.rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing) Error Spark Scala - scala

Question

Hello I am trying to extend the last value of each window to the rest of the window for the column count in order to create a flag which recognizes if the register is the last value of a window. I tried it this way but did not work.
Sample DF:
val df_197 = Seq [(Int, Int, Int, Int)]((1,1,7,10),(1,10,4,300),(1,3,14,50),(1,20,24,70),(1,30,12,90),(2,10,4,900),(2,25,30,40),(2,15,21,60),(2,5,10,80)).toDF("policyId","FECMVTO","aux","IND_DEF").orderBy(asc("policyId"), asc("FECMVTO"))
df_197.show
+--------+-------+---+-------+
|policyId|FECMVTO|aux|IND_DEF|
+--------+-------+---+-------+
| 1| 1| 7| 10|
| 1| 3| 14| 50|
| 1| 10| 4| 300|
| 1| 20| 24| 70|
| 1| 30| 12| 90|
| 2| 5| 10| 80|
| 2| 10| 4| 900|
| 2| 15| 21| 60|
| 2| 25| 30| 40|
+--------+-------+---+-------+
val juntar_riesgo = 1
val var_entidad_2 = $"aux"
//Particionar por uno o dos campos en funcion del valor de la variable juntar_riesgo
//Se creará window_number_2 basado en este particionamiento
val winSpec = if(juntar_riesgo == 1) {
Window.partitionBy($"policyId").orderBy($"FECMVTO")
} else {
Window.partitionBy(var_entidad_2,$"policyId").orderBy("FECMVTO")
}
val df_308 = df_307.withColumn("window_number", row_number().over(winSpec))
.withColumn("count", last("window_number",true) over (winSpec))
.withColumn("FLG_LAST_WDW", when(col("window_number") === col("count"),1).otherwise(lit(0))).show
Result (column count I would need to be 5 for all elements at 1st partition and 4 for all elements at 2nd partition):
+--------+-------+---+-------+-------------+-----+------------+
|policyId|FECMVTO|aux|IND_DEF|window_number|count|FLG_LAST_WDW|
+--------+-------+---+-------+-------------+-----+------------+
| 1| 1| 7| 10| 1| 1| 1|
| 1| 3| 14| 50| 2| 2| 1|
| 1| 10| 4| 300| 3| 3| 1|
| 1| 20| 24| 70| 4| 4| 1|
| 1| 30| 12| 90| 5| 5| 1|
| 2| 5| 10| 80| 1| 1| 1|
| 2| 10| 4| 900| 2| 2| 1|
| 2| 15| 21| 60| 3| 3| 1|
| 2| 25| 30| 40| 4| 4| 1|
+--------+-------+---+-------+-------------+-----+------------+
Then I read when you use orderBy after windowPartition clause, you must specify the clause .rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing) to achieve what I need. However, when I try it, I am facing this error:
val juntar_riesgo = 1
val var_entidad_2 = $"aux"
//Particionar por uno o dos campos en funcion del valor de la variable juntar_riesgo
//Se creará window_number_2 basado en este particionamiento
val winSpec = if(juntar_riesgo == 1) {
Window.partitionBy($"policyId").orderBy($"FECMVTO")
.rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing)
} else {
Window.partitionBy(var_entidad_2,$"policyId").orderBy("FECMVTO")
.rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing)
}
val df_198 = df_197.withColumn("window_number", row_number().over(winSpec))
.withColumn("count", last("window_number",true) over (winSpec))
.withColumn("FLG_LAST_WDW", when(col("window_number") === col("count"),1).otherwise(lit(0))).show
ERROR: org.apache.spark.sql.AnalysisException: Window Frame specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$()) must match the required frame specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$());
Thanks for your help!

Answer 1

You should not use last here but max without specifying an ordering:
val df_198 = df_197
.withColumn("window_number", row_number().over(Window.partitionBy($"policyId").orderBy($"FECMVTO")))
.withColumn("count", max("window_number") over (Window.partitionBy($"policyId")))
.withColumn("FLG_LAST_WDW", when(col("window_number") === col("count"),1).otherwise(lit(0))).show
+--------+-------+---+-------+-------------+-----+------------+
|policyId|FECMVTO|aux|IND_DEF|window_number|count|FLG_LAST_WDW|
+--------+-------+---+-------+-------------+-----+------------+
| 1| 1| 7| 10| 1| 5| 0|
| 1| 3| 14| 50| 2| 5| 0|
| 1| 10| 4| 300| 3| 5| 0|
| 1| 20| 24| 70| 4| 5| 0|
| 1| 30| 12| 90| 5| 5| 1|
| 2| 5| 10| 80| 1| 4| 0|
| 2| 10| 4| 900| 2| 4| 0|
| 2| 15| 21| 60| 3| 4| 0|
| 2| 25| 30| 40| 4| 4| 1|
+--------+-------+---+-------+-------------+-----+------------+
Note that you can write this shorter by calculating row_number with descending ordering and then take row_number===1:
val df_198 = df_197
.withColumn("FLG_LAT_WDW", when(row_number().over(Window.partitionBy($"policyId").orderBy($"FECMVTO".desc))===1,1).otherwise(0))
.show