The main difference use case between orderBY and sort

[Ashok Kumar]

Hi,
In Spark programing I can use
df.filter(col("transactiontype") === 
"DEB").groupBy("transactiondate").agg(sum("debitamount").cast("Float").as("Total
 Debit Card")).orderBy("transactiondate").show(5)
or
df.filter(col("transactiontype") === 
"DEB").groupBy("transactiondate").agg(sum("debitamount").cast("Float").as("Total
 Debit Card")).sort("transactiondate").show(5)

i get the same results
and i can use both as well
df.ilter(col("transactiontype") === 
"DEB").groupBy("transactiondate").agg(sum("debitamount").cast("Float").as("Total
 Debit Card")).orderBy("transactiondate").sort("transactiondate").show(5)

but the last one takes more time.
what is the use case for both these please. does it make sense to use both?
Thanks