在文本文件中写入/存储数据框 [英] Write/store dataframe in text file

问题描述

我正在尝试将dataframe写入text文件.如果文件包含单列，则可以在文本文件中写入.如果文件包含多列，那么我将面临一些错误

I am trying to write dataframe to text file. If a file contains single column then I am able to write in text file. If file contains multiple column then I a facing some error

文本数据源仅支持一列，并且您有2个 列.

Text data source supports only a single column, and you have 2 columns.

object replace {

  def main(args:Array[String]): Unit = {

    Logger.getLogger("org").setLevel(Level.ERROR)

    val spark = SparkSession.builder.master("local[1]").appName("Decimal Field Validation").getOrCreate()

    var sourcefile = spark.read.option("header","true").text("C:/Users/phadpa01/Desktop/inputfiles/decimalvalues.txt")

     val rowRDD = sourcefile.rdd.zipWithIndex().map(indexedRow => Row.fromSeq((indexedRow._2.toLong+1) +: indexedRow._1.toSeq)) //adding prgrefnbr               
                         //add column for prgrefnbr in schema
     val newstructure = StructType(Array(StructField("PRGREFNBR",LongType)).++(sourcefile.schema.fields))

     //create new dataframe containing prgrefnbr

     sourcefile = spark.createDataFrame(rowRDD, newstructure)
     val op= sourcefile.write.mode("overwrite").format("text").save("C:/Users/phadpa01/Desktop/op")

  }

}

推荐答案

您可以将数据帧转换为rdd并将隐蔽的行转换为字符串，并将最后一行写为

you can convert the dataframe to rdd and covert the row to string and write the last line as

 val op= sourcefile.rdd.map(_.toString()).saveAsTextFile("C:/Users/phadpa01/Desktop/op")

已编辑

正如@philantrovert和@Pravinkumar指出的那样，以上内容将在输出文件中附加[和]，这是正确的.解决的办法是用empty字符将replace用作

As @philantrovert and @Pravinkumar have pointed that the above would append [ and ] in the output file, which is true. The solution would be to replace them with empty character as

val op= sourcefile.rdd.map(_.toString().replace("[","").replace("]", "")).saveAsTextFile("C:/Users/phadpa01/Desktop/op")

一个人甚至可以使用regex

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