Spark Dataframe using a new indicator column

Question

I need to group the “KEY” column and need to check if the “TYPE_CODE” column has the values ​​“PL” and “JL”, if so, I need to add an indicator column like “Y”, otherwise “N”,

Example:

    //Input Values
    val values = List(List("66","PL") ,
    List("67","JL") , List("67","PL"),List("67","PO"),
    List("68","JL"),List("68","PO")).map(x =>(x(0), x(1)))

    import spark.implicits._
    //created a dataframe
    val cmc = values.toDF("KEY","TYPE_CODE")

    cmc.show(false)
    ------------------------
    KEY |TYPE_CODE  |
    ------------------------
    66  |PL |
    67  |JL |
    67  |PL |
    67  |PO |
    68  |JL |
    68  |PO |
    -------------------------

Expected Result:

For each "KEY", if it has "TYPE_CODE", there is both PL and JL, then Y else N

    -----------------------------------------------------
    KEY |TYPE_CODE  | Indicator
    -----------------------------------------------------
    66  |PL         | N
    67  |JL         | Y
    67  |PL         | Y
    67  |PO         | Y
    68  |JL         | N
    68  |PO         | N
    ---------------------------------------------------

For example, 67 has both PL and JL - So "Y" 66 has only PL - So "N" 68 has only JL - So "N"

Answer 1

One option:

1) collect TYPE_CODE as a list;

2) , ;

3), explode:

(cmc.groupBy("KEY")
    .agg(collect_list("TYPE_CODE").as("TYPE_CODE"))
    .withColumn("Indicator", 
        when(array_contains($"TYPE_CODE", "PL") && array_contains($"TYPE_CODE", "JL"), "Y").otherwise("N"))
    .withColumn("TYPE_CODE", explode($"TYPE_CODE"))).show
+---+---------+---------+
|KEY|TYPE_CODE|Indicator|
+---+---------+---------+
| 68|       JL|        N|
| 68|       PO|        N|    
| 67|       JL|        Y|
| 67|       PL|        Y|
| 67|       PO|        Y|
| 66|       PL|        N|
+---+---------+---------+

Answer 2

:

• KEY agg ( JL PL),

• join DataFrame

:

val indicators = cmc.groupBy("KEY").agg(
  sum(when($"TYPE_CODE" === "PL", 1).otherwise(0)) as "pls",
  sum(when($"TYPE_CODE" === "JL", 1).otherwise(0)) as "jls"
).withColumn("Indicator", when($"pls" > 0 && $"jls" > 0, "Y").otherwise("N"))

val result = cmc.join(indicators, "KEY")
  .select("KEY", "TYPE_CODE", "Indicator")

, @Psidom, - collect_list , ( ).

, (.. JL/PL , ), indicators count, () :

val indicators = cmc
  .where($"TYPE_CODE".isin("PL", "JL"))
  .groupBy("KEY").count()
  .withColumn("Indicator", when($"count" === 2, "Y").otherwise("N"))