Load and process CSV content using spark. / published by https://github.com/dacr/code-examples-manager #a77196dd-c148-4f86-a7b7-e7a1b3805bc2/8e707313d3fe0ce549436b8b6d7e9d3436bb6cf7

spark-csv-load.sc

// summary : Load and process CSV content using spark.
// keywords : scala, feed, csv, bigdata, spark
// publish : gist
// authors : David Crosson
// license : Apache NON-AI License Version 2.0 (https://raw.githubusercontent.com/non-ai-licenses/non-ai-licenses/main/NON-AI-APACHE2)
// id : a77196dd-c148-4f86-a7b7-e7a1b3805bc2
// created-on : 2020-05-31T19:54:52Z
// managed-by : https://github.com/dacr/code-examples-manager
// execution : scala 2.12 ammonite script (http://ammonite.io/) - run as follow 'amm scriptname.sc'

/*
 spark 2.4.4 is only for scala 2.12, 2.5.x will bring scala 2.13 support

 ---------------

 In REPL mode use AmmoniteSparkSession instead of SparkSession

 import $ivy.`sh.almond::ammonite-spark:0.7.2`
 val spark =
   AmmoniteSparkSession.builder()
     .master("local[*]")
     .getOrCreate()
 */

import $ivy.`org.apache.spark::spark-sql:3.1.1`
import $ivy.`com.github.pathikrit::better-files:3.9.1`
import org.apache.spark.sql._

{
  import better.files._
  import better.files.Dsl._
  val csvFile = file"data.csv"
  csvFile < "id,name,age,gender\n"
  csvFile << "1,joe,32,1\n"
  csvFile << "2,sarah,42,2\n"
  csvFile << "3,john,4,1\n"
}


val spark =
  SparkSession.builder()
    .master("local[*]")
    .getOrCreate()

def sc = spark.sparkContext

val csvDataFrame =
  spark.read.format("csv")
    .option("sep", ",")
    .option("inferSchema", "true")
    .option("header", "true")
    .load("data.csv")

assert(csvDataFrame.count() == 3, "Didnt get the right row numbers")
assert(csvDataFrame.columns.size == 4, "Didnt get the right column numbers")