How to select last value in a pySpark DataFrame based on a datetime column

Question

I have a DataFrame df structured as follows:

date_time           id   value
2020-12-06 17:00    A    10
2020-12-06 17:05    A    18
2020-12-06 17:00    B    20
2020-12-06 17:05    B    28
2020-12-06 17:00    C    30
2020-12-06 17:05    C    38

And I have to select only the most recent row for each id in a DataFrame named df_last.

This is a solution that works:

from pyspark.sql import functions as F
from pyspark.sql.window import *

df_rows = df.withColumn('row_num', F.row_number().over(Window.partitionBy('id').orderBy(F.desc('date_time')))-1)
df_last = df_rows.filter(F.col('row_num')==0)

I wonder if there is a simpler/cleaner solution

Answer 1

That's pretty much the way to do it. Just some minor improvements that can be made - no need to subtract 1 from the row number:

from pyspark.sql import functions as F
from pyspark.sql.window import Window

df_rows = df.withColumn(
    'row_num', 
    F.row_number().over(Window.partitionBy('id').orderBy(F.desc('date_time')))
)
df_last = df_rows.filter('row_num = 1')