[SPARK-25381] Stratified sampling by Column argument

• Type: Improvement
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 2.4.0
• Fix Version/s: 3.0.0
• Component/s: SQL
• Assignee: Max Gekk
• Reporter: Max Gekk
• Created: 08/Sep/18 16:06
• Updated: 02/Oct/18 15:56
• Resolved: 20/Sep/18 17:13

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

Issue Links

• links to: [Github] Pull Request #22365 (MaxGekk)
• links to: [Github] Pull Request #22365 (MaxGekk)