dffromJdbcboundary.scala

// Method to generate Boundary Query
def buildBoundaryQuery(column: String, tableName: String): String = {
  s"(SELECT MIN(${column}) AS lowerBound, MAX(${column}) AS upperBound FROM ${tableName}) bq"
}
 
val bq = buildBoundaryQuery("id", tableName)
 
// Boundary Read Options
val boundaryReadOptions = Map(
  "driver" -> JDBC_DRIVER,
  "url" -> JDBC_URL,
  "user" -> JDBC_USERNAME,
  "password" -> JDBC_PASSWORD,
  "dbtable" -> bq
)
 
// Create DataFrame to execute Boundary Query on Source
val boundaryDF = (
  spark.read
  .options(boundaryReadOptions)
  .format("jdbc")
  .load
)
// Extract Lower Bound and Upper Bound Values to pass it to readOptions
import org.apache.spark.sql.functions.col
 
val bounds: (String, String) = (
  boundaryDF
  .select(col("lowerBound").cast(StringType).alias("lowerBound"), col("upperBound").cast(StringType).alias("upperBound"))
  .map(row => (row.getString(0), row.getString(1)))
  .first
)
 
val lowerBound: String = bounds._1
val upperBound: String = bounds._2
 
println("lowerBound and upperBound for 'id' column")
println(s"lowerBound => ${lowerBound}")
println(s"upperBound => ${upperBound}\n")
/*lowerBound and upperBound for 'id' column
lowerBound => 201
upperBound => 4079

import org.apache.spark.sql.functions.col
bounds: (String, String) = (201,4079)
lowerBound: String = 201
upperBound: String = 4079*/