Planner — IMDB — JOB-22B

SELECT MIN(cn.name) AS movie_company,
       MIN(mi_idx.info) AS rating,
       MIN(t.title) AS western_violent_movie
FROM job.company_name AS cn,
     job.company_type AS ct,
     job.info_type AS it1,
     job.info_type AS it2,
     job.keyword AS k,
     job.kind_type AS kt,
     job.movie_companies AS mc,
     job.movie_info AS mi,
     job.movie_info_idx AS mi_idx,
     job.movie_keyword AS mk,
     job.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;

Engine Compare

Accuracy chart, rows processed ?
Scan Scan	Seek Seek	Join Probe Join	Sort Sort	Hash Build Hash	Aggregate Agg	Distribute Dist
Estimation Error Est Err 4,528,890 4.5M Rank		Estimation Error Est Err 4,537,699 4.5M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 87,390 87K Rank	Estimation Error Est Err 31 31 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 21,714,506 22M Rank		Estimation Error Est Err 33,287,083 33M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 15,336,957 15M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 6,837,084 6.8M Rank		Estimation Error Est Err 6,172,102 6.2M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 750,972 751K Rank	Estimation Error Est Err 32 32 Rank	Estimation Error Est Err 710,113 710K Rank
Estimation Error Est Err 12,766,635 13M Rank		Estimation Error Est Err 11,881,633 12M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 5,398,858 5.4M Rank	Estimation Error Est Err 41 41 Rank	Estimation Error Est Err 726,482 726K Rank
Estimation Error Est Err 379,778 380K Rank		Estimation Error Est Err 418,781 419K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 716,613 717K Rank	Estimation Error Est Err 31 31 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 78,083 78K Rank	Estimation Error Est Err 78,080 78K Rank	Estimation Error Est Err 81,656 82K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 82,179 82K Rank	Estimation Error Est Err 31 31 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 868,725 869K Rank	Estimation Error Est Err 868,721 869K Rank	Estimation Error Est Err 971,213 971K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 905,812 906K Rank	Estimation Error Est Err 31 31 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 1,029,802 1M Rank		Estimation Error Est Err 933,428 933K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,255,570 1.3M Rank	Estimation Error Est Err 47 47 Rank	Estimation Error Est Err 903,588 904K Rank

Actual Query Plans

Query Plan per Engine ?
	Query Plan
	Estimate Actual Operator 1 1 AGGREGATE min, min, min 2 31 INNER JOIN HASH ON id = company_type_id 4 4 │└TABLE SCAN company_type 1 31 INNER JOIN HASH ON id72 = company_id 1 39 │└INNER JOIN HASH ON movie_id65 = movie_id57 2 991 │ │└INNER JOIN HASH ON id6 = info_type_id58 1 1 │ │ │└TABLE SCAN info_type WHERE info = rating 1 991 │ │ INNER JOIN HASH ON id33 = movie_id57 3 2061 │ │ │└INNER JOIN HASH ON id11 = info_type_id 1 1 │ │ │ │└TABLE SCAN info_type WHERE info = countries 2 2175 │ │ │ INNER JOIN HASH ON id33 = movie_id49 9 3517 │ │ │ │└INNER JOIN HASH ON id16 = kind_id 2 2 │ │ │ │ │└TABLE SCAN kind_type WHERE kind17 IN(episode,movie) 27 3668 │ │ │ │ INNER JOIN HASH ON id33 = movie_id 129 37091 │ │ │ │ │└INNER JOIN HASH ON id21 = keyword_id 4 3 │ │ │ │ │ │└TABLE SCAN keyword WHERE keyword IN(blood,murder,murder - in - title,violence) 4523930 4523930 │ │ │ │ │ TABLE SCAN movie_keyword 506156 2711 │ │ │ │ TABLE SCAN title WHERE production_year >= 2010 565032 1570 │ │ │ TABLE SCAN movie_info WHERE info51 IN(American,German,Germany,USA) 1180576 634 │ │ TABLE SCAN movie_info_idx WHERE info < 7.0 248981 21 │ TABLE SCAN movie_companies WHERE note68 LIKE '%(200%)%' AND NOT (note68 LIKE '%(USA)%') 120711 13 TABLE SCAN company_name WHERE country_code <> us
	Estimate Actual Operator - 1 PROJECT a1 AS movie_company, a2 AS rating, a3 AS western_violent_movie - 1 AGGREGATE MIN(name) AS a1, MIN(info) AS a2, MIN(title) AS a3 - 0 PROJECT name, info, title - 0 PROJECT name, info, title - 0 INNER JOIN HASH ON tuple(PROJECTION_2374.movie_id,PROJECTION_2374.movie_id,PROJECTION_2374.movie_id,PROJECTION_2374.movie_id,PROJECTION_2374.movie_id,PROJECTION_2374.movie_id) = tuple(PROJECTION_2353.movie_id,PROJECTION_2353.movie_id,PROJECTION_2353.movie_id,PROJECTION_2353.id,PROJECTION_2353.id,PROJECTION_2353.id) - 233592 │└PROJECT movie_id AS movie_id_right, id, title - 233592 │ PROJECT movie_id, title, id - 233592 │ INNER JOIN HASH ON PROJECTION_2359.kind_id = PROJECTION_2356.id - 7 │ │└PROJECT id AS id_right - 7 │ │ PROJECT id - 7 │ │ TABLE SCAN kind_type WHERE TRUE - 233592 │ PROJECT kind_id, movie_id, title, id AS id_left - 233592 │ PROJECT movie_id, title, id, kind_id - 233592 │ INNER JOIN HASH ON PROJECTION_2365.movie_id = PROJECTION_2362.id - 533369 │ │└PROJECT id, title, kind_id - 533369 │ │ PROJECT id, title, kind_id - 533369 │ │ TABLE SCAN title WHERE production_year > 2009 - 1325361 │ PROJECT movie_id - 1325361 │ PROJECT movie_id - 1325361 │ INNER JOIN HASH ON PROJECTION_2371.info_type_id = PROJECTION_2368.id - 1 │ │└PROJECT id - 1 │ │ PROJECT id - 1 │ │ TABLE SCAN info_type WHERE info = 'countries' - 14835720 │ PROJECT info_type_id, movie_id - 14835720 │ PROJECT movie_id, info_type_id - 14835720 │ TABLE SCAN movie_info WHERE TRUE - 5183566 PROJECT movie_id AS movie_id_left, movie_id AS movie_id_left_2, movie_id AS movie_id_left_3, name, info - 5183566 PROJECT name, movie_id, info, movie_id, movie_id - 5183566 INNER JOIN HASH ON tuple(PROJECTION_2392.movie_id,PROJECTION_2392.movie_id) = tuple(PROJECTION_2377.movie_id,PROJECTION_2377.movie_id) - 299742 │└PROJECT movie_id AS movie_id_right, name - 299742 │ PROJECT name, movie_id - 299742 │ INNER JOIN HASH ON PROJECTION_2383.company_type_id = PROJECTION_2380.id - 4 │ │└PROJECT id - 4 │ │ PROJECT id - 4 │ │ TABLE SCAN company_type - 299742 │ PROJECT company_type_id, name, movie_id - 299742 │ PROJECT name, company_type_id, movie_id - 299742 │ INNER JOIN HASH ON PROJECTION_2389.id = PROJECTION_2386.company_id - 303271 │ │└PROJECT company_id, company_type_id, movie_id - 303271 │ │ PROJECT company_id, company_type_id, movie_id - 303271 │ │ TABLE SCAN movie_companies WHERE notLike(note,'%(USA)%') AND note LIKE '%(200%)%' - 211073 │ PROJECT id, name - 211073 │ PROJECT id, name - 211073 │ TABLE SCAN company_name WHERE country_code <> 'us' - 2376417 PROJECT movie_id_left, movie_id AS movie_id_left_2, info - 2376417 PROJECT info, movie_id, movie_id - 2376417 INNER JOIN HASH ON PROJECTION_2398.keyword_id = PROJECTION_2395.id - 134170 │└PROJECT id - 134170 │ PROJECT id - 134170 │ TABLE SCAN keyword WHERE TRUE - 2376417 PROJECT keyword_id, info, movie_id, movie_id - 2376417 PROJECT info, movie_id, movie_id, keyword_id - 2376417 INNER JOIN HASH ON PROJECTION_2404.movie_id = PROJECTION_2401.movie_id - 4523930 │└PROJECT movie_id AS movie_id_right, keyword_id - 4523930 │ PROJECT movie_id, keyword_id - 4523930 │ TABLE SCAN movie_keyword - 324117 PROJECT movie_id AS movie_id_left, info - 324117 PROJECT info, movie_id - 324117 INNER JOIN HASH ON PROJECTION_2410.info_type_id = PROJECTION_2407.id - 1 │└PROJECT id - 1 │ PROJECT id - 1 │ TABLE SCAN info_type WHERE info = 'rating' - 1172960 PROJECT info_type_id, info, movie_id - 1172960 PROJECT movie_id, info, info_type_id - 1172960 TABLE SCAN movie_info_idx WHERE info < '7.0'
	Estimate Actual Operator - 1 AGGREGATE MIN(#0), MIN(#1), MIN(#2) 0 31 PROJECT name, info, title 0 31 INNER JOIN HASH ON id = company_type_id 0 31 │└INNER JOIN HASH ON id = keyword_id 0 2606 │ │└INNER JOIN HASH ON movie_id = movie_id 0 91 │ │ │└INNER JOIN HASH ON info_type_id = id 2 1 │ │ │ │└FILTER id <= 110 2 1 │ │ │ │ TABLE SCAN info_type WHERE info = 'countries' 7 91 │ │ │ INNER JOIN HASH ON movie_id = movie_id 5 347 │ │ │ │└INNER JOIN HASH ON id = company_id 29 488 │ │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 142 31111 │ │ │ │ │ │└INNER JOIN HASH ON kind_id = id 1 2 │ │ │ │ │ │ │└FILTER (kind = 'movie') OR (kind = 'episode') 7 7 │ │ │ │ │ │ │ TABLE SCAN kind_type WHERE kind IN('movie','episode') 994 41458 │ │ │ │ │ │ INNER JOIN HASH ON id = movie_id 4885 324111 │ │ │ │ │ │ │└INNER JOIN HASH ON info_type_id = id 2 1 │ │ │ │ │ │ │ │└FILTER id >= 99 2 1 │ │ │ │ │ │ │ │ TABLE SCAN info_type WHERE info = 'rating' 276007 324111 │ │ │ │ │ │ │ FILTER movie_id <= 2525745 276007 324117 │ │ │ │ │ │ │ TABLE SCAN movie_info_idx WHERE info < '7.0' 505662 46093 │ │ │ │ │ │ FILTER id BETWEEN 2 AND 2525745 505662 46096 │ │ │ │ │ │ TABLE SCAN title WHERE production_year > 2009 521825 1770 │ │ │ │ │ TABLE SCAN movie_companies WHERE ( NOT contains(note,'(USA)')) AND (note LIKE '%(200%)%') 46999 437 │ │ │ │ TABLE SCAN company_name WHERE country_code != 'us' 2967144 861 │ │ │ FILTER movie_id BETWEEN 2 AND 2525745 2967144 861 │ │ │ FILTER (info = 'Germany') OR (info = 'German') OR (info = 'USA') OR (info = 'American') 14835720 2079 │ │ │ TABLE SCAN movie_info WHERE info IN('Germany','German','USA','American') 4523930 3898 │ │ TABLE SCAN movie_keyword WHERE movie_id <= 2525745 26834 3 │ FILTER (keyword = 'murder') OR (keyword = 'murder-in-title') OR (keyword = 'blood') OR (keyword = 'violence') 134170 1371 │ TABLE SCAN keyword WHERE keyword IN('murder','murder-in-title','blood','violence') 4 1 TABLE SCAN company_type WHERE id <= 2
	Estimate Actual Operator 1 1 PROJECT movie_company, rating, western_violent_movie 1 1 AGGREGATE MIN(name), MIN(info), MIN(title) 7666 10 DISTRIBUTE GATHER 7666 10 AGGREGATE MIN(name), MIN(info), MIN(title) 7666 31 INNER JOIN HASH ON id = kind_id 2 2 │└DISTRIBUTE GATHER 2 2 │ FILTER (kind = 'movie') OR (kind = 'episode') 7 7 │ DISTRIBUTE ROUND ROBIN 7 7 │ TABLE SCAN kind_type WHERE (kind = 'movie') OR (kind = 'episode') 26834 32 INNER JOIN HASH ON movie_id = id AND movie_id = id AND movie_id = id AND movie_id = id 26834 40185 │└DISTRIBUTE GATHER 26834 40185 │ INNER JOIN HASH ON id = keyword_id 26834 3 │ │└DISTRIBUTE GATHER 26834 3 │ │ FILTER keyword IN('murder','murder-in-title','blood','violence') 134170 134170 │ │ DISTRIBUTE ROUND ROBIN 134170 134170 │ │ TABLE SCAN keyword WHERE keyword IN('murder','murder-in-title','blood','violence') 45898 4137827 │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id AND movie_id = movie_id 25628 62374 │ │└DISTRIBUTE GATHER 25628 62374 │ │ INNER JOIN HASH ON id = info_type_id 23 1 │ │ │└DISTRIBUTE GATHER 23 1 │ │ │ FILTER info = 'rating' 113 113 │ │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ │ TABLE SCAN info_type WHERE info = 'rating' 25628 258207 │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id 25628 114885 │ │ │└DISTRIBUTE GATHER 25628 114885 │ │ │ INNER JOIN HASH ON id = info_type_id 23 1 │ │ │ │└DISTRIBUTE GATHER 23 1 │ │ │ │ FILTER info = 'countries' 113 113 │ │ │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ │ │ TABLE SCAN info_type WHERE info = 'countries' 122571 114885 │ │ │ INNER JOIN HASH ON movie_id = movie_id 104366 248388 │ │ │ │└DISTRIBUTE GATHER 104366 248388 │ │ │ │ INNER JOIN HASH ON id = company_type_id 4 4 │ │ │ │ │└TABLE SCAN company_type 104366 248388 │ │ │ │ INNER JOIN HASH ON id = company_id 47000 126230 │ │ │ │ │└DISTRIBUTE GATHER 47000 126230 │ │ │ │ │ FILTER country_code <> 'us' 234997 234997 │ │ │ │ │ TABLE SCAN company_name WHERE country_code <> 'us' 521826 303271 │ │ │ │ FILTER note NOT LIKE '%(USA)%' AND note LIKE '%(200%)%' 2609129 2609129 │ │ │ │ TABLE SCAN movie_companies WHERE ((note NOT LIKE '%(USA)%' AND note LIKE '%(200%)%') AND (((company_id >= 4) AND (company_id <= 234995)) AND TRUE)) AND (((company_type_id >= 1) AND (company_type_id <= 4)) AND company_type_id IN(1,2,3,4)) 2967144 588764 │ │ │ FILTER info IN('Germany','German','USA','American') 14835720 1355825 │ │ │ TABLE SCAN movie_info WHERE (info IN('Germany','German','USA','American') AND (((movie_id >= 82) AND (movie_id <= 2525666)) AND TRUE)) AND (((info_type_id >= 8) AND (info_type_id <= 8)) AND info_type_id IN 8) 276007 1172960 │ │ FILTER info < '7.0' 1380035 1380035 │ │ TABLE SCAN movie_info_idx WHERE ((info < '7.0') AND ((((movie_id >= 114) AND (movie_id <= 2525502)) AND ((movie_id >= 114) AND (movie_id <= 2525502))) AND TRUE)) AND (((info_type_id >= 101) AND (info_type_id <= 101)) AND info_type_id IN 101) 4523930 4523930 │ TABLE SCAN movie_keyword WHERE (((((movie_id >= 114) AND (movie_id <= 2525471)) AND ((movie_id >= 114) AND (movie_id <= 2525471))) AND ((movie_id >= 114) AND (movie_id <= 2525471))) AND TRUE) AND (((keyword_id >= 137) AND (keyword_id <= 875)) AND keyword_id IN(875,865,137)) 180594 533369 FILTER production_year > 2009 2528312 2528312 TABLE SCAN title WHERE ((production_year > 2009) AND ((((((id >= 10496) AND (id <= 2525471)) AND ((id >= 10496) AND (id <= 2525471))) AND ((id >= 10496) AND (id <= 2525471))) AND ((id >= 10496) AND (id <= 2525471))) AND TRUE)) AND (((kind_id >= 1) AND (kind_id <= 7)) AND kind_id IN(1,7))
	Estimate Actual Operator 1 1 AGGREGATE MIN(cn.name), MIN(mi_idx.info), MIN(t.title) 1 1 DISTRIBUTE GATHER 1 1 AGGREGATE MIN(cn.name), MIN(mi_idx.info), MIN(t.title) 1530 31 INNER JOIN HASH ON mi.info_type_id = it1.id 1530 1 │└DISTRIBUTE GATHER 4520000 1 │ TABLE SCAN info_type WHERE it1.info = 'countries' 1530 34 INNER JOIN HASH ON mc.movie_id = mi.movie_id 1530 669336 │└DISTRIBUTE GATHER 134000 669336 │ TABLE SCAN movie_info WHERE mi.info IN('Germany','German','USA','American') 1530 50 INNER JOIN HASH ON mi_idx.info_type_id = it2.id 1530 1 │└DISTRIBUTE GATHER 7 1 │ TABLE SCAN info_type WHERE it2.info = 'rating' 1530 149 INNER JOIN HASH ON mc.movie_id = mi_idx.movie_id 1530 62 │└DISTRIBUTE GATHER 492 62 │ INNER JOIN HASH ON mc.company_id = cn.id 492 95 │ │└DISTRIBUTE GATHER 476 95 │ │ INNER JOIN HASH ON mc.company_type_id = ct.id 476 4 │ │ │└DISTRIBUTE GATHER 4 4 │ │ │ TABLE SCAN company_type 476 95 │ │ INNER JOIN HASH ON mk.movie_id = mc.movie_id 476 3517 │ │ │└DISTRIBUTE GATHER 186 3517 │ │ │ INNER JOIN HASH ON t.kind_id = kt.id 186 2 │ │ │ │└DISTRIBUTE GATHER 1380000 2 │ │ │ │ TABLE SCAN kind_type WHERE kt.kind IN('movie','episode') 186 4037 │ │ │ INNER JOIN HASH ON mk.movie_id = t.id 186 37091 │ │ │ │└DISTRIBUTE GATHER 176 37091 │ │ │ │ INNER JOIN HASH ON mk.keyword_id = k.id 176 3 │ │ │ │ │└DISTRIBUTE GATHER 113 3 │ │ │ │ │ TABLE SCAN keyword WHERE k.keyword IN('murder','murder-in-title','blood','violence') 14800000 4519843 │ │ │ │ TABLE SCAN movie_keyword 113 531554 │ │ │ TABLE SCAN title WHERE (t.production_year IS NOT NULL) AND (t.production_year > 2009L) 235000 244695 │ │ TABLE SCAN movie_companies WHERE (mc.note IS NOT NULL) AND ( NOT contains(mc.note,'(USA)')) AND mc.note LIKE '%(200%)%' 2610000 123973 │ TABLE SCAN company_name WHERE (cn.country_code IS NOT NULL) AND ( NOT (cn.country_code = 'us')) 2530000 747672 TABLE SCAN movie_info_idx WHERE mi_idx.info < '7.0'
	Estimate Actual Operator 1 1 AGGREGATE MIN(name as name) AS Expr1022, MIN(info as info) AS Expr1023, MIN(title as title) AS Expr1024 1 31 FILTER info as info = 'rating' 1 92 INNER JOIN LOOP ON Bmk1006 = Bmk1006 1 92 │└TABLE SEEK info_type AS it2 1 92 INNER JOIN LOOP ON mi_idx.info_type_id = it2.id 1 92 │└TABLE SEEK info_type AS it2 1 92 INNER JOIN LOOP ON t.id = mi_idx.movie_id 1 92 │└TABLE SEEK movie_info_idx AS mi_idx WHERE info as info < '7.0' 1 34 FILTER kind as kind = 'episode' OR kind as kind = 'movie' 1 35 INNER JOIN LOOP ON Bmk1010 = Bmk1010 1 35 │└TABLE SEEK kind_type AS kt 1 35 INNER JOIN LOOP ON t.kind_id = kt.id 1 35 │└TABLE SEEK kind_type AS kt 1 35 INNER JOIN LOOP ON Bmk1020 = Bmk1020 0 35 │└TABLE SEEK title AS t WHERE production_year as production_year > 2009 8 65436 PROJECT BmkToPage Bmk1020 AS Expr1082 8 65436 INNER JOIN LOOP ON mk.movie_id = t.id 1 65436 │└TABLE SEEK title AS t 8 65436 FILTER country_code as country_code <> 'us' 15 70725 INNER JOIN LOOP ON Bmk1000 = Bmk1000 1 70725 │└TABLE SEEK company_name AS cn 15 70725 INNER JOIN LOOP ON mc.company_id = cn.id 1 70725 │└TABLE SEEK company_name AS cn 15 70725 FILTER NOT note as note LIKE '%(USA)%' AND note as note LIKE '%(200%)%' 133 249339 INNER JOIN LOOP ON Bmk1012 = Bmk1012 1 249339 │└TABLE SEEK movie_companies AS mc 133 249339 PROJECT BmkToPage Bmk1012 AS Expr1080 133 249339 INNER JOIN LOOP ON mk.movie_id = mc.movie_id 9 249339 │└TABLE SEEK movie_companies AS mc 13 23042 FILTER info as info = 'American' OR info as info = 'German' OR info as info = 'Germany' OR info as info = 'USA' 308 44297 INNER JOIN LOOP ON mi.movie_id = mi.movie_id AND Uniq1015 = Uniq1015 1 44297 │└TABLE SEEK movie_info AS mi 308 44297 INNER JOIN LOOP ON it1.id = mi.info_type_id AND mk.movie_id = mi.movie_id 1 44297 │└TABLE SEEK movie_info AS mi 362 37091 INNER JOIN LOOP ON info as info = 'countries' 1 1 │└MATERIALISE AS m40 1 1 │ TABLE SCAN info_type AS it1 WHERE info as info = 'countries' 362 37091 INNER JOIN LOOP ON Bmk1018 = Bmk1018 1 37091 │└TABLE SEEK movie_keyword AS mk 362 37091 INNER JOIN LOOP ON k.id = mk.keyword_id 90 37091 │└TABLE SEEK movie_keyword AS mk 4 3 TABLE SCAN keyword AS k WHERE keyword as keyword = 'blood' OR keyword as keyword = 'murder' OR keyword as keyword = 'murder-in-title' OR keyword as keyword = 'violence'
	Estimate Actual Operator 1 ∞ PROJECT min AS movie_company, min_53 AS rating, min_54 AS western_violent_movie 1 1 AGGREGATE MIN(min_55) AS min, MIN(min_56) AS min_53, MIN(min_57) AS min_54 - 16 DISTRIBUTE GATHER - 16 AGGREGATE MIN(name) AS min_55, MIN(info_36) AS min_56, MIN(title) AS min_57 - 31 INNER JOIN HASH ON kind_id = id_17 7 2 │└DISTRIBUTE GATHER 7 2 │ PROJECT id AS id_17 7 2 │ FILTER kind IN('episode','movie') 7 2 │ TABLE SCAN kind_type - 32 INNER JOIN HASH ON movie_id = id_46 176706 533274 │└DISTRIBUTE HASH ON id_46 176706 533274 │ PROJECT id AS id_46, title, kind_id 176706 533274 │ FILTER production_year > 2009 176706 533274 │ TABLE SCAN title - 40185 INNER JOIN HASH ON keyword_id = id_13 134170 3 │└DISTRIBUTE GATHER 134170 3 │ PROJECT id AS id_13 134170 3 │ FILTER keyword IN('blood','murder','murder-in-title','violence') 134170 3 │ TABLE SCAN keyword - 40185 INNER JOIN HASH ON movie_id = movie_id_42 4523930 37091 │└DISTRIBUTE HASH ON movie_id_42 4523930 37091 │ PROJECT movie_id AS movie_id_42, keyword_id 4523930 37091 │ TABLE SCAN movie_keyword - 22559 INNER JOIN HASH ON info_type_id_35 = id_8 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_8 113 1 │ FILTER info = 'rating' 113 1 │ TABLE SCAN info_type - 22559 INNER JOIN HASH ON movie_id = movie_id_34 1380035 18183 │└DISTRIBUTE HASH ON movie_id_34 1380035 18183 │ PROJECT movie_id AS movie_id_34, info_type_id AS info_type_id_35, info AS info_36 1380035 18183 │ FILTER info < '7.0' 1380035 18183 │ TABLE SCAN movie_info_idx - 22559 INNER JOIN HASH ON info_type_id = id_4 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_4 113 1 │ FILTER info = 'countries' 113 1 │ TABLE SCAN info_type - 22559 INNER JOIN HASH ON movie_id = movie_id_27 13352148 11742 │└DISTRIBUTE HASH ON movie_id_27 13352148 11742 │ PROJECT movie_id AS movie_id_27, info_type_id 13352148 11742 │ FILTER info IN('American','German','Germany','USA') 13352148 11742 │ TABLE SCAN movie_info - 248388 INNER JOIN HASH ON company_type_id = id_0 4 4 │└DISTRIBUTE GATHER 4 4 │ PROJECT id AS id_0 4 4 │ TABLE SCAN company_type - 248388 INNER JOIN HASH ON id = company_id 2348216 303271 │└DISTRIBUTE HASH ON company_id 2348216 303271 │ FILTER NOT (note LIKE '%(USA)%') AND (note LIKE '%(200%)%') 2348216 303271 │ TABLE SCAN movie_companies 105537 126230 FILTER country_code <> 'us' 105537 126230 TABLE SCAN company_name
	Estimate Actual Operator 1 1 AGGREGATE MIN(name), MIN(info), MIN(title) 1 31 INNER JOIN LOOP ON id = info_type_id 1 92 │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 34 │ │└INNER JOIN LOOP ON id = info_type_id 2 37 │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 62 │ │ │ │└INNER JOIN LOOP ON id = company_type_id AND (id = company_type_id) 1 62 │ │ │ │ │└INNER JOIN LOOP ON id = company_id 2 95 │ │ │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 8 3517 │ │ │ │ │ │ │└INNER JOIN LOOP ON id = kind_id AND (id = kind_id) 29 4040 │ │ │ │ │ │ │ │└INNER JOIN LOOP ON id = movie_id 135 37091 │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON keyword_id = id 4 3 │ │ │ │ │ │ │ │ │ │└TABLE SEEK keyword AS k 915 37091 │ │ │ │ │ │ │ │ │ TABLE SEEK movie_keyword AS mk 37091 37091 │ │ │ │ │ │ │ │ TABLE SEEK title AS t WHERE t.production_year > 2009 2 2 │ │ │ │ │ │ │ TABLE SCAN kind_type AS kt WHERE kt.kind IN('movie','episode') 3517 3517 │ │ │ │ │ │ TABLE SEEK movie_companies AS mc WHERE (mc.note NOT LIKE '%(USA)%') AND (mc.note LIKE '%(200%)%') 95 95 │ │ │ │ │ TABLE SEEK company_name AS cn WHERE cn.country_code <> 'us' 4 1 │ │ │ │ TABLE SCAN company_type AS ct 124 62 │ │ │ TABLE SEEK movie_info AS mi WHERE mi.info IN('Germany','German','USA','American') 37 37 │ │ TABLE SEEK info_type AS it1 WHERE it1.info = 'countries' 68 92 │ TABLE SEEK movie_info_idx AS mi_idx WHERE mi_idx.info < '7.0' 92 92 TABLE SEEK info_type AS it2 WHERE it2.info = 'rating'