Hey everyone, I'm trying to use Flink SQL to construct a set of transformations for my application. Let's say the topology just has three steps:
- SQL Source - SQL SELECT statement - SQL Sink (via INSERT) The sink I'm using (JDBC) would really benefit from data partitioning (by PK ID) to avoid conflicting transactions and deadlocks. I can force Flink to partition the data by the PK ID before the INSERT by resorting to DataStream API and leveraging the keyBy method, then transforming DataStream back to the Table again... Is there a simpler way to do this? I understand that, for example, a GROUP BY statement will probably perform similar data shuffling, but what if I have a simple SELECT followed by INSERT? Thank you!
