spark2.0+不用集成第三方的库，可以很方便进行读写csv文件
import org.apache.spark.sql.{DataFrame, SQLContext}
import org.apache.spark.{SparkConf, SparkContext}
object SparkReadFile {
def main(args: Array[String]): Unit = {
val localpath=”E:\\input\\test.csv”
val outpath=”E:\\output\\word”
val conf = new SparkConf()
conf.setAppName(“SparkReadFile”)
conf.setMaster(“local”)
val sparkContext = new SparkContext(conf)
val sqlContext = new SQLContext(sparkContext)
//读csv文件
val data: DataFrame = sqlContext.read.format(“com.databricks.spark.csv”)
.option(“header”, “false”) //在csv第一行有属性”true”，没有就是”false”
.option(“inferSchema”, true.toString) //这是自动推断属性列的数据类型
.load(localpath)
// data.show()
// 写csv文件
data.repartition(1).write.format(“com.databricks.spark.csv”)
.option(“header”, “false”)//在csv第一行有属性”true”，没有就是”false”
.option(“delimiter”,”,”)//默认以”,”分割
.save(outpath)
sparkContext.stop()
}
}