql.functions._
import spark.implicits._

val pairsUdf = udf((arr: mutable.Seq[Int]) => arr.combinations(2).toArray)
val result = df.select(explode(pairsUdf($"candidateList")) as "candidates")

result.show(numRows = 8)
// +----------+
// |candidates|
// +----------+
// |    [1, 2]|
// |    [2, 3]|
// |    [2, 4]|
// |    [3, 4]|
// |    [1, 3]|
// |    [1, 5]|
// |    [3, 5]|
// |    [1, 2]|
// +----------+