Convert Row to map in spark scala

Question

I have a row from a data frame and I want to convert it to a Map[String, Any] that maps column names to the values in the row for that column.

Is there an easy way to do it?

I did it for string values like

def rowToMap(row:Row): Map[String, String] = {
row.schema.fieldNames.map(field => field -> row.getAs[String](field)).toMap
}

val myRowMap = rowToMap(myRow)

If the row contains other values, not specific ones like String then the code gets messier because the row does not have a a method .get(field)

Any ideas?

Answer 1

You can use getValuesMap:

val df = Seq((1, 2.0, "a")).toDF("A", "B", "C")    
val row = df.first

To get Map[String, Any]:

row.getValuesMap[Any](row.schema.fieldNames)
// res19: Map[String,Any] = Map(A -> 1, B -> 2.0, C -> a)

Or you can get Map[String, AnyVal] for this simple case since the values are not complex objects

row.getValuesMap[AnyVal](row.schema.fieldNames)
// res20: Map[String,AnyVal] = Map(A -> 1, B -> 2.0, C -> a)

Note: _{the returned value type of the getValuesMap can be labelled as any type, so you can not rely on it to figure out what data types you have but need to keep in mind what you have from the beginning instead.}