how to read a whole directory of XLSX with apache spark scala?

I have to read a whole directory of xlsx files, and I need to load all the directory with Apache Spark using Scala.

Actually I'm using this dependency : "com.crealytics" %% "spark-excel" % "0.12.3", and I don't know how to load all.

There doesnt seem a shortcut option to be put into the path through option method. So I have created a workaround as below(assuming each excel file has same number of columns). Created a method to get all the paths of every file in the source directory and ran a loop over those file paths creating new dataframe and appending to the previous one.

import java.io.File
import org.apache.spark.sql.Row
import org.apache.spark.sql.types._

def getListOfFiles(dir : String) : List[File] = {
  val d = new File(dir)
  if (d.exists && d.isDirectory){
    d.listFiles().filter(_.isFile).toList
  } else {
      List[File]()
  }
}

val path = " \\directory path"

// shows list of files with fully qualified paths
println(getListOfFiles(path))

val schema = StructType(
    StructField("id", IntegerType, true) ::
    StructField("name", StringType, false) ::
    StructField("age", IntegerType, false) :: Nil)


// Created Empty dataframe with as many columns as in each excel
var data = spark.createDataFrame(spark.sparkContext.emptyRDD[Row], schema)
for(filePath <- getListOfFiles(path)){
  var tempDF = spark.read.format("com.crealytics.spark.excel")
    .option("location", s"$filePath")
    .option("useHeader", "true")
    .option("treatEmptyValuesAsNulls", "true")
    .option("inferSchema", "true")
    .option("addColorColumns", "False")
    .load()
  data = data.union(tempDF)
}

data.show()