t; >
>> > I think what Arvid meant is a UNION ALL in SQL. You would normalize the
>> > two streams into a CarWithBrand before (containing nulls for the other
>> > side), and then groupBy/aggregate to the last value and filter out
>> > invalid CarWithBrands.
Hi,
We're trying to use Flink 1.11 Java tables API to process a streaming use
case:
We have 2 streams, each one with different structures. Both events,
coming from Kafka, can be:
- A new event (not in the system already)
- An updated event (updating an event that previously was inserted)
so we
