Hi Reminia,
What Hequn said is correct.
However, I would *not* use a regular but model the problem as a
time-versioned table join.
A regular join will materialize both inputs which is probably not want you
want to do for a stream.
For a time-versioned table join, only the time-versioned table wou
Hi Reminia,
Currently, we can't join a DataStream with a DataSet in Flink. However, the
DataSet is actually a kind of bounded stream. From the point of this view,
you can use a streaming job to achieve your goal. Flink Table API & SQL
support different kinds of join[1]. You can take a closer look
Spark streaming supports direct join from stream DataFrame and batch
DataFrame , and it's
easy to implement an enrich pipeline that joins a stream and a dimension
table.
I checked the doc of flink, seems that this feature is a jira ticket which
haven't been resolved yet.
So how can I implement s
