Merge Spark output CSV files with a single header

Question

I want to create a data processing pipeline in AWS to eventually use the processed data for Machine Learning.

I have a Scala script that takes raw data from S3, proc

Answer 1

To merge files in a folder into one file:

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs._

def merge(srcPath: String, dstPath: String): Unit =  {
  val hadoopConfig = new Configuration()
  val hdfs = FileSystem.get(hadoopConfig)
  FileUtil.copyMerge(hdfs, new Path(srcPath), hdfs, new Path(dstPath), false, hadoopConfig, null)
}

If you want to merge all files into one file, but still in the same folder (but this brings all data to the driver node):

dataFrame
      .coalesce(1)
      .write
      .format("com.databricks.spark.csv")
      .option("header", "true")
      .save(out)

Another solution would be to use solution #2 then move the one file inside the folder to another path (with the name of our CSV file).

def df2csv(df: DataFrame, fileName: String, sep: String = ",", header: Boolean = false): Unit = {
    val tmpDir = "tmpDir"

    df.repartition(1)
      .write
      .format("com.databricks.spark.csv")
      .option("header", header.toString)
      .option("delimiter", sep)
      .save(tmpDir)

    val dir = new File(tmpDir)
    val tmpCsvFile = tmpDir + File.separatorChar + "part-00000"
    (new File(tmpCsvFile)).renameTo(new File(fileName))

    dir.listFiles.foreach( f => f.delete )
    dir.delete
}