Update Dataframe Schema Read Spark Scala - scala

Question

I am trying to read in a schema from hdfs to load into my dataframe. This allows the schema to be updated and reside outside the Spark Scala code. I was wondering what the best way was to do this? Below is what I have currently inside the code.
val schema_example = StructType(Array(
StructField("EXAMPLE_1", StringType, true),
StructField("EXAMPLE_2", StringType, true),
StructField("EXAMPLE_3", StringType, true))
def main(args: Array[String]): Unit = {
val df_example = get_df("example.txt", schema_example)
}
def get_df(filename: String, schema: StructType): DataFrame = {
val df = sqlContext.read
.format("com.databricks.spark.csv")
.option("delimiter","~")
.schema(schema)
.option("quote", "'")
.option("quoteMode", "ALL")
.load(filename)
df.select(df.columns.map(c => trim(col(c)).alias(c)): _*)
}

Answer 1

Better would be to read Schema from HOCON Config file, which can be updated as and when required.
schema[
{
columnName = EXAMPLE_1
type = string
},
{
columnName = EXAMPLE_2
type = string
},
{
columnName = EXAMPLE_3
type = string
}
]
They you can read this file using ConfigFactory.
This will be more better and cleaner way to maintain file schema.