Adding dataframes to List in Spark

Question

I'm trying to create "n" dataframes based on the data of one. I'm checking the Integer value of a column in dataframe and looping the sql sentence for creating "n" dataframes as many as Integers in the column.

This is my code:

val maxvalue = spark.sql("SELECT MAX(column4) as maxval FROM mydata").collect()(0).getInt(0)
for( i <- 0 to maxvalue){
         var query = "SELECT column1,colum2,colum3 FROM mydata WHERE column4 = "+ i
         val newdataframe = spark.sql(query)
         //add dataframe to List

}

I need to create "n" dataframes but I don't know how to declare the List type before loop and populate inside the for.

The existing dataframe data type:

// +------------+------------+------------+------------+
// |     column1|     column2|     column3|     column4|
// +------------+------------+------------+------------+
// |      String|      Double|         Int|         Int|
// +------------+------------+------------+------------+

The new dataframes data type:

// +------------+------------+------------+
// |     column1|     column2|     column3|     
// +------------+------------+------------+
// |      String|      Double|         Int|
// +------------+------------+------------+

Answer 1

You can create a mutable list and populate it:

val dfs = mutable.ArrayBuffer[DataFrame]()
for( i <- 0 to maxvalue){
  val query = "SELECT column1,colum2,colum3 FROM mydata WHERE column4 = "+ i
  val newdataframe = spark.sql(query)
  dfs += newdataframe
}

But a better approach (not using mutable data structure) is to map the list of integers into a list of DataFrames:

val dfs: Seq[DataFrame] = (0 to maxvalue).map { i => 
  spark.sql("SELECT column1,colum2,colum3 FROM mydata WHERE column4 = " + i)
}