Rename more than one column using withColumnRenamed

Question

I want to change names of two columns using spark withColumnRenamed function. Of course, I can write:

data = sqlContext.createDataFrame([(1,2), (3,4)], ['x1', 'x2'])
data = (data
       .withColumnRenamed('x1','x3')
       .withColumnRenamed('x2', 'x4'))

but I want to do this in one step (having list/tuple of new names). Unfortunately, neither this:

data = data.withColumnRenamed(['x1', 'x2'], ['x3', 'x4'])

nor this:

data = data.withColumnRenamed(('x1', 'x2'), ('x3', 'x4'))

is working. Is it possible to do this that way?

Answer 1

It is not possible to use a single withColumnRenamed call.

• You can use DataFrame.toDF method*

  data.toDF('x3', 'x4')
  

  or

  new_names = ['x3', 'x4']
  data.toDF(*new_names)
  

• It is also possible to rename with simple select:

  from pyspark.sql.functions import col
  
  mapping = dict(zip(['x1', 'x2'], ['x3', 'x4']))
  data.select([col(c).alias(mapping.get(c, c)) for c in data.columns])
  

Similarly in Scala you can:

• Rename all columns:

  val newNames = Seq("x3", "x4")
  
  data.toDF(newNames: _*)
  

• Rename from mapping with select:

  val  mapping = Map("x1" -> "x3", "x2" -> "x4")
  
  df.select(
    df.columns.map(c => df(c).alias(mapping.get(c).getOrElse(c))): _*
  )
  

  or foldLeft + withColumnRenamed

  mapping.foldLeft(data){
    case (data, (oldName, newName)) => data.withColumnRenamed(oldName, newName) 
  }
  

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* Not to be confused with RDD.toDF which is not a variadic functions, and takes column names as a list,