Cassandra lightweight transactions

Question

I have a Flink job counts "application" events coming from a Kafka broker. I have a keyed window stream and, for each window, I count the number of events (I have 5-minutes windows). Finally I push the aggregated data into Cassandra with Cassandra Sink connector.

application	window_start	window_end	count
app1	2022-03-21 15:00:00	2022-03-21 15:05:00	15
app2	2022-03-21 15:00:00	2022-03-21 15:05:00	23

I also handle late events with side-outputs. So, when a late event arrives I have this situation:

| app1 | 2022-03-21 15:00:00 | 2022-03-21 15:05:00 | 1 |

The expected output must be:

application	window_start	window_end	count
app1	2022-03-21 15:00:00	2022-03-21 15:05:00	16
app2	2022-03-21 15:00:00	2022-03-21 15:05:00	23

But it is:

application	window_start	window_end	count
app1	2022-03-21 15:00:00	2022-03-21 15:05:00	1
app2	2022-03-21 15:00:00	2022-03-21 15:05:00	23

This because Cassandra uses UPSERT. With a SQL database (es. PostgreSQL) I can handle this problem:

"INSERT INTO table(window_start, window_end, application, count) VALUES(?, ?, ?, ?) ON CONFLICT (window_start, window_end, event_name, application) DO UPDATE SET count=EXCLUDED.count + table.count;"

Is it possible to make this kind of query with Cassandra, or this is a limitation?

Remember I'm using Apache Flink and Cassandra as Sink and Java is my programming language.

Thanks!