Currently the sampleBy method accepts the first argument of string type only. Need to provide overloaded method which accepts Column type too. So, it will allow sampling by multiple columns , for example:
import org.apache.spark.sql.Row import org.apache.spark.sql.functions.struct val df = spark.createDataFrame(Seq(("Bob", 17), ("Alice", 10), ("Nico", 8), ("Bob", 17), ("Alice", 10))).toDF("name", "age") val fractions = Map(Row("Alice", 10) -> 0.3, Row("Nico", 8) -> 1.0) df.stat.sampleBy(struct($"name", $"age"), fractions, 36L).show() +-----+---+ | name|age| +-----+---+ | Nico| 8| |Alice| 10| +-----+---+