select specific columns after joining 2 dataframes in spark

Question

I have joined 2 dataframes and now trying to get a report comprising of columns from my both data frames. I tried using .select (cols = String* ) but it is not working.

Also the method described here doesnt seem to solve my issue.

Below is the code. val full_report is where I need to get the columns.

import org.apache.spark.sql.types._

object read_data {


  def main (args:Array[String]) {

    val spark = org.apache.spark.sql.SparkSession.builder
      .master("local")
      .appName("Spark CSV Reader")
      .getOrCreate;


    val customSchema = StructType(Array(
      StructField("order_id", IntegerType, true),
      StructField("parent_order_uuid", StringType, true),
      StructField("company", StringType, true),
      StructField("country_id", IntegerType, true)))

    val readogp = spark.read.format("csv")
      .option("header", "false")
      .schema(customSchema)
      .load("/home/cloudera/Desktop/ogp_csv.csv")

    readogp.show()

    val read_country = spark.read.format("csv")
      .option("header", "true")
      .load("/home/cloudera/Desktop/country.csv")

    read_country.show()

    println("************************************************************************")

   val full_report  = readogp.join(read_country, readogp.col("country_id") === read_country.col("country_id"))
       .select(readogp.select("order_id" + "parent_order_id"))  

    full.show()

  }

}

Please let me know how can I overcome this hurdle.

Answer 1

After joining dataframes, you can get specific columns using following syntax.

Based on your example:

val full_report_df  = readogp.join(read_country, readogp.col("country_id") == read_country.col("country_id"))

val full_report = full_report_df.select("order_id","parent_order_id")  

// Below will show 10 records for 2 columns order_id, parent_order_id.

full_report.show(10,false)