Spark DataFrame performance issue: select with where vs. filter

Question

Which of the following Spark operation has less memory and time overhead? N.B. Both operations are giving the same output.

  1.  val df2 = df1.select("*").where(df1("col").isNotNull)
  2.  val df2 = df1.filter(df1("col").isNotNull)