Hi @Shazal Gomes​ ,

I found out using pyspark this solution

from pyspark.sql import functions as F
from pyspark.sql.window import Window
from pyspark.sql import Row
from pyspark.sql.types import *
 
 
 
ids = ["33", "272", "317", "318"]
df_ids = spark.createDataFrame([Row(ID = i) for i in ids])
 
display(
  df_ids.withColumn(
    'PREVIOUS_ID', F.concat_ws('/',F.array_sort(F.collect_set(F.col('ID')).over(Window.orderBy(F.col('ID').cast('integer'))).cast('array<integer>')))
  )
)

Let me know if It meets your need.