Use Map to replace column values in Spark

Question

I have to map a list of columns to another column in a Spark dataset: think something like this

val translationMap: Map[Column, Column] = Map(
  lit("foo") -> lit("bar"),
  lit("baz") -> lit("bab")
)

And I have a dataframe like this one:

val df = Seq("foo", "baz").toDF("mov")

So I intend to perform the translation like this:

df.select(
  col("mov"),
  translationMap(col("mov"))
)

but this piece of code spits the following error

key not found: movs
java.util.NoSuchElementException: key not found: movs

Is there a way to perform such translation without concatenating hundreds of whens? think that translationMap could have lots of pairs key-value.

Answer 1

Instead of Map[Column, Column] you should use a Column containing a map literal:

import org.apache.spark.sql.functions.typedLit

val translationMap: Column = typedLit(Map(
  "foo" -> "bar",
  "baz" -> "bab"
))

The rest of your code can stay as-is:

df.select(
  col("mov"),
  translationMap(col("mov"))
).show

+---+---------------------------------------+
|mov|keys: [foo,baz], values: [bar,bab][mov]|
+---+---------------------------------------+
|foo|                                    bar|
|baz|                                    bab|
+---+---------------------------------------+