Add an aggregate of column to existing spark streaming dataframe - apache-spark

Question

I need to add an aggregated column to a spark streaming dataframe.
My spark dataframe has this form:
+-----------+---------+
| Timestamp | User_id |
+-----------+---------+
| 123343222 | 01 |
| 121212122 | 02 |
| 121212121 | 03 |
+-----------+---------+
I need to have a spark streaming dataframe of that form:
+-----------+---------+--------------+
| Timestamp | User_id | Array_UID |
+-----------+---------+--------------+
| 123343222 | 01 | [01] |
| 121212122 | 02 | [01, 02] |
| 121212121 | 03 | [01, 02, 03] |
+-----------+---------+--------------+
After the creation of this spark streaming dataframe I need to process it with a udf that needs to take in consideration all the user id already arrived.
I tried to collect the id using this code:
presenceDF = dfStreaming\
.groupBy(
window("timestamp", "30 minutes", "30 minutes"), \
).agg((F.collect_set(F.col("User_id"))).alias("Array")) \
The result is the following:
+---------+--------------+
| Window | Array |
+---------+--------------+
| W1 | [01] |
| W2 | [01, 02] |
| W3 | [01, 02, 03] |
+---------+--------------+
I need to have also the information of the latest User_id arrived, that's because this form doesn't work for me.
Is there a way to add the Array column to the streaming dataframe, preserving the original columns?
In static dataframe you can achieve that making a self join, but here is not possible.
Any help?