Where toDF in Spark-shell, how to use with Vector, Seq or other?

Question

I try some basic data types,

val x = Vector("John Smith", 10, "Illinois")
val x = Seq("John Smith", 10, "Illinois")
val x = Array("John Smith", 10, "Illinois")
val x = ...
val x = Seq( Vector("John Smith",10,"Illinois"), Vector("Foo",2,"Bar"))

but no one offer toDF(), even after import spark.implicits._.

My aim is to use someting as x.toDF("name","age","city").show

In the last example the toDF exists, but error "java.lang.ClassNotFoundException".

---

NOTES:

• I am using Spark-shell with Spark v2.2.

• Need generic transformation based on colunm names parametrized in toDF(names), not complex solutions as create Vector of case class Person(name: String, age: Long, city: String)

Expected result of show after toDF is

+----------+---+--------+
|      name|age|    city|
+----------+---+--------+
|John Smith| 10|Illinois|
+----------+---+--------+

Answer 1

you should put values in tuple to create 3 columns

scala> Seq(("John Smith", "asd", "Illinois")).toDF("name","age","city").show
+----------+---+--------+
|      name|age|    city|
+----------+---+--------+
|John Smith|asd|Illinois|
+----------+---+--------+