Tempura: extending Calcite into an incremental query optimizer

As discussed in the email thread, this is an attempt to extend the Calcite optimizer into a general incremental query optimizer, based on our research paper published in VLDB 2021:
Tempura: a general cost-based optimizer framework for incremental data processing

To our best knowledge, this is the first general cost-based incremental optimizer that can find the best plan across multiple families of incremental computing methods, including IVM, Streaming, DBToaster, etc. Experiments (in the paper) shows that the generated best plan is consistently much better than the plans from each individual method alone.

In general, incremental query planning is central to database view maintenance and stream processing systems, and are being adopted in active databases, resumable query execution, approximate query processing, etc. We are hoping that this feature can help widening the spectrum of Calcite, solicit more use cases and adoption of Calcite.