Planner — IMDB — JOB-25B

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 job.cast_info AS ci,
     job.info_type AS it1,
     job.info_type AS it2,
     job.keyword AS k,
     job.movie_info AS mi,
     job.movie_info_idx AS mi_idx,
     job.movie_keyword AS mk,
     job.name AS n,
     job.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;

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 5,904,012 5.9M Rank		Estimation Error Est Err 5,904,040 5.9M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 124,246 124K Rank	Estimation Error Est Err 6 6 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 44,052,934 44M Rank		Estimation Error Est Err 97,880,880 98M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 44,887,568 45M Rank	Estimation Error Est Err 1,372 1.4K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 8,910,525 8.9M Rank		Estimation Error Est Err 6,005,644 6M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 3,204,829 3.2M Rank	Estimation Error Est Err 7 7 Rank	Estimation Error Est Err 3,076,821 3.1M Rank
Estimation Error Est Err 27,463,576 27M Rank		Estimation Error Est Err 7,783,198 7.8M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,660,717 1.7M Rank	Estimation Error Est Err 16 16 Rank	Estimation Error Est Err 9,089,225 9.1M Rank
Estimation Error Est Err 31,189 31K Rank		Estimation Error Est Err 31,206 31K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 61,684 62K Rank	Estimation Error Est Err 6 6 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 124,260 124K Rank	Estimation Error Est Err 124,260 124K Rank	Estimation Error Est Err 124,255 124K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 124,255 124K Rank	Estimation Error Est Err 6 6 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 1,281 1.3K Rank	Estimation Error Est Err 1,207 1.2K Rank	Estimation Error Est Err 1,259 1.3K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,207 1.2K Rank	Estimation Error Est Err 6 6 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 1,739,681 1.7M Rank		Estimation Error Est Err 36 36 Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,739,683 1.7M Rank	Estimation Error Est Err 22 22 Rank	Estimation Error Est Err 1,739,694 1.7M Rank

Actual Query Plans

Query Plan per Engine ?
	Query Plan
	Estimate Actual Operator 1 1 AGGREGATE min, min, min, min 1 6 INNER JOIN HASH ON id = info_type_id70 1 1 │└TABLE SCAN info_type WHERE info = votes 1 18 INNER JOIN HASH ON movie_id48 = movie_id69 1 6 │└INNER JOIN HASH ON id6 = info_type_id 1 1 │ │└TABLE SCAN info_type WHERE info = genres 1 6 │ INNER JOIN HASH ON id56 = person_id 1 6 │ │└INNER JOIN HASH ON movie_id48 = movie_id39 1 9 │ │ │└INNER JOIN HASH ON movie_id39 = movie_id 1 9 │ │ │ │└INNER JOIN HASH ON id23 = movie_id 119 62096 │ │ │ │ │└INNER JOIN HASH ON id11 = keyword_id 4 5 │ │ │ │ │ │└TABLE SCAN keyword WHERE keyword BETWEEN blood AND murder AND keyword IN(blood,death,female - nudity,gore,murder) 4523930 4523930 │ │ │ │ │ TABLE SCAN movie_keyword 979 30 │ │ │ │ TABLE SCAN title WHERE production_year >= 2011 AND title) Vampire 57952 5 │ │ │ TABLE SCAN movie_info WHERE info = Horror 1274215 3 │ │ TABLE SCAN cast_info WHERE note BETWEEN (head writer) AND (written by) AND note50 IN((head writer),(story editor),story,writer,(written by)) 1778509 2 │ TABLE SCAN name WHERE gender = m 1380035 1380035 TABLE SCAN movie_info_idx
	Estimate Actual Operator - 1 PROJECT a1 AS movie_budget, a2 AS movie_votes, a3 AS male_writer, a4 AS violent_movie_title - 1 AGGREGATE MIN(info_left) AS a1, MIN(info_right) AS a2, MIN(name) AS a3, MIN(title) AS a4 - 1372 PROJECT info, info, name, title - 1372 PROJECT info, info, name, title - 1372 INNER JOIN HASH ON tuple(PROJECTION_2953.movie_id,PROJECTION_2953.movie_id,PROJECTION_2953.movie_id,PROJECTION_2953.movie_id,PROJECTION_2953.movie_id,PROJECTION_2953.movie_id) = tuple(PROJECTION_2938.movie_id,PROJECTION_2938.movie_id,PROJECTION_2938.movie_id,PROJECTION_2938.id,PROJECTION_2938.id,PROJECTION_2938.id) - 16 │└PROJECT movie_id AS movie_id_right, id, info AS info_right, title - 16 │ PROJECT info, movie_id, title, id - 16 │ INNER JOIN HASH ON PROJECTION_2950.id = PROJECTION_2941.movie_id - 459925 │ │└PROJECT movie_id, info - 459925 │ │ PROJECT info, movie_id - 459925 │ │ INNER JOIN HASH ON PROJECTION_2947.info_type_id = PROJECTION_2944.id - 1 │ │ │└PROJECT id - 1 │ │ │ PROJECT id - 1 │ │ │ TABLE SCAN info_type WHERE info = 'votes' - 1380035 │ │ PROJECT info_type_id, info, movie_id - 1380035 │ │ PROJECT info, movie_id, info_type_id - 1380035 │ │ TABLE SCAN movie_info_idx - 73 │ PROJECT id, title - 73 │ PROJECT id, title - 73 │ TABLE SCAN title WHERE (production_year > 2010) AND startsWith(title,'Vampire') - 8378116 PROJECT movie_id_left, movie_id_left_2, movie_id AS movie_id_left_3, info AS info_left, name - 8378116 PROJECT movie_id, info, movie_id, movie_id, name - 8378116 INNER JOIN HASH ON PROJECTION_2959.person_id = PROJECTION_2956.id - 1739579 │└PROJECT id, name - 1739579 │ PROJECT id, name - 1739579 │ TABLE SCAN name WHERE gender = 'm' - 17036235 PROJECT person_id, movie_id, info, movie_id, movie_id - 17036235 PROJECT movie_id, person_id, info, movie_id, movie_id - 17036235 INNER JOIN HASH ON PROJECTION_2965.keyword_id = PROJECTION_2962.id - 134170 │└PROJECT id - 134170 │ PROJECT id - 134170 │ TABLE SCAN keyword WHERE TRUE - 17036235 PROJECT keyword_id, movie_id, person_id, info, movie_id, movie_id - 17036235 PROJECT movie_id, person_id, info, movie_id, movie_id, keyword_id - 17036235 INNER JOIN HASH ON tuple(PROJECTION_2971.movie_id,PROJECTION_2971.movie_id) = tuple(PROJECTION_2968.movie_id,PROJECTION_2968.movie_id) - 4523930 │└PROJECT movie_id AS movie_id_right, keyword_id - 4523930 │ PROJECT movie_id, keyword_id - 4523930 │ TABLE SCAN movie_keyword - 746153 PROJECT movie_id_left, movie_id AS movie_id_left_2, person_id, info - 746153 PROJECT movie_id, person_id, info, movie_id - 746153 INNER JOIN HASH ON PROJECTION_2977.info_type_id = PROJECTION_2974.id - 1 │└PROJECT id - 1 │ PROJECT id - 1 │ TABLE SCAN info_type WHERE info = 'genres' - 769607 PROJECT info_type_id, movie_id, person_id, info, movie_id - 769607 PROJECT movie_id, person_id, info, movie_id, info_type_id - 769607 INNER JOIN HASH ON PROJECTION_2983.movie_id = PROJECTION_2980.movie_id - 30801 │└PROJECT movie_id AS movie_id_right, info, info_type_id - 30801 │ PROJECT movie_id, info, info_type_id - 30801 │ TABLE SCAN movie_info WHERE info = 'Horror' - 36244344 PROJECT movie_id AS movie_id_left, person_id - 36244344 PROJECT movie_id, person_id - 36244344 TABLE SCAN cast_info WHERE TRUE
	Estimate Actual Operator - 1 AGGREGATE MIN(#0), MIN(#1), MIN(#2), MIN(#3) 0 6 PROJECT info, info, name, title 0 6 INNER JOIN HASH ON id = person_id 0 6 │└INNER JOIN HASH ON movie_id = id 0 9 │ │└INNER JOIN HASH ON id = keyword_id 0 74 │ │ │└INNER JOIN HASH ON movie_id = movie_id 0 10 │ │ │ │└INNER JOIN HASH ON id = info_type_id 0 30 │ │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 0 23 │ │ │ │ │ │└INNER JOIN HASH ON id = movie_id 0 30413 │ │ │ │ │ │ │└INNER JOIN HASH ON info_type_id = id 2 1 │ │ │ │ │ │ │ │└FILTER id <= 110 2 1 │ │ │ │ │ │ │ │ TABLE SCAN info_type WHERE info = 'genres' 15 30413 │ │ │ │ │ │ │ FILTER movie_id BETWEEN 2 AND 2525793 15 30413 │ │ │ │ │ │ │ TABLE SCAN movie_info WHERE info = 'Horror' 505662 23 │ │ │ │ │ │ FILTER id BETWEEN 2 AND 2525793 505662 23 │ │ │ │ │ │ TABLE SCAN title WHERE production_year > 2010 AND title >= 'Vampire' AND title < 'Vampirf' 1380035 30 │ │ │ │ │ TABLE SCAN movie_info_idx 2 1 │ │ │ │ FILTER id >= 99 2 1 │ │ │ │ TABLE SCAN info_type WHERE info = 'votes' 4523930 74 │ │ │ TABLE SCAN movie_keyword WHERE movie_id <= 2525793 26834 4 │ │ FILTER IN ... 134170 530 │ │ INNER JOIN HASH ON keyword = #0 0 5 │ │ │└SCAN MATERIALISED 134170 530 │ │ TABLE SCAN keyword WHERE keyword IN('murder','blood','gore','death','female-nudity') 7248868 3 │ FILTER movie_id BETWEEN 2 AND 2525793 7248868 3 │ FILTER IN ... 36244344 105 │ INNER JOIN HASH ON note = #0 0 5 │ │└SCAN MATERIALISED 36244344 105 │ TABLE SCAN cast_info WHERE note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 2083746 2 FILTER id <= 4061926 2083746 2 TABLE SCAN "name" WHERE gender = 'm'
	Estimate Actual Operator 1 1 PROJECT movie_budget, movie_votes, male_writer, violent_movie_title 1 1 AGGREGATE MIN(info), MIN(info), MIN(name), MIN(title) 494319 10 DISTRIBUTE GATHER 494319 10 AGGREGATE MIN(info), MIN(info), MIN(name), MIN(title) 494319 6 INNER JOIN HASH ON movie_id = id AND movie_id = id AND movie_id = id AND movie_id = id 494319 4407 │└DISTRIBUTE HASH ON movie_id, movie_id, movie_id, movie_id 494319 4407 │ INNER JOIN HASH ON person_id = id 494319 7112 │ │└DISTRIBUTE HASH ON person_id 494319 7112 │ │ INNER JOIN HASH ON id = keyword_id 26834 5 │ │ │└DISTRIBUTE GATHER 26834 5 │ │ │ FILTER keyword IN('murder','blood','gore','death','female-nudity') 134170 134170 │ │ │ DISTRIBUTE ROUND ROBIN 134170 134170 │ │ │ TABLE SCAN keyword WHERE keyword IN('murder','blood','gore','death','female-nudity') 2471597 207091 │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id AND movie_id = movie_id 1380035 8650 │ │ │└DISTRIBUTE HASH ON movie_id, movie_id, movie_id 1380035 8650 │ │ │ INNER JOIN HASH ON id = info_type_id 23 1 │ │ │ │└DISTRIBUTE GATHER 23 1 │ │ │ │ FILTER info = 'votes' 113 113 │ │ │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ │ │ TABLE SCAN info_type WHERE info = 'votes' 1380035 25956 │ │ │ PROJECT person_id, movie_id, movie_id, info, movie_id, info_type_id, info 1380035 25956 │ │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id 1380035 1380035 │ │ │ │└DISTRIBUTE HASH ON movie_id, movie_id 1380035 1380035 │ │ │ │ TABLE SCAN movie_info_idx WHERE ((info_type_id >= 100) AND (info_type_id <= 100)) AND info_type_id IN 100 1780068 15897 │ │ │ DISTRIBUTE HASH ON movie_id, movie_id 1780068 15897 │ │ │ INNER JOIN HASH ON id = info_type_id 23 1 │ │ │ │└DISTRIBUTE GATHER 23 1 │ │ │ │ FILTER info = 'genres' 113 113 │ │ │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ │ │ TABLE SCAN info_type WHERE info = 'genres' 8513371 15897 │ │ │ PROJECT person_id, movie_id, movie_id, info_type_id, info 8513371 15897 │ │ │ INNER JOIN HASH ON movie_id = movie_id 2967144 30413 │ │ │ │└DISTRIBUTE HASH ON movie_id 2967144 30413 │ │ │ │ FILTER info = 'Horror' 14835720 1724005 │ │ │ │ TABLE SCAN movie_info WHERE ((info = 'Horror') AND (((info_type_id >= 3) AND (info_type_id <= 3)) AND info_type_id IN 3)) AND CASE MOD(HASH_REPARTITION(movie_id,movie_id),10) WHEN 1 THEN ((((movie_id >= 57) AND (movie_id <= 2525790)) AND ((movie_id >= 57) AND (movie_id <= 2525790))) AND TRUE) WHEN 3 THEN ((((movie_id >= 11) AND (movie_id <= 2525784)) AND ((movie_id >= 11) AND (movie_id <= 2525784))) AND TRUE) WHEN 5 THEN ((((movie_id >= 52) AND (movie_id <=... 7248869 1244716 │ │ │ DISTRIBUTE HASH ON movie_id 7248869 1244716 │ │ │ FILTER note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 36244344 15326137 │ │ │ TABLE SCAN cast_info WHERE note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') AND CASE MOD(HASH_REPARTITION movie_id,10) WHEN 0 THEN (((movie_id >= 11530) AND (movie_id <= 2525631)) AND TRUE) WHEN 1 THEN (((movie_id >= 31537) AND (movie_id <= 2525625)) AND TRUE) WHEN 2 THEN (((movie_id >= 4665) AND (movie_id <= 2524996)) AND TRUE) WHEN 3 THEN (((movie_id >= 679) AND (movie_id <= 2525793)) AND TRUE) WHEN 4 THEN (((movie_id >= 34054) AN... 4523930 4523930 │ │ DISTRIBUTE HASH ON movie_id, movie_id, movie_id 4523930 4523930 │ │ TABLE SCAN movie_keyword WHERE CASE MOD(HASH_REPARTITION(movie_id,movie_id,movie_id),10) WHEN 0 THEN (((((movie_id >= 188281) AND (movie_id <= 2521028)) AND ((movie_id >= 188281) AND (movie_id <= 2521028))) AND ((movie_id >= 188281) AND (movie_id <= 2521028))) AND TRUE) WHEN 1 THEN (((((movie_id >= 96537) AND (movie_id <= 2524953)) AND ((movie_id >= 96537) AND (movie_id <= 2524953))) AND ((movie_id >= 96537) AND (movie_id <= 2524953))) AND TRUE) WHEN 2 THEN (((((mo... 833499 1739579 │ DISTRIBUTE HASH ON id 833499 1739579 │ FILTER gender = 'm' 4167491 1846761 │ TABLE SCAN name WHERE (gender = 'm') AND CASE MOD(HASH_REPARTITION id,10) WHEN 0 THEN (((id >= 2281) AND (id <= 3858670)) AND TRUE) WHEN 1 THEN (((id >= 28576) AND (id <= 3225587)) AND TRUE) WHEN 2 THEN (((id >= 3656) AND (id <= 3227769)) AND TRUE) WHEN 3 THEN (((id >= 10782) AND (id <= 3221761)) AND TRUE) WHEN 4 THEN (((id >= 15326) AND (id <= 3227684)) AND TRUE) WHEN 5 THEN (((id >= 13047) AND (id <= 3222478)) AND TRUE) WHEN 6 THEN (((id >= 3168) AND (id <= 3704202))... 505663 73 DISTRIBUTE HASH ON id, id, id, id 505663 73 FILTER (production_year > 2010) AND title LIKE 'Vampire%' 2528312 2528312 TABLE SCAN title WHERE ((production_year > 2010) AND title LIKE 'Vampire%') AND CASE MOD(HASH_REPARTITION(id,id,id,id),10) WHEN 1 THEN ((((((id >= 506304) AND (id <= 2520945)) AND ((id >= 506304) AND (id <= 2520945))) AND ((id >= 506304) AND (id <= 2520945))) AND ((id >= 506304) AND (id <= 2520945))) AND TRUE) WHEN 3 THEN ((((((id >= 560970) AND (id <= 2521126)) AND ((id >= 560970) AND (id <= 2521126))) AND ((id >= 560970) AND (id <= 2521126))) AND ((id >= 560970) AND (id ...
	Estimate Actual Operator 1 1 AGGREGATE MIN(mi.info), MIN(mi_idx.info), MIN(n.name), MIN(t.title) 1 1 DISTRIBUTE GATHER 1 1 AGGREGATE MIN(mi.info), MIN(mi_idx.info), MIN(n.name), MIN(t.title) 315 6 INNER JOIN HASH ON ci.movie_id = mk.movie_id 315 9 │└DISTRIBUTE GATHER 315 9 │ INNER JOIN HASH ON mk.movie_id = t.id 315 62096 │ │└DISTRIBUTE GATHER 6 62096 │ │ INNER JOIN HASH ON mk.keyword_id = k.id 6 5 │ │ │└DISTRIBUTE GATHER 2530000 5 │ │ │ TABLE SCAN keyword WHERE k.keyword IN('murder','blood','gore','death','female-nudity') 36200000 4519847 │ │ TABLE SCAN movie_keyword 14800000 18 │ TABLE SCAN title WHERE (t.production_year IS NOT NULL) AND (t.production_year > 2010L) AND startswith(t.title,'Vampire') 96 4851 INNER JOIN HASH ON ci.person_id = n.id 96 1739579 │└DISTRIBUTE GATHER 113 1739579 │ TABLE SCAN name WHERE (n.gender IS NOT NULL) AND (n.gender = 'm') 96 8650 INNER JOIN HASH ON mi.movie_id = ci.movie_id 96 1244716 │└DISTRIBUTE GATHER 4170000 1244716 │ TABLE SCAN cast_info WHERE ci.note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 213000 16480 INNER JOIN HASH ON mi_idx.info_type_id = it2.id 213000 1 │└DISTRIBUTE GATHER 113 1 │ TABLE SCAN info_type WHERE it2.info = 'votes' 426000 49440 INNER JOIN HASH ON mi.movie_id = mi_idx.movie_id 426000 30413 │└DISTRIBUTE GATHER 211 30413 │ INNER JOIN HASH ON mi.info_type_id = it1.id 211 1 │ │└DISTRIBUTE GATHER 134000 1 │ │ TABLE SCAN info_type WHERE it1.info = 'genres' 4520000 30413 │ TABLE SCAN movie_info WHERE mi.info = 'Horror' 1380000 1375945 TABLE SCAN movie_info_idx
	Estimate Actual Operator 1 1 AGGREGATE MIN(info as info) AS Expr1018, MIN(info as info) AS Expr1019, MIN(name as name) AS Expr1020, MIN(title as title) AS Expr1021 1 6 FILTER keyword as keyword = 'blood' OR keyword as keyword = 'death' OR keyword as keyword = 'female-nudity' OR keyword as keyword = 'gore' OR keyword as keyword = 'murder' 18 35 INNER JOIN LOOP ON Bmk1006 = Bmk1006 1 35 │└TABLE SEEK keyword AS k 18 35 INNER JOIN LOOP ON mk.keyword_id = k.id 1 35 │└TABLE SEEK keyword AS k 18 35 INNER JOIN LOOP ON Bmk1012 = Bmk1012 1 35 │└TABLE SEEK movie_keyword AS mk 18 35 INNER JOIN LOOP ON t.id = mk.movie_id 18 35 │└TABLE SEEK movie_keyword AS mk 1 4 FILTER gender as gender = 'm' 1 4 INNER JOIN LOOP ON Bmk1014 = Bmk1014 1 4 │└TABLE SEEK name AS n 1 4 PROJECT BmkToPage Bmk1014 AS Expr1076 1 4 INNER JOIN LOOP ON ci.person_id = n.id 1 4 │└TABLE SEEK name AS n 1 4 FILTER info as info = 'votes' 2 12 INNER JOIN LOOP ON Bmk1004 = Bmk1004 1 12 │└TABLE SEEK info_type AS it2 2 12 INNER JOIN LOOP ON mi_idx.info_type_id = it2.id 1 12 │└TABLE SEEK info_type AS it2 2 12 INNER JOIN LOOP ON t.id = mi_idx.movie_id 2 12 │└TABLE SEEK movie_info_idx AS mi_idx 1 13 FILTER note as note = '(head writer)' OR note as note = '(story editor)' OR note as note = '(story)' OR note as note = '(writer)' OR note as note = '(written by)' 30 477 INNER JOIN LOOP ON Bmk1000 = Bmk1000 1 477 │└TABLE SEEK cast_info AS ci 30 477 PROJECT BmkToPage Bmk1000 AS Expr1074 30 477 INNER JOIN LOOP ON t.id = ci.movie_id 30 477 │└TABLE SEEK cast_info AS ci 1 23 FILTER info as info = 'genres' 41 23 INNER JOIN LOOP ON Bmk1002 = Bmk1002 1 23 │└TABLE SEEK info_type AS it1 41 23 INNER JOIN LOOP ON mi.info_type_id = it1.id 1 23 │└TABLE SEEK info_type AS it1 41 23 INNER JOIN LOOP ON t.id = mi.movie_id 1 23 │└TABLE SEEK movie_info AS mi WHERE info as info = 'Horror' 355 74 TABLE SCAN title AS t WHERE (production_year as production_year > 2010) AND (title as title LIKE 'Vampire%')
	Estimate Actual Operator 1 ∞ PROJECT min AS movie_budget, min_45 AS movie_votes, min_46 AS male_writer, min_47 AS violent_movie_title 1 1 AGGREGATE MIN(min_48) AS min, MIN(min_49) AS min_45, MIN(min_50) AS min_46, MIN(min_51) AS min_47 - 16 DISTRIBUTE GATHER - 16 AGGREGATE MIN(info_15) AS min_48, MIN(info_23) AS min_49, MIN(name) AS min_50, MIN(title) AS min_51 - 6 INNER JOIN HASH ON movie_id = id_37 143132 73 │└DISTRIBUTE HASH ON id_37 143132 73 │ PROJECT id AS id_37, title 143132 73 │ FILTER (production_year > 2010) AND (title >= 'Vampire') AND (title < 'Vampirf') AND (title LIKE 'Vampire%') 143132 73 │ TABLE SCAN title - 6 INNER JOIN HASH ON person_id = id_33 4167491 1739579 │└DISTRIBUTE HASH ON id_33 4167491 1739579 │ PROJECT id AS id_33, name 4167491 1739579 │ FILTER gender = 'm' 4167491 1739579 │ TABLE SCAN name - 6 INNER JOIN HASH ON keyword_id = id_9 134170 5 │└DISTRIBUTE GATHER 134170 5 │ PROJECT id AS id_9 134170 5 │ FILTER keyword IN('blood','death','female-nudity','gore','murder') 134170 5 │ TABLE SCAN keyword - 6 INNER JOIN HASH ON movie_id = movie_id_29 4523930 9 │└DISTRIBUTE HASH ON movie_id_29 4523930 9 │ PROJECT movie_id AS movie_id_29, keyword_id 4523930 9 │ TABLE SCAN movie_keyword - 3 INNER JOIN HASH ON info_type_id_22 = id_4 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_4 113 1 │ FILTER info = 'votes' 113 1 │ TABLE SCAN info_type - 3 INNER JOIN HASH ON movie_id = movie_id_21 1380035 5 │└DISTRIBUTE HASH ON movie_id_21 1380035 5 │ PROJECT movie_id AS movie_id_21, info_type_id AS info_type_id_22, info AS info_23 1380035 5 │ TABLE SCAN movie_info_idx - 3 INNER JOIN HASH ON info_type_id = id_0 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_0 113 1 │ FILTER info = 'genres' 113 1 │ TABLE SCAN info_type - 3 INNER JOIN HASH ON movie_id = movie_id_14 13352148 5 │└DISTRIBUTE HASH ON movie_id_14 13352148 5 │ PROJECT movie_id AS movie_id_14, info_type_id, info AS info_15 13352148 5 │ FILTER info = 'Horror' 13352148 5 │ TABLE SCAN movie_info 32619910 3 FILTER note IN('(head writer)','(story editor)','(story)','(writer)','(written by)') 32619910 3 TABLE SCAN cast_info
	Estimate Actual Operator 1 1 AGGREGATE MIN(info), MIN(info), MIN(name), MIN(title) 1 6 INNER JOIN LOOP ON id = person_id 1 6 │└INNER JOIN LOOP ON id = info_type_id 1 18 │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 6 │ │ │└INNER JOIN LOOP ON id = info_type_id 1 6 │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 6 │ │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 9 │ │ │ │ │ │└INNER JOIN LOOP ON id = movie_id 169 62096 │ │ │ │ │ │ │└INNER JOIN LOOP ON keyword_id = id 5 5 │ │ │ │ │ │ │ │└TABLE SEEK keyword AS k 1525 62096 │ │ │ │ │ │ │ TABLE SEEK movie_keyword AS mk 62096 62096 │ │ │ │ │ │ TABLE SEEK title AS t WHERE (t.production_year > 2010) AND (t.title LIKE 'Vampire%') 9 9 │ │ │ │ │ TABLE SEEK cast_info AS ci WHERE ci.note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 6 6 │ │ │ │ TABLE SEEK movie_info AS mi WHERE mi.info = 'Horror' 6 6 │ │ │ TABLE SEEK info_type AS it1 WHERE it1.info = 'genres' 18 18 │ │ TABLE SEEK movie_info_idx AS mi_idx 18 18 │ TABLE SEEK info_type AS it2 WHERE it2.info = 'votes' 6 6 TABLE SEEK name AS n WHERE n.gender = 'm'