[SPARK-33536] Incorrect join results when joining twice with the same DF

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 3.0.0, 3.0.1, 3.1.0
• Fix Version/s: 3.1.0
• Component/s: SQL
• Assignee: wuyi
• Reporter: wuyi
• Created: 24/Nov/20 14:19
• Updated: 20/May/21 03:27
• Resolved: 02/Dec/20 17:51

Description

val emp1 = Seq[TestData](
  TestData(1, "sales"),
  TestData(2, "personnel"),
  TestData(3, "develop"),
  TestData(4, "IT")).toDS()
val emp2 = Seq[TestData](
  TestData(1, "sales"),
  TestData(2, "personnel"),
  TestData(3, "develop")).toDS()
val emp3 = emp1.join(emp2, emp1("key") === emp2("key")).select(emp1("*"))
emp1.join(emp3, emp1.col("key") === emp3.col("key"), "left_outer").select(emp1.col("*"), emp3.col("key").as("e2")).show()

// wrong result
+---+---------+---+
|key|    value| e2|
+---+---------+---+
|  1|    sales|  1|
|  2|personnel|  2|
|  3|  develop|  3|
|  4|       IT|  4|
+---+---------+---+

Issue Links

• is related to: SPARK-35454 Ambiguous self-join doesn't fail after transfroming the dataset to dataframe
• links to: [Github] Pull Request #30488 (Ngone51)
• links to: [Github] Pull Request #30488 (Ngone51)
• links to: [Github] Pull Request #30682 (HyukjinKwon)
• links to: [Github] Pull Request #30682 (HyukjinKwon)