Hi all, I have a user case where I want to merge several upstream data source (Kafka topics). The data are essential the same, but they have different field names.
I guess I can say my problem is not so much about flink itself. It is about how to deserialize data and merge different data effectively with flink. I can define different schemas and then deserialize data and merge them manually. I wonder if there is any dynamical way to do such thing, that is, I want to changing field names works like changing pandas dataframe column names. I see there is already https://cwiki.apache.org/confluence/display/FLINK/FLIP-120%3A+Support+conversion+between+PyFlink+Table+and+Pandas+DataFrame but resorting to pandas implies I need to work with python, which is something I prefer not to do. What is your practice on dynamically changing sources and merging them? I'd love to here your opinion. Bests, Yi
