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