equality of two data frames

Question

I have below scenario:

I have 2 dataframes containing only 1 column Lets say

DF1=(1,2,3,4,5)
DF2=(3,6,7,8,9,10)

Basically those values are keys and I am creating a parquet file of DF1 if the keys in DF1 are not in DF2 (In current example it should return false). My current way of achieving my requirement is:

val df1count= DF1.count
val df2count=DF2.count
val diffDF=DF2.except(DF1)
val diffCount=diffDF.count
if(diffCount==(df2count-df1count)) true
else false

The problem with this approach is I am calling action elements 4 times which is for sure not the best way. Can someone suggest me the best effective way of achieving this?

Answer 1

You can use below function:

import org.apache.spark.sql.functions._

def diff(key: String, df1: DataFrame, df2: DataFrame): DataFrame = {
  val fields = df1.schema.fields.map(_.name)
  val diffColumnName = "Diff"

  df1
    .join(df2, df1(key) === df2(key), "full_outer")
    .withColumn(
      diffColumnName,
      when(df1(key).isNull, "New row in DataFrame 2")
        .otherwise(
          when(df2(key).isNull, "New row in DataFrame 1")
            .otherwise(
              concat_ws("",
                fields.map(f => when(df1(f) =!= df2(f), s"$f ").otherwise("")):_*
              )
            )
        )
    )
    .filter(col(diffColumnName) =!= "")
    .select(
      fields.map(f =>
        when(df1(key).isNotNull, df1(f)).otherwise(df2(f)).alias(f)
      ) :+ col(diffColumnName):_*
    )
}

In your case run this:

diff("emp_id", df1, df2)

Example

import org.apache.spark.sql.{DataFrame, SparkSession}
import org.apache.spark.sql.functions._

object DiffDataFrames extends App {
  val session = SparkSession.builder().master("local").getOrCreate()

  import session.implicits._

  val df1 = session.createDataset(Seq((1,"a",11),(2,"b",2),(3,"c",33),(5,"e",5))).toDF("n", "s", "i")
  val df2 = session.createDataset(Seq((1,"a",11),(2,"bb",2),(3,"cc",34),(4,"d",4))).toDF("n", "s", "i")

  def diff(key: String, df1: DataFrame, df2: DataFrame): DataFrame =
  /* above definition */

  diff("n", df1, df2).show(false)
}

Answer 2

Here is a way to to get the uncommon rows between two dataframes:

val d1 = Seq((3, "Chennai", "rahman", "9848022330", 45000, "SanRamon"), (1, "Hyderabad", "ram", "9848022338", 50000, "SF"), (2, "Hyderabad", "robin", "9848022339", 40000, "LA"), (4, "sanjose", "romin", "9848022331", 45123, "SanRamon"))
val d2 = Seq((3, "Chennai", "rahman", "9848022330", 45000, "SanRamon"), (1, "Hyderabad", "ram", "9848022338", 50000, "SF"), (2, "Hyderabad", "robin", "9848022339", 40000, "LA"), (4, "sanjose", "romin", "9848022331", 45123, "SanRamon"), (4, "sanjose", "romino", "9848022331", 45123, "SanRamon"), (5, "LA", "Test", "1234567890", 12345, "Testuser"))

val df1 = d1.toDF("emp_id" ,"emp_city" ,"emp_name" ,"emp_phone" ,"emp_sal" ,"emp_site")
val df2 = d2.toDF("emp_id" ,"emp_city" ,"emp_name" ,"emp_phone" ,"emp_sal" ,"emp_site")

spark.sql("((select * from df1) union (select * from df2)) minus ((select * from df1) intersect (select * from df2))").show //spark is SparkSession