Joining multiple dataframes horizontally

Question

I have the following dataframe

val count :Dataframe = spark.sql("select 1,$database_name,$table_name count(*) from $table_name ")

Output :

1,stock,T076p,4332

val dist_count :Dataframe = spark.sql("1,select distinct count(*) from $table_name")`

Output :

4112 or 4332(can be same )

val truecount : Dataframe = spark.sql("select 1,count(*) from $table_name where flag =true")`

Output :

4330

   val Falsecount : DataFrame = spark.sql("select 1,count(*) from $table_name where flag =false")

Output :

4332

Question : How do I join above dataframe to get the resultant dataframe which give me Output.
as the below.

stock ,T076p, 4332,4332,4330

Here comma is for column separator

P.S - I have added 1 to every dataframe so I can use join dataframes (so 1 is not mandatory here.)

Answer 1

Question :
How do I join above dataframe to get the resultant dataframe which give me o/p as the below.

stock ,T076p, 4332,4332,4330 -Here comma is for column seperator

just check this example. I have mimicked your requirement with dummy dataframes like below.

---

package com.examples

import org.apache.log4j.{Level, Logger}
import org.apache.spark.sql.SparkSession

object MultiDFJoin {
  def main(args: Array[String]) {
    import org.apache.spark.sql.functions._
    Logger.getLogger("org").setLevel(Level.OFF)

    val spark = SparkSession.builder.
      master("local")
      .appName(this.getClass.getName)
      .getOrCreate()
    import spark.implicits._
    val columns = Array("column1", "column2", "column3", "column4")
    val df1 = (Seq(
      (1, "stock", "T076p", 4332))
      ).toDF(columns: _*).as("first")
    df1.show()
    val df2 = Seq((1, 4332)).toDF(columns.slice(0, 2): _*).as("second")
    df2.show()
    val df3 = Seq((1, 4330)).toDF(columns.slice(0, 2): _*).as("third")
    df3.show()
    val df4 = Seq((1, 4332)).toDF(columns.slice(0, 2): _*).as("four")
    df4.show()
    val finalcsv = df1.join(df2, col("first.column1") === col("second.column1")).selectExpr("first.*", "second.column2")
      .join(df3, Seq("column1")).selectExpr("first.*", "third.column2")
      .join(df4, Seq("column1"))
      .selectExpr("first.*", "third.column2", "four.column2")
      .drop("column1").collect.mkString(",") // this column used for just joining hence dropping
    print(finalcsv)
  }
}

Result :

+-------+-------+-------+-------+
|column1|column2|column3|column4|
+-------+-------+-------+-------+
|      1|  stock|  T076p|   4332|
+-------+-------+-------+-------+

+-------+-------+
|column1|column2|
+-------+-------+
|      1|   4332|
+-------+-------+

+-------+-------+
|column1|column2|
+-------+-------+
|      1|   4330|
+-------+-------+

+-------+-------+
|column1|column2|
+-------+-------+
|      1|   4332|
+-------+-------+

[stock,T076p,4332,4330,4332]