Sunday, 3 March 2019

How to select multiple columns from a spark data frame using List[Column]


Let us create Example DataFrame to explain how to select List of columns of type "Column" from a dataframe

spark-shell --queue= *;

To adjust logging level use sc.setLogLevel(newLevel).
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.6.0
Spark context available as sc 
SQL context available as sqlContext.

scala>  val sqlcontext = new org.apache.spark.sql.SQLContext(sc)
sqlcontext: org.apache.spark.sql.SQLContext = org.apache.spark.sql.SQLContext@4f9a8d71  

scala> val BazarDF = Seq(
     | ("Veg", "tomato", 1.99),
     | ("Veg", "potato", 0.45),
     | ("Fruit", "apple", 0.99),
     | ("Fruit", "pineapple", 2.59),
     | ("Fruit", "apple", 1.99)
     | ).toDF("Type", "Item", "Price")
BazarDF: org.apache.spark.sql.DataFrame = [Type: string, Item: string, Price: double]

scala> BazarDF.show()
+-----+---------+-----+
| Type|     Item|Price|
+-----+---------+-----+
|  Veg|   tomato| 1.99|
|  Veg|   potato| 0.45|
|Fruit|    apple| 0.99|
|Fruit|pineapple| 2.59|
|Fruit|    apple| 1.99|
+-----+---------+-----+

Create a List[Column] with column names.

scala> var selectExpr : List[Column] = List("Type","Item","Price")
<console>:25: error: not found: type Column
         var selectExpr : List[Column] = List("Type","Item","Price")
                               ^

If you are getting the same error Please take a look into this page .
Using : _* annotation select the columns from dataframe.

scala> var dfNew = BazarDF.select(selectExpr: _*)
dfNew: org.apache.spark.sql.DataFrame = [Type: string, Item: string, Price: double]

scala> dfNew.show()
+-----+---------+-----+
| Type|     Item|Price|
+-----+---------+-----+
|  Veg|   tomato| 1.99|
|  Veg|   potato| 0.45|
|Fruit|    apple| 0.99|
|Fruit|pineapple| 2.59|
|Fruit|    apple| 1.99|
+-----+---------+-----+


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