Foreach with Map in Scala - dataframe

Question

I have data with following countries and I want to pass country value in foreach loop with map to load the data into separate dataframe based on row restriction.
For Example,
Grouped Data:
Raw Data:
Results Table:
This is my Try
val x = ctrycnt.select("cnt").rdd.map(r => r(0)).collect() x.foreach { x=> var data = s"select * from smscnt_2020_table where Country=$x" }

Answer 1

I have attached the way I could think of. There is some difference in data as I had to cook data, could not directly extract from the problem as you have attached the image. Would be ease if you attached data so that anyone can copy.
Hope it helps
rest_csv:-
Country,Threshold,Row_Restriction
India,0,0
USA,25,5
Sweden,50,2
country_csv:-
Country,ContId,Agent,Threshold,RowNumber
India,123,A,0,1
India,124,A,0,2
India,125,A,0,3
India,126,A,0,4
USA,147,A,50,1
USA,148,A,50,2
USA,149,A,50,3
USA,147,A,50,4
USA,147,A,50,5
USA,146,A,50,6
USA,147,A,50,7
Sweden,152,A,25,1
Sweden,153,A,25,2
Sweden,154,A,25,3
Sweden,157,A,25,4
Sweden,158,A,25,5
Sweden,159,A,25,6
val countryDf = spark.read.format("csv").option("inferSchema","true").option("header",true).load(country_csv)
val restDf = spark.read.format("csv").option("inferSchema","true").option("header",true).load(rest_csv)
val newDf = countryDf.join(restDf,countryDf.col("Country").equalTo(restDf.col("Country")))
val finalDf = newDf.where(col("RowNumber").leq(col("Row_Restriction")).or(col("Row_Restriction").equalTo(lit(0)))).select(countryDf.col("*"))
finalDf.show
result:-
+-------+------+-----+---------+---------+
|Country|ContId|Agent|Threshold|RowNumber|
+-------+------+-----+---------+---------+
| India| 123| A| 0| 1|
| India| 124| A| 0| 2|
| India| 125| A| 0| 3|
| India| 126| A| 0| 4|
| USA| 147| A| 50| 1|
| USA| 148| A| 50| 2|
| USA| 149| A| 50| 3|
| USA| 147| A| 50| 4|
| USA| 147| A| 50| 5|
| Sweden| 152| A| 25| 1|
| Sweden| 153| A| 25| 2|
+-------+------+-----+---------+---------+