Planner — IMDB — JOB-25A

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.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 8,444,742 8.4M Rank		Estimation Error Est Err 8,477,441 8.5M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 173,257 173K Rank	Estimation Error Est Err 4,407 4.4K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 46,581,173 47M Rank		Estimation Error Est Err 58,768,914 59M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 22,281,901 22M Rank	Estimation Error Est Err 8,181,261 8.2M Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 11,423,917 11M Rank		Estimation Error Est Err 11,478,201 11M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 276,068 276K Rank	Estimation Error Est Err 4,408 4.4K Rank	Estimation Error Est Err 148,060 148K Rank
Estimation Error Est Err 27,463,576 27M Rank		Estimation Error Est Err 10,311,437 10M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,660,717 1.7M Rank	Estimation Error Est Err 4,417 4.4K Rank	Estimation Error Est Err 11,617,464 12M Rank
Estimation Error Est Err 835,453 835K Rank		Estimation Error Est Err 877,305 877K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,198,081 1.2M Rank	Estimation Error Est Err 4,407 4.4K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 297,137 297K Rank	Estimation Error Est Err 297,137 297K Rank	Estimation Error Est Err 449,851 450K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 347,855 348K Rank	Estimation Error Est Err 4,407 4.4K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 1,461,917 1.5M Rank	Estimation Error Est Err 1,461,799 1.5M Rank	Estimation Error Est Err 1,482,577 1.5M Rank	Estimation Error Est Err 591,810 592K Rank	Estimation Error Est Err 1,482,573 1.5M Rank	Estimation Error Est Err 4,407 4.4K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 4,374,866 4.4M Rank		Estimation Error Est Err 39,907 40K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 4,385,528 4.4M Rank	Estimation Error Est Err 4,423 4.4K Rank	Estimation Error Est Err 4,371,357 4.4M Rank

Actual Query Plans

Query Plan per Engine ?
	Query Plan
	Estimate Actual Operator 1 1 AGGREGATE min, min, min, min 5 4407 INNER JOIN HASH ON id = info_type_id70 1 1 │└TABLE SCAN info_type WHERE info = votes 11 13233 INNER JOIN HASH ON movie_id24 = movie_id69 8 4690 │└INNER JOIN HASH ON id6 = info_type_id 1 1 │ │└TABLE SCAN info_type WHERE info = genres 8 5196 │ INNER JOIN HASH ON id53 = movie_id24 8 5196 │ │└INNER JOIN HASH ON id41 = person_id 16 8230 │ │ │└INNER JOIN HASH ON movie_id33 = movie_id24 29 13309 │ │ │ │└INNER JOIN HASH ON movie_id24 = 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 57952 6870 │ │ │ │ TABLE SCAN movie_info WHERE info = Horror 1274215 3854 │ │ │ TABLE SCAN cast_info WHERE note BETWEEN (head writer) AND (written by) AND note35 IN((head writer),(story editor),story,writer,(written by)) 1778509 1734 │ │ TABLE SCAN name WHERE gender = m 2528312 2528312 │ TABLE SCAN title 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_right) AS a1, MIN(info_left) AS a2, MIN(name) AS a3, MIN(title) AS a4 - 8181261 PROJECT info, info, name, title - 8181261 PROJECT info, info, name, title - 8181261 INNER JOIN HASH ON tuple(PROJECTION_2906.movie_id,PROJECTION_2906.movie_id,PROJECTION_2906.movie_id,PROJECTION_2906.movie_id,PROJECTION_2906.id,PROJECTION_2906.id) = tuple(PROJECTION_2885.movie_id,PROJECTION_2885.movie_id,PROJECTION_2885.movie_id,PROJECTION_2885.movie_id,PROJECTION_2885.movie_id,PROJECTION_2885.movie_id) - 384814 │└PROJECT movie_id_right, movie_id AS movie_id_right_2, info AS info_right, name - 384814 │ PROJECT movie_id, info, movie_id, name - 384814 │ INNER JOIN HASH ON PROJECTION_2891.person_id = PROJECTION_2888.id - 1739579 │ │└PROJECT id, name - 1739579 │ │ PROJECT id, name - 1739579 │ │ TABLE SCAN name WHERE gender = 'm' - 746153 │ PROJECT person_id, movie_id, info, movie_id - 746153 │ PROJECT movie_id, person_id, info, movie_id - 746153 │ INNER JOIN HASH ON PROJECTION_2897.info_type_id = PROJECTION_2894.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_2903.movie_id = PROJECTION_2900.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 - 3461792 PROJECT movie_id AS movie_id_left, movie_id AS movie_id_left_2, id, info AS info_left, title - 3461792 PROJECT info, movie_id, movie_id, title, id - 3461792 INNER JOIN HASH ON tuple(PROJECTION_2930.id,PROJECTION_2930.id) = tuple(PROJECTION_2909.movie_id,PROJECTION_2909.movie_id) - 3461792 │└PROJECT movie_id, movie_id, info - 3461792 │ PROJECT info, movie_id, movie_id - 3461792 │ INNER JOIN HASH ON PROJECTION_2927.id = PROJECTION_2912.keyword_id - 3461792 │ │└PROJECT keyword_id, info, movie_id, movie_id - 3461792 │ │ PROJECT info, movie_id, movie_id, keyword_id - 3461792 │ │ INNER JOIN HASH ON PROJECTION_2924.movie_id = PROJECTION_2915.movie_id - 459925 │ │ │└PROJECT movie_id AS movie_id_right, info - 459925 │ │ │ PROJECT info, movie_id - 459925 │ │ │ INNER JOIN HASH ON PROJECTION_2921.info_type_id = PROJECTION_2918.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 - 4523930 │ │ PROJECT movie_id AS movie_id_left, keyword_id - 4523930 │ │ PROJECT movie_id, keyword_id - 4523930 │ │ TABLE SCAN movie_keyword - 134170 │ PROJECT id - 134170 │ PROJECT id - 134170 │ TABLE SCAN keyword WHERE TRUE - 2528312 PROJECT id, title - 2528312 PROJECT title, id - 2528312 TABLE SCAN title
	Estimate Actual Operator - 1 AGGREGATE MIN(#0), MIN(#1), MIN(#2), MIN(#3) 0 4407 PROJECT info, info, name, title 0 4407 INNER JOIN HASH ON id = person_id 0 7112 │└INNER JOIN HASH ON movie_id = id 0 11389 │ │└INNER JOIN HASH ON id = movie_id 0 11389 │ │ │└INNER JOIN HASH ON id = keyword_id 0 319480 │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 0 16480 │ │ │ │ │└INNER JOIN HASH ON id = info_type_id 0 49452 │ │ │ │ │ │└INNER JOIN HASH ON movie_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' 1380035 54819 │ │ │ │ │ │ TABLE SCAN movie_info_idx 2 1 │ │ │ │ │ FILTER id >= 99 2 1 │ │ │ │ │ TABLE SCAN info_type WHERE info = 'votes' 4523930 341382 │ │ │ │ TABLE SCAN movie_keyword WHERE movie_id <= 2525793 26834 5 │ │ │ FILTER IN ... 134170 134156 │ │ │ INNER JOIN HASH ON keyword = #0 0 5 │ │ │ │└SCAN MATERIALISED 134170 134156 │ │ │ TABLE SCAN keyword WHERE keyword IN('murder','blood','gore','death','female-nudity') 2528312 6697 │ │ TABLE SCAN title WHERE id >= 2 AND id <= 2525793 7248868 3952 │ FILTER movie_id BETWEEN 2 AND 2525793 7248868 3952 │ FILTER IN ... 36244344 265758 │ INNER JOIN HASH ON note = #0 0 5 │ │└SCAN MATERIALISED 36244344 265758 │ TABLE SCAN cast_info WHERE note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 2083746 2216 FILTER id <= 4061926 2083746 2216 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 4407 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))... 2528312 2528312 DISTRIBUTE HASH ON id, id, id, id 2528312 2528312 TABLE SCAN title WHERE 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 <= 2521126))) AND TRUE) WHEN 5 THEN ((((((id >= 560960) A...
	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) 254 4407 INNER JOIN HASH ON ci.movie_id = mk.movie_id 254 62096 │└DISTRIBUTE GATHER 254 62096 │ INNER JOIN HASH ON mk.keyword_id = k.id 254 5 │ │└DISTRIBUTE GATHER 1380000 5 │ │ TABLE SCAN keyword WHERE k.keyword IN('murder','blood','gore','death','female-nudity') 14800000 4519847 │ TABLE SCAN movie_keyword 254 4851 INNER JOIN HASH ON ci.person_id = n.id 254 8650 │└DISTRIBUTE GATHER 19 8650 │ INNER JOIN HASH ON mi.movie_id = ci.movie_id 19 16480 │ │└DISTRIBUTE GATHER 19 16480 │ │ INNER JOIN HASH ON mi_idx.info_type_id = it2.id 19 1 │ │ │└DISTRIBUTE GATHER 4170000 1 │ │ │ TABLE SCAN info_type WHERE it2.info = 'votes' 6 49440 │ │ INNER JOIN HASH ON mi.movie_id = mi_idx.movie_id 6 30413 │ │ │└DISTRIBUTE GATHER 222 30413 │ │ │ INNER JOIN HASH ON mi.movie_id = t.id 222 30413 │ │ │ │└DISTRIBUTE GATHER 211 30413 │ │ │ │ INNER JOIN HASH ON mi.info_type_id = it1.id 211 1 │ │ │ │ │└DISTRIBUTE GATHER 2530000 1 │ │ │ │ │ TABLE SCAN info_type WHERE it1.info = 'genres' 134000 30413 │ │ │ │ TABLE SCAN movie_info WHERE mi.info = 'Horror' 4520000 2520303 │ │ │ TABLE SCAN title 36200000 1375945 │ │ TABLE SCAN movie_info_idx 113 1241916 │ TABLE SCAN cast_info WHERE ci.note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 113 1735486 TABLE SCAN name WHERE (n.gender IS NOT NULL) AND (n.gender = 'm')
	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 4407 INNER JOIN MERGE ON id as id = keyword_id as keyword_id 5 5 │└SORT id 5 5 │ TABLE SCAN keyword AS k WHERE 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' 1168 4407 SORT keyword_id 1168 128590 INNER JOIN LOOP ON Bmk1012 = Bmk1012 1 128590 │└TABLE SEEK movie_keyword AS mk 1168 128590 INNER JOIN LOOP ON t.id = mk.movie_id 18 128590 │└TABLE SEEK movie_keyword AS mk 63 4851 INNER JOIN LOOP ON Bmk1016 = Bmk1016 1 4851 │└TABLE SEEK title AS t 64 4851 INNER JOIN LOOP ON ci.movie_id = t.id 1 4851 │└TABLE SEEK title AS t 63 4851 SORT movie_id 63 4851 FILTER gender as gender = 'm' 154 8650 INNER JOIN LOOP ON Bmk1014 = Bmk1014 1 8650 │└TABLE SEEK name AS n 154 8650 SORT Expr1060 154 8650 PROJECT BmkToPage Bmk1014 AS Expr1060 154 8650 INNER JOIN LOOP ON ci.person_id = n.id 1 8650 │└TABLE SEEK name AS n 154 8650 SORT person_id 154 8650 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)' 5614 548763 INNER JOIN LOOP ON Bmk1000 = Bmk1000 1 548763 │└TABLE SEEK cast_info AS ci 5614 548763 SORT Expr1059 5614 548763 PROJECT BmkToPage Bmk1000 AS Expr1059 5614 548763 INNER JOIN LOOP ON mi_idx.movie_id = ci.movie_id 30 548763 │└TABLE SEEK cast_info AS ci 185 16480 INNER JOIN MERGE ON id as id = info_type_id as info_type_id 1 1 │└FILTER info as info = 'votes' 113 113 │ INNER JOIN LOOP ON Bmk1004 = Bmk1004 1 113 │ │└TABLE SEEK info_type AS it2 113 113 │ TABLE SEEK info_type AS it2 929 16484 SORT info_type_id 929 49452 INNER JOIN LOOP ON mi.movie_id = mi_idx.movie_id 2 49452 │└TABLE SEEK movie_info_idx AS mi_idx 414 30413 INNER JOIN HASH ON mi.info_type_id = it1.id 1 1 │└FILTER info as info = 'genres' 113 113 │ TABLE SCAN info_type AS it1 29003 30413 TABLE SEEK movie_info AS mi WHERE (PROBE(Bitmap1066,info_type_id as info_type_id,N'IN ROW')) AND (info as info = 'Horror')
	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 - 4407 INNER JOIN HASH ON movie_id = id_37 2528312 2528312 │└DISTRIBUTE HASH ON id_37 2528312 2528312 │ PROJECT id AS id_37, title 2528312 2528312 │ TABLE SCAN title - 4407 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 - 7112 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 - 7112 INNER JOIN HASH ON movie_id = movie_id_29 4523930 62096 │└DISTRIBUTE HASH ON movie_id_29 4523930 62096 │ PROJECT movie_id AS movie_id_29, keyword_id 4523930 62096 │ TABLE SCAN movie_keyword - 3541 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 - 3541 INNER JOIN HASH ON movie_id = movie_id_21 1380035 35510 │└DISTRIBUTE HASH ON movie_id_21 1380035 35510 │ PROJECT movie_id AS movie_id_21, info_type_id AS info_type_id_22, info AS info_23 1380035 35510 │ TABLE SCAN movie_info_idx - 3541 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 - 3541 INNER JOIN HASH ON movie_id = movie_id_14 13352148 5837 │└DISTRIBUTE HASH ON movie_id_14 13352148 5837 │ PROJECT movie_id AS movie_id_14, info_type_id, info AS info_15 13352148 5837 │ FILTER info = 'Horror' 13352148 5837 │ TABLE SCAN movie_info 32619910 3525 FILTER note IN('(head writer)','(story editor)','(story)','(writer)','(written by)') 32619910 3525 TABLE SCAN cast_info
	Estimate Actual Operator 1 1 AGGREGATE MIN(info), MIN(info), MIN(name), MIN(title) 1 4407 INNER JOIN LOOP ON id = movie_id AND movie_id = id AND (movie_id = id) 1 4407 │└INNER JOIN LOOP ON id = person_id 1 7112 │ │└INNER JOIN LOOP ON id = info_type_id 1 7740 │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = movie_id AND (movie_id = movie_id) 1 12260 │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = movie_id AND (movie_id = movie_id) 4 50760 │ │ │ │ │└INNER JOIN HASH ON info_type_id = id 1 1 │ │ │ │ │ │└TABLE SEEK info_type AS it2 491 152720 │ │ │ │ │ INNER JOIN LOOP ON movie_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 186288 152756 │ │ │ │ │ TABLE SEEK movie_info_idx AS mi_idx 50760 50760 │ │ │ │ TABLE SEEK movie_info AS mi WHERE mi.info = 'Horror' 12260 12260 │ │ │ TABLE SEEK cast_info AS ci WHERE ci.note IN('(writer)','(head writer)','(written by)','(story)','(story editor)') 7740 7740 │ │ TABLE SEEK info_type AS it1 WHERE it1.info = 'genres' 7112 7112 │ TABLE SEEK name AS n WHERE n.gender = 'm' 4407 4407 TABLE SEEK title AS t