code: def rand(seed=None):
      
      sc = SparkContext._active_spark_context
      if seed is not None:
          jc = sc._jvm.functions.rand(seed)
      else:
          jc = sc._jvm.functions.rand()
      return Column(jc)
docs: Generates a random column with independent and identically distributed (i.i.d.) samples
      from U[0.0, 1.0].
  
      .. note:: The function is non-deterministic in general case.
  
      >>> df.withColumn('rand', rand(seed=42) * 3).collect()
      [Row(age=2, name=u'Alice', rand=2.4052597283576684),
       Row(age=5, name=u'Bob', rand=2.3913904055683974)]