*The distinct transformation does not preserve order, you need to distinct
first, then orderby.*
Thanks Enrico. You are correct. Worked fine!
joint_accounts.
select(year(col("transactiondate")).as("Year")
, month(col("transactiondate")).as("Month")
, sum("moneyin").over(wSpec).cast(
or just use SQL, which is less verbose, easily readable, and takes care of
all such scenarios. But for some weird reason I have found that people
using data frame API's have a perception that using SQL is less
intelligent. But I think that using less effort to get better output can me
a measure of
The distinct transformation does not preserve order, you need to
distinct first, then orderby.
Enrico
Am 06.01.20 um 00:39 schrieb Mich Talebzadeh:
Hi,
I am working out monthly outgoing etc from an account and I am using
the following code
import org.apache.spark.sql.expressions.Window
va
Hi,
I am working out monthly outgoing etc from an account and I am using the
following code
import org.apache.spark.sql.expressions.Window
val wSpec =
Window.partitionBy(year(col("transactiondate")),month(col("transactiondate")))
joint_accounts.
select(year(col("transactiondate")).as("Year"
