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Hi Ember,
(For some reason I don't see your reply in this Idea, although I received a copy of it in my notifications. )
I'm not that familar with the Python support for Db2 but the problem with the parameter markers might be because Python is trying to bind in a value, which is only necessary if the statement is actually executed, which shouldn't be the case when EXPLAIN MODE is RECOMMEND INDEXES. Does Python have support for preparing a statement or declaring a cursor? If so, that might avoid the issue. It works in CLP. i.e. "declare c1 cursor for select..." will result in index recommendations but the query is not executed until the cursor is opened.
Replacing the parameter marker with a literal could result in different index recommendations because the optimizer can compare the literal to the statistics to get a better filtering estimate. There are other optimizations possible such as introducing predicates implied via transitivity e.g. c1=1, c2=1 --> c1=c2.
Hi Ember,
Can you provide more details about why the RECOMMEND INDEXES and EVALUATE INDEXES explain modes are difficult to use from a Jupyter notebook and why using them would require the full Db2 client to be installed?
Supporting these explain modes with EXPLAIN_FROM_SECTION doesn't make sense architecturally because they require invoking the optimizer and that doesn't happen with EXPLAIN_FROM_SECTION. EXPLAIN_FROM_SECTION extracts explain information that is stored along with the access section and writes it to the explain tables. The SQL compiler and optimizer aren't called during this process. In order to support these index explain modes, the index recommendations would need to occur for every statement compilation and the resulting information would need to be stored along with the access section. This would increase prepare time and the size of access sections. I might be able to suggest an alternative way to accomplish what you want if I understand your use case better.