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Add IMDB(JOB) Benchmark [2/N] (imdb queries) (#12529)
* imdb dataset * cargo fmt * Add 113 queries for IMDB(JOB) Signed-off-by: Austin Liu <[email protected]> * Add `get_query_sql` from `query_id` string Signed-off-by: Austin Liu <[email protected]> * Fix CSV reader & Remove Parquet partition Signed-off-by: Austin Liu <[email protected]> * Add benchmark IMDB runner Signed-off-by: Austin Liu <[email protected]> * Add `run_imdb` script Signed-off-by: Austin Liu <[email protected]> * Add checker for imdb option Signed-off-by: Austin Liu <[email protected]> * Add SLT for IMDB Signed-off-by: Austin Liu <[email protected]> * Fix `get_query_sql()` for CI roundtrip test Signed-off-by: Austin Liu <[email protected]> Fix `get_query_sql()` for CI roundtrip test Signed-off-by: Austin Liu <[email protected]> Fix `get_query_sql()` for CI roundtrip test Signed-off-by: Austin Liu <[email protected]> * Clean up Signed-off-by: Austin Liu <[email protected]> * Add missing license Signed-off-by: Austin Liu <[email protected]> * Add IMDB(JOB) queries `2b` to `5c` Signed-off-by: Austin Liu <[email protected]> * Add `INCLUDE_IMDB` in CI verify-benchmark-results Signed-off-by: Austin Liu <[email protected]> * Prepare IMDB dataset Signed-off-by: Austin Liu <[email protected]> Prepare IMDB dataset Signed-off-by: Austin Liu <[email protected]> * use uint as id type * format * Seperate `tpch` and `imdb` benchmarking CI jobs Signed-off-by: Austin Liu <[email protected]> Fix path Signed-off-by: Austin Liu <[email protected]> Fix path Signed-off-by: Austin Liu <[email protected]> Remove `tpch` in `imdb` benchmark Signed-off-by: Austin Liu <[email protected]> * Remove IMDB(JOB) slt in CI Signed-off-by: Austin Liu <[email protected]> Remove IMDB(JOB) slt in CI Signed-off-by: Austin Liu <[email protected]> --------- Signed-off-by: Austin Liu <[email protected]> Co-authored-by: DouPache <[email protected]>
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‎benchmarks/bench.sh

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run_clickbench_1
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run_clickbench_partitioned
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run_clickbench_extended
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run_imdb
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;;
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tpch)
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run_tpch "1"
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clickbench_extended)
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run_clickbench_extended
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;;
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imdb)
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run_imdb
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;;
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*)
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echo "Error: unknown benchmark '$BENCHMARK' for run"
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usage
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fi
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}
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# Runs the imdb benchmark
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run_imdb() {
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IMDB_DIR="${DATA_DIR}/imdb"
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RESULTS_FILE="${RESULTS_DIR}/imdb.json"
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echo "RESULTS_FILE: ${RESULTS_FILE}"
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echo "Running imdb benchmark..."
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$CARGO_COMMAND --bin imdb -- benchmark datafusion --iterations 5 --path "${IMDB_DIR}" --prefer_hash_join "${PREFER_HASH_JOIN}" --format parquet -o "${RESULTS_FILE}"
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}
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‎benchmarks/queries/imdb/10a.sql

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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;

‎benchmarks/queries/imdb/10b.sql

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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;

‎benchmarks/queries/imdb/10c.sql

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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;

‎benchmarks/queries/imdb/11a.sql

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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;

‎benchmarks/queries/imdb/11b.sql

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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;

‎benchmarks/queries/imdb/11c.sql

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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;

‎benchmarks/queries/imdb/11d.sql

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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;

‎benchmarks/queries/imdb/12a.sql

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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;

‎benchmarks/queries/imdb/12b.sql

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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;

‎benchmarks/queries/imdb/12c.sql

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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;

‎benchmarks/queries/imdb/13a.sql

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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;

‎benchmarks/queries/imdb/13b.sql

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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;

‎benchmarks/queries/imdb/13c.sql

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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;

‎benchmarks/queries/imdb/13d.sql

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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;

‎benchmarks/queries/imdb/14a.sql

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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;

‎benchmarks/queries/imdb/14b.sql

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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;

‎benchmarks/queries/imdb/14c.sql

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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;

‎benchmarks/queries/imdb/15a.sql

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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;

‎benchmarks/queries/imdb/15b.sql

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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;

‎benchmarks/queries/imdb/15c.sql

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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;

‎benchmarks/queries/imdb/15d.sql

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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;

‎benchmarks/queries/imdb/16a.sql

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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;

‎benchmarks/queries/imdb/16b.sql

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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;

‎benchmarks/queries/imdb/16c.sql

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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;

‎benchmarks/queries/imdb/16d.sql

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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;

‎benchmarks/queries/imdb/17a.sql

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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;

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