CODEWITHSUNDEEP
sqlscalaapache-spark
satyambansal117
satyambansal117

Reputation: 193

Data transformation in Spark Scala

I have the following dataframe

+-----+-----+-----+ .......+-------+
|item1|item2|item3|........| itemN |
+-----+-----+-----+........|-------+
|   v1|   v2|   v3|........| vN----+
|   v4|   v5|   v6|........| v2N---+
+-----+-----+-----+........|-------+

here item1 , item2 and item3 are the column names and table consists of 1 row v1,v2,v3.

I want to transform it into

colA   colB
item1    v1
item2    v2
item3    v3
 .        .
 .        .
 .        .

Here there are two columns lets say colA and colB and rows are as shown.

How to do this transformation in spark using scala?

Upvotes: 1

Views: 1069

Answers (1)

Tzach Zohar
Tzach Zohar

Reputation: 37832

You can use explode:

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

input.show()
// +-----+-----+-----+
// |item1|item2|item3|
// +-----+-----+-----+
// |   v1|   v2|   v3|
// |   v4|   v5|   v6|
// +-----+-----+-----+

val columns: Array[String] = input.columns

val result = input.explode(columns.map(s => col(s)): _*) {
  r: Row => columns.zipWithIndex.map { case (name, index) => (name, r.getAs[String](index)) }
}.select($"_1" as "colA", $"_2" as "colB")

result.show()
// +-----+----+
// | colA|colB|
// +-----+----+
// |item1|  v1|
// |item2|  v2|
// |item3|  v3|
// |item1|  v4|
// |item2|  v5|
// |item3|  v6|
// +-----+----+

Upvotes: 5

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