[SPARK-25381] Stratified sampling by Column argument - ASF JIRA

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Details

Type: Improvement
Status: Resolved
Priority: Minor
Resolution: Fixed
Affects Version/s: 2.4.0
Fix Version/s: 3.0.0
Component/s: SQL
Labels:
None

Description

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|
       +-----+---+