-- LOAD 'auto_explain';
-- set work_mem='1GB';
-- set max_parallel_workers=0;
-- set max_parallel_workers_per_gather=0;
-- set jit=off;
--set enable_nestloop=off;
--set enable_mergejoin=off;
-- set auto_explain.log_min_duration=0;
-- set auto_explain.log_analyze=on;
-- set auto_explain.add_statistics_threshold=10;
set enable_resultcache=false;

explain analyze SELECT MIN(chn.name) AS uncredited_voiced_character,
       MIN(t.title) AS russian_movie
FROM char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     company_type AS ct,
     movie_companies AS mc,
     role_type AS rt,
     title AS t
WHERE ci.note LIKE '%(voice)%'
  AND ci.note LIKE '%(uncredited)%'
  AND cn.country_code = '[ru]'
  AND rt.role = 'actor'
  AND t.production_year > 2005
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mc.movie_id
  AND chn.id = ci.person_role_id
  AND rt.id = ci.role_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(chn.name) AS character,
       MIN(t.title) AS russian_mov_with_actor_producer
FROM char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     company_type AS ct,
     movie_companies AS mc,
     role_type AS rt,
     title AS t
WHERE ci.note LIKE '%(producer)%'
  AND cn.country_code = '[ru]'
  AND rt.role = 'actor'
  AND t.production_year > 2010
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mc.movie_id
  AND chn.id = ci.person_role_id
  AND rt.id = ci.role_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(chn.name) AS character,
       MIN(t.title) AS movie_with_american_producer
FROM char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     company_type AS ct,
     movie_companies AS mc,
     role_type AS rt,
     title AS t
WHERE ci.note LIKE '%(producer)%'
  AND cn.country_code = '[us]'
  AND t.production_year > 1990
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mc.movie_id
  AND chn.id = ci.person_role_id
  AND rt.id = ci.role_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;
explain analyze SELECT MIN(cn.name) AS from_company,
       MIN(lt.link) AS movie_link_type,
       MIN(t.title) AS non_polish_sequel_movie
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND t.production_year BETWEEN 1950 AND 2000
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS from_company,
       MIN(lt.link) AS movie_link_type,
       MIN(t.title) AS sequel_movie
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follows%'
  AND mc.note IS NULL
  AND t.production_year = 1998
  AND t.title LIKE '%Money%'
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS from_company,
       MIN(mc.note) AS production_note,
       MIN(t.title) AS movie_based_on_book
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '20th Century Fox%'
       OR cn.name LIKE 'Twentieth Century Fox%')
  AND ct.kind != 'production companies'
  AND ct.kind IS NOT NULL
  AND k.keyword IN ('sequel',
                    'revenge',
                    'based-on-novel')
  AND mc.note IS NOT NULL
  AND t.production_year > 1950
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS from_company,
       MIN(mc.note) AS production_note,
       MIN(t.title) AS movie_based_on_book
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND ct.kind != 'production companies'
  AND ct.kind IS NOT NULL
  AND k.keyword IN ('sequel',
                    'revenge',
                    'based-on-novel')
  AND mc.note IS NOT NULL
  AND t.production_year > 1950
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS drama_horror_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     title AS t
WHERE cn.country_code = '[us]'
  AND ct.kind = 'production companies'
  AND it1.info = 'genres'
  AND it2.info = 'rating'
  AND mi.info IN ('Drama',
                  'Horror')
  AND mi_idx.info > '8.0'
  AND t.production_year BETWEEN 2005 AND 2008
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND mi.info_type_id = it1.id
  AND mi_idx.info_type_id = it2.id
  AND t.id = mc.movie_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id;

explain analyze SELECT MIN(mi.info) AS budget,
       MIN(t.title) AS unsuccsessful_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     title AS t
WHERE cn.country_code ='[us]'
  AND ct.kind IS NOT NULL
  AND (ct.kind ='production companies'
       OR ct.kind = 'distributors')
  AND it1.info ='budget'
  AND it2.info ='bottom 10 rank'
  AND t.production_year >2000
  AND (t.title LIKE 'Birdemic%'
       OR t.title LIKE '%Movie%')
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND mi.info_type_id = it1.id
  AND mi_idx.info_type_id = it2.id
  AND t.id = mc.movie_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS mainstream_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     title AS t
WHERE cn.country_code = '[us]'
  AND ct.kind = 'production companies'
  AND it1.info = 'genres'
  AND it2.info = 'rating'
  AND mi.info IN ('Drama',
                  'Horror',
                  'Western',
                  'Family')
  AND mi_idx.info > '7.0'
  AND t.production_year BETWEEN 2000 AND 2010
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND mi.info_type_id = it1.id
  AND mi_idx.info_type_id = it2.id
  AND t.id = mc.movie_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id;

explain analyze SELECT MIN(mi.info) AS release_date,
       MIN(miidx.info) AS rating,
       MIN(t.title) AS german_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it,
     info_type AS it2,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS miidx,
     title AS t
WHERE cn.country_code ='[de]'
  AND ct.kind ='production companies'
  AND it.info ='rating'
  AND it2.info ='release dates'
  AND kt.kind ='movie'
  AND mi.movie_id = t.id
  AND it2.id = mi.info_type_id
  AND kt.id = t.kind_id
  AND mc.movie_id = t.id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND miidx.movie_id = t.id
  AND it.id = miidx.info_type_id
  AND mi.movie_id = miidx.movie_id
  AND mi.movie_id = mc.movie_id
  AND miidx.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(miidx.info) AS rating,
       MIN(t.title) AS movie_about_winning
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it,
     info_type AS it2,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS miidx,
     title AS t
WHERE cn.country_code ='[us]'
  AND ct.kind ='production companies'
  AND it.info ='rating'
  AND it2.info ='release dates'
  AND kt.kind ='movie'
  AND t.title != ''
  AND (t.title LIKE '%Champion%'
       OR t.title LIKE '%Loser%')
  AND mi.movie_id = t.id
  AND it2.id = mi.info_type_id
  AND kt.id = t.kind_id
  AND mc.movie_id = t.id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND miidx.movie_id = t.id
  AND it.id = miidx.info_type_id
  AND mi.movie_id = miidx.movie_id
  AND mi.movie_id = mc.movie_id
  AND miidx.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(miidx.info) AS rating,
       MIN(t.title) AS movie_about_winning
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it,
     info_type AS it2,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS miidx,
     title AS t
WHERE cn.country_code ='[us]'
  AND ct.kind ='production companies'
  AND it.info ='rating'
  AND it2.info ='release dates'
  AND kt.kind ='movie'
  AND t.title != ''
  AND (t.title LIKE 'Champion%'
       OR t.title LIKE 'Loser%')
  AND mi.movie_id = t.id
  AND it2.id = mi.info_type_id
  AND kt.id = t.kind_id
  AND mc.movie_id = t.id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND miidx.movie_id = t.id
  AND it.id = miidx.info_type_id
  AND mi.movie_id = miidx.movie_id
  AND mi.movie_id = mc.movie_id
  AND miidx.movie_id = mc.movie_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(miidx.info) AS rating,
       MIN(t.title) AS movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it,
     info_type AS it2,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS miidx,
     title AS t
WHERE cn.country_code ='[us]'
  AND ct.kind ='production companies'
  AND it.info ='rating'
  AND it2.info ='release dates'
  AND kt.kind ='movie'
  AND mi.movie_id = t.id
  AND it2.id = mi.info_type_id
  AND kt.id = t.kind_id
  AND mc.movie_id = t.id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND miidx.movie_id = t.id
  AND it.id = miidx.info_type_id
  AND mi.movie_id = miidx.movie_id
  AND mi.movie_id = mc.movie_id
  AND miidx.movie_id = mc.movie_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS northern_dark_movie
FROM info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind = 'movie'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2010
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_dark_production
FROM info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title')
  AND kt.kind = 'movie'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info > '6.0'
  AND t.production_year > 2010
  AND (t.title LIKE '%murder%'
       OR t.title LIKE '%Murder%'
       OR t.title LIKE '%Mord%')
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS north_european_dark_production
FROM info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IS NOT NULL
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Danish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi.info) AS release_date,
       MIN(t.title) AS internet_movie
FROM aka_title AS at,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND mc.note LIKE '%(200%)%'
  AND mc.note LIKE '%(worldwide)%'
  AND mi.note LIKE '%internet%'
  AND mi.info LIKE 'USA:% 200%'
  AND t.production_year > 2000
  AND t.id = at.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = at.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = at.movie_id
  AND mc.movie_id = at.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(mi.info) AS release_date,
       MIN(t.title) AS youtube_movie
FROM aka_title AS at,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code = '[us]'
  AND cn.name = 'YouTube'
  AND it1.info = 'release dates'
  AND mc.note LIKE '%(200%)%'
  AND mc.note LIKE '%(worldwide)%'
  AND mi.note LIKE '%internet%'
  AND mi.info LIKE 'USA:% 200%'
  AND t.production_year BETWEEN 2005 AND 2010
  AND t.id = at.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = at.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = at.movie_id
  AND mc.movie_id = at.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(mi.info) AS release_date,
       MIN(t.title) AS modern_american_internet_movie
FROM aka_title AS at,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND mi.note LIKE '%internet%'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'USA:% 199%'
       OR mi.info LIKE 'USA:% 200%')
  AND t.production_year > 1990
  AND t.id = at.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = at.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = at.movie_id
  AND mc.movie_id = at.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(at.title) AS aka_title,
       MIN(t.title) AS internet_movie_title
FROM aka_title AS at,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND mi.note LIKE '%internet%'
  AND t.production_year > 1990
  AND t.id = at.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = at.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = at.movie_id
  AND mc.movie_id = at.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

explain analyze SELECT MIN(an.name) AS cool_actor_pseudonym,
       MIN(t.title) AS series_named_after_char
FROM aka_name AS an,
     cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND t.episode_nr >= 50
  AND t.episode_nr < 100
  AND an.person_id = n.id
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND an.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(an.name) AS cool_actor_pseudonym,
       MIN(t.title) AS series_named_after_char
FROM aka_name AS an,
     cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND an.person_id = n.id
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND an.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(an.name) AS cool_actor_pseudonym,
       MIN(t.title) AS series_named_after_char
FROM aka_name AS an,
     cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND t.episode_nr < 100
  AND an.person_id = n.id
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND an.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(an.name) AS cool_actor_pseudonym,
       MIN(t.title) AS series_named_after_char
FROM aka_name AS an,
     cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND t.episode_nr >= 5
  AND t.episode_nr < 100
  AND an.person_id = n.id
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND an.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_american_movie,
       MIN(n.name) AS a1
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND n.name LIKE 'B%'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_movie,
       MIN(n.name) AS a1
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword ='character-name-in-title'
  AND n.name LIKE 'Z%'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_movie,
       MIN(n.name) AS a1
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword ='character-name-in-title'
  AND n.name LIKE 'X%'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_movie
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword ='character-name-in-title'
  AND n.name LIKE '%Bert%'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_movie
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(n.name) AS member_in_charnamed_movie
FROM cast_info AS ci,
     company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword ='character-name-in-title'
  AND n.name LIKE '%B%'
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.movie_id = mc.movie_id
  AND ci.movie_id = mk.movie_id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(t.title) AS movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     name AS n,
     title AS t
WHERE ci.note IN ('(producer)',
                  '(executive producer)')
  AND it1.info = 'budget'
  AND it2.info = 'votes'
  AND n.gender = 'm'
  AND n.name LIKE '%Tim%'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(t.title) AS movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'rating'
  AND mi.info IN ('Horror',
                  'Thriller')
  AND mi.note IS NULL
  AND mi_idx.info > '8.0'
  AND n.gender IS NOT NULL
  AND n.gender = 'f'
  AND t.production_year BETWEEN 2008 AND 2014
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(t.title) AS movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND mi.info IN ('Horror',
                  'Action',
                  'Sci-Fi',
                  'Thriller',
                  'Crime',
                  'War')
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(n.name) AS voicing_actress,
       MIN(t.title) AS voiced_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND mc.note IS NOT NULL
  AND (mc.note LIKE '%(USA)%'
       OR mc.note LIKE '%(worldwide)%')
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%200%'
       OR mi.info LIKE 'USA:%200%')
  AND n.gender ='f'
  AND n.name LIKE '%Ang%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2005 AND 2009
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mi.movie_id = ci.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id;

explain analyze SELECT MIN(n.name) AS voicing_actress,
       MIN(t.title) AS kung_fu_panda
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note = '(voice)'
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND mc.note LIKE '%(200%)%'
  AND (mc.note LIKE '%(USA)%'
       OR mc.note LIKE '%(worldwide)%')
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%2007%'
       OR mi.info LIKE 'USA:%2008%')
  AND n.gender ='f'
  AND n.name LIKE '%Angel%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2007 AND 2008
  AND t.title LIKE '%Kung%Fu%Panda%'
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mi.movie_id = ci.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id;

explain analyze SELECT MIN(n.name) AS voicing_actress,
       MIN(t.title) AS jap_engl_voiced_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%200%'
       OR mi.info LIKE 'USA:%200%')
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.production_year > 2000
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mi.movie_id = ci.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id;

explain analyze SELECT MIN(n.name) AS voicing_actress,
       MIN(t.title) AS jap_engl_voiced_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND n.gender ='f'
  AND rt.role ='actress'
  AND t.production_year > 2000
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mi.movie_id = ci.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id;

explain analyze 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;

explain analyze 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;

explain analyze 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)%')
  AND t.production_year >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;

explain analyze 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 >2000
  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;

explain analyze SELECT MIN(t.title) AS complete_downey_ironman_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     keyword AS k,
     kind_type AS kt,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name NOT LIKE '%Sherlock%'
  AND (chn.name LIKE '%Tony%Stark%'
       OR chn.name LIKE '%Iron%Man%')
  AND k.keyword IN ('superhero',
                    'sequel',
                    'second-part',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence')
  AND kt.kind = 'movie'
  AND t.production_year > 1950
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND ci.movie_id = cc.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(t.title) AS complete_downey_ironman_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     keyword AS k,
     kind_type AS kt,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name NOT LIKE '%Sherlock%'
  AND (chn.name LIKE '%Tony%Stark%'
       OR chn.name LIKE '%Iron%Man%')
  AND k.keyword IN ('superhero',
                    'sequel',
                    'second-part',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence')
  AND kt.kind = 'movie'
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND ci.movie_id = cc.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(n.name) AS cast_member,
       MIN(t.title) AS complete_dynamic_hero_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     keyword AS k,
     kind_type AS kt,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name IS NOT NULL
  AND (chn.name LIKE '%man%'
       OR chn.name LIKE '%Man%')
  AND k.keyword IN ('superhero',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence',
                    'magnet',
                    'web',
                    'claw',
                    'laser')
  AND kt.kind = 'movie'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND ci.movie_id = cc.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(cn.name) AS company_name,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS western_follow_up
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German')
  AND t.production_year BETWEEN 1950 AND 2000
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id;

explain analyze SELECT MIN(cn.name) AS company_name,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS german_follow_up
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Germany',
                  'German')
  AND t.production_year BETWEEN 2000 AND 2010
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id;

explain analyze SELECT MIN(cn.name) AS company_name,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS western_follow_up
FROM company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'English')
  AND t.production_year BETWEEN 1950 AND 2010
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_violent_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Germany',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '7.0'
  AND t.production_year > 2008
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_violent_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Germany',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '7.0'
  AND t.production_year > 2009
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_violent_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Danish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_violent_movie
FROM company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Danish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(kt.kind) AS movie_kind,
       MIN(t.title) AS complete_us_internet_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'complete+verified'
  AND cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND kt.kind IN ('movie')
  AND mi.note LIKE '%internet%'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'USA:% 199%'
       OR mi.info LIKE 'USA:% 200%')
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND cct1.id = cc.status_id;

explain analyze SELECT MIN(kt.kind) AS movie_kind,
       MIN(t.title) AS complete_nerdy_internet_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'complete+verified'
  AND cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND k.keyword IN ('nerd',
                    'loner',
                    'alienation',
                    'dignity')
  AND kt.kind IN ('movie')
  AND mi.note LIKE '%internet%'
  AND mi.info LIKE 'USA:% 200%'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND cct1.id = cc.status_id;

explain analyze SELECT MIN(kt.kind) AS movie_kind,
       MIN(t.title) AS complete_us_internet_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'complete+verified'
  AND cn.country_code = '[us]'
  AND it1.info = 'release dates'
  AND kt.kind IN ('movie',
                  'tv movie',
                  'video movie',
                  'video game')
  AND mi.note LIKE '%internet%'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'USA:% 199%'
       OR mi.info LIKE 'USA:% 200%')
  AND t.production_year > 1990
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id
  AND cct1.id = cc.status_id;

explain analyze SELECT MIN(chn.name) AS voiced_char_name,
       MIN(n.name) AS voicing_actress_name,
       MIN(t.title) AS voiced_action_movie_jap_eng
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND k.keyword IN ('hero',
                    'martial-arts',
                    'hand-to-hand-combat')
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%201%'
       OR mi.info LIKE 'USA:%201%')
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.production_year > 2010
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mk.movie_id
  AND mi.movie_id = ci.movie_id
  AND mi.movie_id = mk.movie_id
  AND ci.movie_id = mk.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(chn.name) AS voiced_char_name,
       MIN(n.name) AS voicing_actress_name,
       MIN(t.title) AS kung_fu_panda
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND cn.name = 'DreamWorks Animation'
  AND it.info = 'release dates'
  AND k.keyword IN ('hero',
                    'martial-arts',
                    'hand-to-hand-combat',
                    'computer-animated-movie')
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%201%'
       OR mi.info LIKE 'USA:%201%')
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.production_year > 2010
  AND t.title LIKE 'Kung Fu Panda%'
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mk.movie_id
  AND mi.movie_id = ci.movie_id
  AND mi.movie_id = mk.movie_id
  AND ci.movie_id = mk.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS male_writer,
       MIN(t.title) AS violent_movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity')
  AND mi.info = 'Horror'
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS male_writer,
       MIN(t.title) AS violent_movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity')
  AND mi.info = 'Horror'
  AND n.gender = 'm'
  AND t.production_year > 2010
  AND t.title LIKE 'Vampire%'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS male_writer,
       MIN(t.title) AS violent_movie_title
FROM cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Action',
                  'Sci-Fi',
                  'Thriller',
                  'Crime',
                  'War')
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(chn.name) AS character_name,
       MIN(mi_idx.info) AS rating,
       MIN(n.name) AS playing_actor,
       MIN(t.title) AS complete_hero_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name IS NOT NULL
  AND (chn.name LIKE '%man%'
       OR chn.name LIKE '%Man%')
  AND it2.info = 'rating'
  AND k.keyword IN ('superhero',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence',
                    'magnet',
                    'web',
                    'claw',
                    'laser')
  AND kt.kind = 'movie'
  AND mi_idx.info > '7.0'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND ci.movie_id = cc.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND cc.movie_id = mi_idx.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(chn.name) AS character_name,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS complete_hero_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name IS NOT NULL
  AND (chn.name LIKE '%man%'
       OR chn.name LIKE '%Man%')
  AND it2.info = 'rating'
  AND k.keyword IN ('superhero',
                    'marvel-comics',
                    'based-on-comic',
                    'fight')
  AND kt.kind = 'movie'
  AND mi_idx.info > '8.0'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND ci.movie_id = cc.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND cc.movie_id = mi_idx.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(chn.name) AS character_name,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS complete_hero_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE '%complete%'
  AND chn.name IS NOT NULL
  AND (chn.name LIKE '%man%'
       OR chn.name LIKE '%Man%')
  AND it2.info = 'rating'
  AND k.keyword IN ('superhero',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence',
                    'magnet',
                    'web',
                    'claw',
                    'laser')
  AND kt.kind = 'movie'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND t.id = cc.movie_id
  AND t.id = mi_idx.movie_id
  AND mk.movie_id = ci.movie_id
  AND mk.movie_id = cc.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND ci.movie_id = cc.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND cc.movie_id = mi_idx.movie_id
  AND chn.id = ci.person_role_id
  AND n.id = ci.person_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND it2.id = mi_idx.info_type_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS complete_western_sequel
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cct1.kind IN ('cast',
                    'crew')
  AND cct2.kind = 'complete'
  AND cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Sweden',
                  'Germany',
                  'Swedish',
                  'German')
  AND t.production_year BETWEEN 1950 AND 2000
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND t.id = cc.movie_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id
  AND ml.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = cc.movie_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS complete_western_sequel
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cct1.kind IN ('cast',
                    'crew')
  AND cct2.kind = 'complete'
  AND cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Sweden',
                  'Germany',
                  'Swedish',
                  'German')
  AND t.production_year = 1998
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND t.id = cc.movie_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id
  AND ml.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = cc.movie_id;

explain analyze SELECT MIN(cn.name) AS producing_company,
       MIN(lt.link) AS link_type,
       MIN(t.title) AS complete_western_sequel
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     keyword AS k,
     link_type AS lt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind LIKE 'complete%'
  AND cn.country_code !='[pl]'
  AND (cn.name LIKE '%Film%'
       OR cn.name LIKE '%Warner%')
  AND ct.kind ='production companies'
  AND k.keyword ='sequel'
  AND lt.link LIKE '%follow%'
  AND mc.note IS NULL
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'English')
  AND t.production_year BETWEEN 1950 AND 2010
  AND lt.id = ml.link_type_id
  AND ml.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND t.id = mc.movie_id
  AND mc.company_type_id = ct.id
  AND mc.company_id = cn.id
  AND mi.movie_id = t.id
  AND t.id = cc.movie_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id
  AND ml.movie_id = mk.movie_id
  AND ml.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND ml.movie_id = mi.movie_id
  AND mk.movie_id = mi.movie_id
  AND mc.movie_id = mi.movie_id
  AND ml.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = cc.movie_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS complete_euro_dark_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'crew'
  AND cct2.kind != 'complete+verified'
  AND cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Danish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2000
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS complete_euro_dark_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'crew'
  AND cct2.kind != 'complete+verified'
  AND cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Sweden',
                  'Germany',
                  'Swedish',
                  'German')
  AND mi_idx.info > '6.5'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS complete_euro_dark_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     company_name AS cn,
     company_type AS ct,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     kind_type AS kt,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind = 'complete'
  AND cn.country_code != '[us]'
  AND it1.info = 'countries'
  AND it2.info = 'rating'
  AND k.keyword IN ('murder',
                    'murder-in-title',
                    'blood',
                    'violence')
  AND kt.kind IN ('movie',
                  'episode')
  AND mc.note NOT LIKE '%(USA)%'
  AND mc.note LIKE '%(200%)%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Danish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND mi_idx.info < '8.5'
  AND t.production_year > 2005
  AND kt.id = t.kind_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = mc.movie_id
  AND t.id = cc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = cc.movie_id
  AND mc.movie_id = mi_idx.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND ct.id = mc.company_type_id
  AND cn.id = mc.company_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(chn.name) AS voiced_char,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS voiced_animation
FROM aka_name AS an,
     complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     info_type AS it3,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     name AS n,
     person_info AS pi,
     role_type AS rt,
     title AS t
WHERE cct1.kind ='cast'
  AND cct2.kind ='complete+verified'
  AND chn.name = 'Queen'
  AND ci.note IN ('(voice)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND it3.info = 'trivia'
  AND k.keyword = 'computer-animation'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%200%'
       OR mi.info LIKE 'USA:%200%')
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.title = 'Shrek 2'
  AND t.production_year BETWEEN 2000 AND 2010
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mk.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = ci.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id
  AND n.id = pi.person_id
  AND ci.person_id = pi.person_id
  AND it3.id = pi.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(chn.name) AS voiced_char,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS voiced_animation
FROM aka_name AS an,
     complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     info_type AS it3,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     name AS n,
     person_info AS pi,
     role_type AS rt,
     title AS t
WHERE cct1.kind ='cast'
  AND cct2.kind ='complete+verified'
  AND chn.name = 'Queen'
  AND ci.note IN ('(voice)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND it3.info = 'height'
  AND k.keyword = 'computer-animation'
  AND mi.info LIKE 'USA:%200%'
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.title = 'Shrek 2'
  AND t.production_year BETWEEN 2000 AND 2005
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mk.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = ci.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id
  AND n.id = pi.person_id
  AND ci.person_id = pi.person_id
  AND it3.id = pi.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(chn.name) AS voiced_char,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS voiced_animation
FROM aka_name AS an,
     complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     info_type AS it,
     info_type AS it3,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_keyword AS mk,
     name AS n,
     person_info AS pi,
     role_type AS rt,
     title AS t
WHERE cct1.kind ='cast'
  AND cct2.kind ='complete+verified'
  AND ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND it.info = 'release dates'
  AND it3.info = 'trivia'
  AND k.keyword = 'computer-animation'
  AND mi.info IS NOT NULL
  AND (mi.info LIKE 'Japan:%200%'
       OR mi.info LIKE 'USA:%200%')
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2000 AND 2010
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND mc.movie_id = ci.movie_id
  AND mc.movie_id = mi.movie_id
  AND mc.movie_id = mk.movie_id
  AND mc.movie_id = cc.movie_id
  AND mi.movie_id = ci.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND cn.id = mc.company_id
  AND it.id = mi.info_type_id
  AND n.id = ci.person_id
  AND rt.id = ci.role_id
  AND n.id = an.person_id
  AND ci.person_id = an.person_id
  AND chn.id = ci.person_role_id
  AND n.id = pi.person_id
  AND ci.person_id = pi.person_id
  AND it3.id = pi.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code ='[de]'
  AND k.keyword ='character-name-in-title'
  AND cn.id = mc.company_id
  AND mc.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code ='[nl]'
  AND k.keyword ='character-name-in-title'
  AND cn.id = mc.company_id
  AND mc.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code ='[sm]'
  AND k.keyword ='character-name-in-title'
  AND cn.id = mc.company_id
  AND mc.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM company_name AS cn,
     keyword AS k,
     movie_companies AS mc,
     movie_keyword AS mk,
     title AS t
WHERE cn.country_code ='[us]'
  AND k.keyword ='character-name-in-title'
  AND cn.id = mc.company_id
  AND mc.movie_id = t.id
  AND t.id = mk.movie_id
  AND mk.keyword_id = k.id
  AND mc.movie_id = mk.movie_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS complete_violent_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind IN ('cast',
                    'crew')
  AND cct2.kind ='complete+verified'
  AND ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Thriller')
  AND n.gender = 'm'
  AND t.production_year > 2000
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS complete_gore_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind IN ('cast',
                    'crew')
  AND cct2.kind ='complete+verified'
  AND ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Thriller')
  AND n.gender = 'm'
  AND t.production_year > 2000
  AND (t.title LIKE '%Freddy%'
       OR t.title LIKE '%Jason%'
       OR t.title LIKE 'Saw%')
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS complete_violent_movie
FROM complete_cast AS cc,
     comp_cast_type AS cct1,
     comp_cast_type AS cct2,
     cast_info AS ci,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE cct1.kind = 'cast'
  AND cct2.kind ='complete+verified'
  AND ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Action',
                  'Sci-Fi',
                  'Thriller',
                  'Crime',
                  'War')
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = cc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = cc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = cc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = cc.movie_id
  AND mk.movie_id = cc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cct1.id = cc.subject_id
  AND cct2.id = cc.status_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS violent_liongate_movie
FROM cast_info AS ci,
     company_name AS cn,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND cn.name LIKE 'Lionsgate%'
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Thriller')
  AND n.gender = 'm'
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS violent_liongate_movie
FROM cast_info AS ci,
     company_name AS cn,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND cn.name LIKE 'Lionsgate%'
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mc.note LIKE '%(Blu-ray)%'
  AND mi.info IN ('Horror',
                  'Thriller')
  AND n.gender = 'm'
  AND t.production_year > 2000
  AND (t.title LIKE '%Freddy%'
       OR t.title LIKE '%Jason%'
       OR t.title LIKE 'Saw%')
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(mi.info) AS movie_budget,
       MIN(mi_idx.info) AS movie_votes,
       MIN(n.name) AS writer,
       MIN(t.title) AS violent_liongate_movie
FROM cast_info AS ci,
     company_name AS cn,
     info_type AS it1,
     info_type AS it2,
     keyword AS k,
     movie_companies AS mc,
     movie_info AS mi,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE ci.note IN ('(writer)',
                  '(head writer)',
                  '(written by)',
                  '(story)',
                  '(story editor)')
  AND cn.name LIKE 'Lionsgate%'
  AND it1.info = 'genres'
  AND it2.info = 'votes'
  AND k.keyword IN ('murder',
                    'violence',
                    'blood',
                    'gore',
                    'death',
                    'female-nudity',
                    'hospital')
  AND mi.info IN ('Horror',
                  'Action',
                  'Sci-Fi',
                  'Thriller',
                  'Crime',
                  'War')
  AND t.id = mi.movie_id
  AND t.id = mi_idx.movie_id
  AND t.id = ci.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND ci.movie_id = mi.movie_id
  AND ci.movie_id = mi_idx.movie_id
  AND ci.movie_id = mk.movie_id
  AND ci.movie_id = mc.movie_id
  AND mi.movie_id = mi_idx.movie_id
  AND mi.movie_id = mk.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi_idx.movie_id = mk.movie_id
  AND mi_idx.movie_id = mc.movie_id
  AND mk.movie_id = mc.movie_id
  AND n.id = ci.person_id
  AND it1.id = mi.info_type_id
  AND it2.id = mi_idx.info_type_id
  AND k.id = mk.keyword_id
  AND cn.id = mc.company_id;

explain analyze SELECT MIN(lt.link) AS link_type,
       MIN(t1.title) AS first_movie,
       MIN(t2.title) AS second_movie
FROM keyword AS k,
     link_type AS lt,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t1,
     title AS t2
WHERE k.keyword ='10,000-mile-club'
  AND mk.keyword_id = k.id
  AND t1.id = mk.movie_id
  AND ml.movie_id = t1.id
  AND ml.linked_movie_id = t2.id
  AND lt.id = ml.link_type_id
  AND mk.movie_id = t1.id;

explain analyze SELECT MIN(lt.link) AS link_type,
       MIN(t1.title) AS first_movie,
       MIN(t2.title) AS second_movie
FROM keyword AS k,
     link_type AS lt,
     movie_keyword AS mk,
     movie_link AS ml,
     title AS t1,
     title AS t2
WHERE k.keyword ='character-name-in-title'
  AND mk.keyword_id = k.id
  AND t1.id = mk.movie_id
  AND ml.movie_id = t1.id
  AND ml.linked_movie_id = t2.id
  AND lt.id = ml.link_type_id
  AND mk.movie_id = t1.id;

explain analyze SELECT MIN(cn1.name) AS first_company,
       MIN(cn2.name) AS second_company,
       MIN(mi_idx1.info) AS first_rating,
       MIN(mi_idx2.info) AS second_rating,
       MIN(t1.title) AS first_movie,
       MIN(t2.title) AS second_movie
FROM company_name AS cn1,
     company_name AS cn2,
     info_type AS it1,
     info_type AS it2,
     kind_type AS kt1,
     kind_type AS kt2,
     link_type AS lt,
     movie_companies AS mc1,
     movie_companies AS mc2,
     movie_info_idx AS mi_idx1,
     movie_info_idx AS mi_idx2,
     movie_link AS ml,
     title AS t1,
     title AS t2
WHERE cn1.country_code = '[us]'
  AND it1.info = 'rating'
  AND it2.info = 'rating'
  AND kt1.kind IN ('tv series')
  AND kt2.kind IN ('tv series')
  AND lt.link IN ('sequel',
                  'follows',
                  'followed by')
  AND mi_idx2.info < '3.0'
  AND t2.production_year BETWEEN 2005 AND 2008
  AND lt.id = ml.link_type_id
  AND t1.id = ml.movie_id
  AND t2.id = ml.linked_movie_id
  AND it1.id = mi_idx1.info_type_id
  AND t1.id = mi_idx1.movie_id
  AND kt1.id = t1.kind_id
  AND cn1.id = mc1.company_id
  AND t1.id = mc1.movie_id
  AND ml.movie_id = mi_idx1.movie_id
  AND ml.movie_id = mc1.movie_id
  AND mi_idx1.movie_id = mc1.movie_id
  AND it2.id = mi_idx2.info_type_id
  AND t2.id = mi_idx2.movie_id
  AND kt2.id = t2.kind_id
  AND cn2.id = mc2.company_id
  AND t2.id = mc2.movie_id
  AND ml.linked_movie_id = mi_idx2.movie_id
  AND ml.linked_movie_id = mc2.movie_id
  AND mi_idx2.movie_id = mc2.movie_id;

explain analyze SELECT MIN(cn1.name) AS first_company,
       MIN(cn2.name) AS second_company,
       MIN(mi_idx1.info) AS first_rating,
       MIN(mi_idx2.info) AS second_rating,
       MIN(t1.title) AS first_movie,
       MIN(t2.title) AS second_movie
FROM company_name AS cn1,
     company_name AS cn2,
     info_type AS it1,
     info_type AS it2,
     kind_type AS kt1,
     kind_type AS kt2,
     link_type AS lt,
     movie_companies AS mc1,
     movie_companies AS mc2,
     movie_info_idx AS mi_idx1,
     movie_info_idx AS mi_idx2,
     movie_link AS ml,
     title AS t1,
     title AS t2
WHERE cn1.country_code = '[nl]'
  AND it1.info = 'rating'
  AND it2.info = 'rating'
  AND kt1.kind IN ('tv series')
  AND kt2.kind IN ('tv series')
  AND lt.link LIKE '%follow%'
  AND mi_idx2.info < '3.0'
  AND t2.production_year = 2007
  AND lt.id = ml.link_type_id
  AND t1.id = ml.movie_id
  AND t2.id = ml.linked_movie_id
  AND it1.id = mi_idx1.info_type_id
  AND t1.id = mi_idx1.movie_id
  AND kt1.id = t1.kind_id
  AND cn1.id = mc1.company_id
  AND t1.id = mc1.movie_id
  AND ml.movie_id = mi_idx1.movie_id
  AND ml.movie_id = mc1.movie_id
  AND mi_idx1.movie_id = mc1.movie_id
  AND it2.id = mi_idx2.info_type_id
  AND t2.id = mi_idx2.movie_id
  AND kt2.id = t2.kind_id
  AND cn2.id = mc2.company_id
  AND t2.id = mc2.movie_id
  AND ml.linked_movie_id = mi_idx2.movie_id
  AND ml.linked_movie_id = mc2.movie_id
  AND mi_idx2.movie_id = mc2.movie_id;

explain analyze SELECT MIN(cn1.name) AS first_company,
       MIN(cn2.name) AS second_company,
       MIN(mi_idx1.info) AS first_rating,
       MIN(mi_idx2.info) AS second_rating,
       MIN(t1.title) AS first_movie,
       MIN(t2.title) AS second_movie
FROM company_name AS cn1,
     company_name AS cn2,
     info_type AS it1,
     info_type AS it2,
     kind_type AS kt1,
     kind_type AS kt2,
     link_type AS lt,
     movie_companies AS mc1,
     movie_companies AS mc2,
     movie_info_idx AS mi_idx1,
     movie_info_idx AS mi_idx2,
     movie_link AS ml,
     title AS t1,
     title AS t2
WHERE cn1.country_code != '[us]'
  AND it1.info = 'rating'
  AND it2.info = 'rating'
  AND kt1.kind IN ('tv series',
                   'episode')
  AND kt2.kind IN ('tv series',
                   'episode')
  AND lt.link IN ('sequel',
                  'follows',
                  'followed by')
  AND mi_idx2.info < '3.5'
  AND t2.production_year BETWEEN 2000 AND 2010
  AND lt.id = ml.link_type_id
  AND t1.id = ml.movie_id
  AND t2.id = ml.linked_movie_id
  AND it1.id = mi_idx1.info_type_id
  AND t1.id = mi_idx1.movie_id
  AND kt1.id = t1.kind_id
  AND cn1.id = mc1.company_id
  AND t1.id = mc1.movie_id
  AND ml.movie_id = mi_idx1.movie_id
  AND ml.movie_id = mc1.movie_id
  AND mi_idx1.movie_id = mc1.movie_id
  AND it2.id = mi_idx2.info_type_id
  AND t2.id = mi_idx2.movie_id
  AND kt2.id = t2.kind_id
  AND cn2.id = mc2.company_id
  AND t2.id = mc2.movie_id
  AND ml.linked_movie_id = mi_idx2.movie_id
  AND ml.linked_movie_id = mc2.movie_id
  AND mi_idx2.movie_id = mc2.movie_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM keyword AS k,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE k.keyword LIKE '%sequel%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German')
  AND t.production_year > 2005
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi.movie_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM keyword AS k,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE k.keyword LIKE '%sequel%'
  AND mi.info IN ('Bulgaria')
  AND t.production_year > 2010
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi.movie_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(t.title) AS movie_title
FROM keyword AS k,
     movie_info AS mi,
     movie_keyword AS mk,
     title AS t
WHERE k.keyword LIKE '%sequel%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND t.production_year > 1990
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi.movie_id
  AND k.id = mk.keyword_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS movie_title
FROM info_type AS it,
     keyword AS k,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it.info ='rating'
  AND k.keyword LIKE '%sequel%'
  AND mi_idx.info > '5.0'
  AND t.production_year > 2005
  AND t.id = mi_idx.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS movie_title
FROM info_type AS it,
     keyword AS k,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it.info ='rating'
  AND k.keyword LIKE '%sequel%'
  AND mi_idx.info > '9.0'
  AND t.production_year > 2010
  AND t.id = mi_idx.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it.id = mi_idx.info_type_id;

explain analyze SELECT MIN(mi_idx.info) AS rating,
       MIN(t.title) AS movie_title
FROM info_type AS it,
     keyword AS k,
     movie_info_idx AS mi_idx,
     movie_keyword AS mk,
     title AS t
WHERE it.info ='rating'
  AND k.keyword LIKE '%sequel%'
  AND mi_idx.info > '2.0'
  AND t.production_year > 1990
  AND t.id = mi_idx.movie_id
  AND t.id = mk.movie_id
  AND mk.movie_id = mi_idx.movie_id
  AND k.id = mk.keyword_id
  AND it.id = mi_idx.info_type_id;

explain analyze SELECT MIN(t.title) AS typical_european_movie
FROM company_type AS ct,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     title AS t
WHERE ct.kind = 'production companies'
  AND mc.note LIKE '%(theatrical)%'
  AND mc.note LIKE '%(France)%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German')
  AND t.production_year > 2005
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND mc.movie_id = mi.movie_id
  AND ct.id = mc.company_type_id
  AND it.id = mi.info_type_id;

explain analyze SELECT MIN(t.title) AS american_vhs_movie
FROM company_type AS ct,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     title AS t
WHERE ct.kind = 'production companies'
  AND mc.note LIKE '%(VHS)%'
  AND mc.note LIKE '%(USA)%'
  AND mc.note LIKE '%(1994)%'
  AND mi.info IN ('USA',
                  'America')
  AND t.production_year > 2010
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND mc.movie_id = mi.movie_id
  AND ct.id = mc.company_type_id
  AND it.id = mi.info_type_id;

explain analyze SELECT MIN(t.title) AS american_movie
FROM company_type AS ct,
     info_type AS it,
     movie_companies AS mc,
     movie_info AS mi,
     title AS t
WHERE ct.kind = 'production companies'
  AND mc.note NOT LIKE '%(TV)%'
  AND mc.note LIKE '%(USA)%'
  AND mi.info IN ('Sweden',
                  'Norway',
                  'Germany',
                  'Denmark',
                  'Swedish',
                  'Denish',
                  'Norwegian',
                  'German',
                  'USA',
                  'American')
  AND t.production_year > 1990
  AND t.id = mi.movie_id
  AND t.id = mc.movie_id
  AND mc.movie_id = mi.movie_id
  AND ct.id = mc.company_type_id
  AND it.id = mi.info_type_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS marvel_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword = 'marvel-cinematic-universe'
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2010
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS hero_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword IN ('superhero',
                    'sequel',
                    'second-part',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence')
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2014
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS marvel_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword = 'marvel-cinematic-universe'
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2014
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS hero_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword IN ('superhero',
                    'sequel',
                    'second-part',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence')
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2000
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS marvel_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword = 'marvel-cinematic-universe'
  AND n.name LIKE '%Downey%Robert%'
  AND t.production_year > 2000
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(k.keyword) AS movie_keyword,
       MIN(n.name) AS actor_name,
       MIN(t.title) AS hero_movie
FROM cast_info AS ci,
     keyword AS k,
     movie_keyword AS mk,
     name AS n,
     title AS t
WHERE k.keyword IN ('superhero',
                    'sequel',
                    'second-part',
                    'marvel-comics',
                    'based-on-comic',
                    'tv-special',
                    'fight',
                    'violence')
  AND t.production_year > 2000
  AND k.id = mk.keyword_id
  AND t.id = mk.movie_id
  AND t.id = ci.movie_id
  AND ci.movie_id = mk.movie_id
  AND n.id = ci.person_id;

explain analyze SELECT MIN(n.name) AS of_person,
       MIN(t.title) AS biography_movie
FROM aka_name AS an,
     cast_info AS ci,
     info_type AS it,
     link_type AS lt,
     movie_link AS ml,
     name AS n,
     person_info AS pi,
     title AS t
WHERE an.name LIKE '%a%'
  AND it.info ='mini biography'
  AND lt.link ='features'
  AND n.name_pcode_cf BETWEEN 'A' AND 'F'
  AND (n.gender='m'
       OR (n.gender = 'f'
           AND n.name LIKE 'B%'))
  AND pi.note ='Volker Boehm'
  AND t.production_year BETWEEN 1980 AND 1995
  AND n.id = an.person_id
  AND n.id = pi.person_id
  AND ci.person_id = n.id
  AND t.id = ci.movie_id
  AND ml.linked_movie_id = t.id
  AND lt.id = ml.link_type_id
  AND it.id = pi.info_type_id
  AND pi.person_id = an.person_id
  AND pi.person_id = ci.person_id
  AND an.person_id = ci.person_id
  AND ci.movie_id = ml.linked_movie_id;

explain analyze SELECT MIN(n.name) AS of_person,
       MIN(t.title) AS biography_movie
FROM aka_name AS an,
     cast_info AS ci,
     info_type AS it,
     link_type AS lt,
     movie_link AS ml,
     name AS n,
     person_info AS pi,
     title AS t
WHERE an.name LIKE '%a%'
  AND it.info ='mini biography'
  AND lt.link ='features'
  AND n.name_pcode_cf LIKE 'D%'
  AND n.gender='m'
  AND pi.note ='Volker Boehm'
  AND t.production_year BETWEEN 1980 AND 1984
  AND n.id = an.person_id
  AND n.id = pi.person_id
  AND ci.person_id = n.id
  AND t.id = ci.movie_id
  AND ml.linked_movie_id = t.id
  AND lt.id = ml.link_type_id
  AND it.id = pi.info_type_id
  AND pi.person_id = an.person_id
  AND pi.person_id = ci.person_id
  AND an.person_id = ci.person_id
  AND ci.movie_id = ml.linked_movie_id;

explain analyze SELECT MIN(n.name) AS cast_member_name,
       MIN(pi.info) AS cast_member_info
FROM aka_name AS an,
     cast_info AS ci,
     info_type AS it,
     link_type AS lt,
     movie_link AS ml,
     name AS n,
     person_info AS pi,
     title AS t
WHERE an.name IS NOT NULL
  AND (an.name LIKE '%a%'
       OR an.name LIKE 'A%')
  AND it.info ='mini biography'
  AND lt.link IN ('references',
                  'referenced in',
                  'features',
                  'featured in')
  AND n.name_pcode_cf BETWEEN 'A' AND 'F'
  AND (n.gender='m'
       OR (n.gender = 'f'
           AND n.name LIKE 'A%'))
  AND pi.note IS NOT NULL
  AND t.production_year BETWEEN 1980 AND 2010
  AND n.id = an.person_id
  AND n.id = pi.person_id
  AND ci.person_id = n.id
  AND t.id = ci.movie_id
  AND ml.linked_movie_id = t.id
  AND lt.id = ml.link_type_id
  AND it.id = pi.info_type_id
  AND pi.person_id = an.person_id
  AND pi.person_id = ci.person_id
  AND an.person_id = ci.person_id
  AND ci.movie_id = ml.linked_movie_id;

explain analyze SELECT MIN(an1.name) AS actress_pseudonym,
       MIN(t.title) AS japanese_movie_dubbed
FROM aka_name AS an1,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n1,
     role_type AS rt,
     title AS t
WHERE ci.note ='(voice: English version)'
  AND cn.country_code ='[jp]'
  AND mc.note LIKE '%(Japan)%'
  AND mc.note NOT LIKE '%(USA)%'
  AND n1.name LIKE '%Yo%'
  AND n1.name NOT LIKE '%Yu%'
  AND rt.role ='actress'
  AND an1.person_id = n1.id
  AND n1.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND an1.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id;

explain analyze SELECT MIN(an.name) AS acress_pseudonym,
       MIN(t.title) AS japanese_anime_movie
FROM aka_name AS an,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note ='(voice: English version)'
  AND cn.country_code ='[jp]'
  AND mc.note LIKE '%(Japan)%'
  AND mc.note NOT LIKE '%(USA)%'
  AND (mc.note LIKE '%(2006)%'
       OR mc.note LIKE '%(2007)%')
  AND n.name LIKE '%Yo%'
  AND n.name NOT LIKE '%Yu%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2006 AND 2007
  AND (t.title LIKE 'One Piece%'
       OR t.title LIKE 'Dragon Ball Z%')
  AND an.person_id = n.id
  AND n.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND an.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id;

explain analyze SELECT MIN(a1.name) AS writer_pseudo_name,
       MIN(t.title) AS movie_title
FROM aka_name AS a1,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n1,
     role_type AS rt,
     title AS t
WHERE cn.country_code ='[us]'
  AND rt.role ='writer'
  AND a1.person_id = n1.id
  AND n1.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND a1.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id;

explain analyze SELECT MIN(an1.name) AS costume_designer_pseudo,
       MIN(t.title) AS movie_with_costumes
FROM aka_name AS an1,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n1,
     role_type AS rt,
     title AS t
WHERE cn.country_code ='[us]'
  AND rt.role ='costume designer'
  AND an1.person_id = n1.id
  AND n1.id = ci.person_id
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND an1.person_id = ci.person_id
  AND ci.movie_id = mc.movie_id;

explain analyze SELECT MIN(an.name) AS alternative_name,
       MIN(chn.name) AS character_name,
       MIN(t.title) AS movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND mc.note IS NOT NULL
  AND (mc.note LIKE '%(USA)%'
       OR mc.note LIKE '%(worldwide)%')
  AND n.gender ='f'
  AND n.name LIKE '%Ang%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2005 AND 2015
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND ci.movie_id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND n.id = ci.person_id
  AND chn.id = ci.person_role_id
  AND an.person_id = n.id
  AND an.person_id = ci.person_id;

explain analyze SELECT MIN(an.name) AS alternative_name,
       MIN(chn.name) AS voiced_character,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS american_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note = '(voice)'
  AND cn.country_code ='[us]'
  AND mc.note LIKE '%(200%)%'
  AND (mc.note LIKE '%(USA)%'
       OR mc.note LIKE '%(worldwide)%')
  AND n.gender ='f'
  AND n.name LIKE '%Angel%'
  AND rt.role ='actress'
  AND t.production_year BETWEEN 2007 AND 2010
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND ci.movie_id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND n.id = ci.person_id
  AND chn.id = ci.person_role_id
  AND an.person_id = n.id
  AND an.person_id = ci.person_id;

explain analyze SELECT MIN(an.name) AS alternative_name,
       MIN(chn.name) AS voiced_character_name,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS american_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND n.gender ='f'
  AND n.name LIKE '%An%'
  AND rt.role ='actress'
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND ci.movie_id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND n.id = ci.person_id
  AND chn.id = ci.person_role_id
  AND an.person_id = n.id
  AND an.person_id = ci.person_id;

explain analyze SELECT MIN(an.name) AS alternative_name,
       MIN(chn.name) AS voiced_char_name,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS american_movie
FROM aka_name AS an,
     char_name AS chn,
     cast_info AS ci,
     company_name AS cn,
     movie_companies AS mc,
     name AS n,
     role_type AS rt,
     title AS t
WHERE ci.note IN ('(voice)',
                  '(voice: Japanese version)',
                  '(voice) (uncredited)',
                  '(voice: English version)')
  AND cn.country_code ='[us]'
  AND n.gender ='f'
  AND rt.role ='actress'
  AND ci.movie_id = t.id
  AND t.id = mc.movie_id
  AND ci.movie_id = mc.movie_id
  AND mc.company_id = cn.id
  AND ci.role_id = rt.id
  AND n.id = ci.person_id
  AND chn.id = ci.person_role_id
  AND an.person_id = n.id
  AND an.person_id = ci.person_id;