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enhancementNew feature or requestNew feature or requestgood first issueGood for newcomersGood for newcomers
Description
Is your feature request related to a problem or challenge?
Follow up issue from #12311
We have clickbench.slt that run the queries against 10 rows data for clickbench
It would be nice if we have similar for imdb benchmark
Describe the solution you'd like
The straightforward way is to copy & paste them all, but there are lots of file. It is better to read them by script and add query and add testID on top of them like and run with complete.
# 1a
query
SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'top 250 rank' AND mc.note not like '%(as Metro-Goldwyn-Mayer Pictures)%' and (mc.note like '%(co-production)%' or mc.note like '%(presents)%') AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id;
# 1b
query
SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'bottom 10 rank' AND mc.note not like '%(as Metro-Goldwyn-Mayer Pictures)%' AND t.production_year between 2005 and 2010 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id;
Describe alternatives you've considered
No response
Additional context
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enhancementNew feature or requestNew feature or requestgood first issueGood for newcomersGood for newcomers