Planner — IMDB — JOB-29C

SELECT MIN(chn.name) AS voiced_char,
       MIN(n.name) AS voicing_actress,
       MIN(t.title) AS voiced_animation
FROM job.aka_name AS an,
     job.complete_cast AS cc,
     job.comp_cast_type AS cct1,
     job.comp_cast_type AS cct2,
     job.char_name AS chn,
     job.cast_info AS ci,
     job.company_name AS cn,
     job.info_type AS it,
     job.info_type AS it3,
     job.keyword AS k,
     job.movie_companies AS mc,
     job.movie_info AS mi,
     job.movie_keyword AS mk,
     job.name AS n,
     job.person_info AS pi,
     job.role_type AS rt,
     job.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;

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 14,139,183 14M Rank		Estimation Error Est Err 14,188,183 14M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 205,615 206K Rank	Estimation Error Est Err 16,308 16K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 52,061,756 52M Rank		Estimation Error Est Err 0 Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 0 Rank	Estimation Error Est Err 0 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 16,322,399 16M Rank		Estimation Error Est Err 16,154,335 16M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 4,396,396 4.4M Rank	Estimation Error Est Err 271,961 272K Rank	Estimation Error Est Err 2,674,659 2.7M Rank
Estimation Error Est Err 27,165,689 27M Rank		Estimation Error Est Err 15,248,673 15M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 7,103,179 7.1M Rank	Estimation Error Est Err 16,318 16K Rank	Estimation Error Est Err 4,964,160 5M Rank
Estimation Error Est Err 6,916 6.9K Rank		Estimation Error Est Err 121,929 122K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 185,672 186K Rank	Estimation Error Est Err 16,308 16K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 79,196 79K Rank	Estimation Error Est Err 79,196 79K Rank	Estimation Error Est Err 79,199 79K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 79,199 79K Rank	Estimation Error Est Err 16,308 16K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 213,431 213K Rank	Estimation Error Est Err 213,426 213K Rank	Estimation Error Est Err 309,239 309K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 236,979 237K Rank	Estimation Error Est Err 22,402 22K Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 4,896,559 4.9M Rank		Estimation Error Est Err 66,738 67K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 4,929,724 4.9M Rank	Estimation Error Est Err 16,324 16K Rank	Estimation Error Est Err 4,896,570 4.9M Rank

Actual Query Plans

Query Plan per Engine ?
	Query Plan
	Estimate Actual Operator 1 1 AGGREGATE min, min, min 1 16308 INNER JOIN HASH ON id = info_type_id 1 1 │└TABLE SCAN info_type WHERE info = release dates 1 16308 INNER JOIN HASH ON id127 = person_role_id 1 16308 │└INNER JOIN HASH ON id117 = company_id 1 75240 │ │└INNER JOIN HASH ON id38 = movie_id110 1 2868 │ │ │└INNER JOIN HASH ON id6 = subject_id 1 1 │ │ │ │└TABLE SCAN comp_cast_type WHERE kind = cast 1 2868 │ │ │ INNER JOIN HASH ON id11 = info_type_id103 1 1 │ │ │ │└TABLE SCAN info_type WHERE info = trivia 3 12279 │ │ │ INNER JOIN HASH ON person_id102 = person_id91 1 33 │ │ │ │└INNER JOIN HASH ON id78 = person_id91 1 8 │ │ │ │ │└INNER JOIN HASH ON id16 = status_id 1 1 │ │ │ │ │ │└TABLE SCAN comp_cast_type WHERE kind = complete + verified 1 8 │ │ │ │ │ INNER JOIN HASH ON id21 = role_id 1 1 │ │ │ │ │ │└TABLE SCAN role_type WHERE role = actress 1 8 │ │ │ │ │ INNER JOIN HASH ON id78 = person_id 1 1655 │ │ │ │ │ │└INNER JOIN HASH ON movie_id70 = id38 4 68 │ │ │ │ │ │ │└INNER JOIN HASH ON movie_id61 = id38 3 19 │ │ │ │ │ │ │ │└INNER JOIN HASH ON id38 = movie_id54 14 249 │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id38 = movie_id 32 414 │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id26 = keyword_id 1 1 │ │ │ │ │ │ │ │ │ │ │└TABLE SCAN keyword WHERE keyword = computer - animation 4523930 4523930 │ │ │ │ │ │ │ │ │ │ TABLE SCAN movie_keyword 1081445 249 │ │ │ │ │ │ │ │ │ TABLE SCAN title WHERE production_year BETWEEN 2000 AND 2010 38175 19 │ │ │ │ │ │ │ │ TABLE SCAN complete_cast 376688 61 │ │ │ │ │ │ │ TABLE SCAN movie_info WHERE info63 LIKE '%200%' 408889 429 │ │ │ │ │ │ TABLE SCAN cast_info WHERE note72 IN(voice,voice uncredited,(voice : English version),(voice : Japanese version)) 61047 3 │ │ │ │ │ TABLE SCAN name WHERE gender = f AND name LIKE '%An%' 901343 901343 │ │ │ │ TABLE SCAN aka_name 2963664 2963664 │ │ │ TABLE SCAN person_info 2609129 2609129 │ │ TABLE SCAN movie_companies 90648 11 │ TABLE SCAN company_name WHERE country_code = us 3140339 3140339 TABLE SCAN char_name
	Estimate Actual Operator - ∞ PROJECT a1 AS voiced_char, a2 AS voicing_actress, a3 AS voiced_animation - ∞ AGGREGATE MIN(name_left) AS a1, MIN(name_right) AS a2, MIN(title) AS a3 - ∞ PROJECT name_left, name_right, title - ∞ PROJECT name_left, name_right, title - ∞ INNER JOIN HASH ON tuple(PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id,PROJECTION_3969.movie_id) = tuple(PROJECTION_3954.movie_id,PROJECTION_3954.movie_id,PROJECTION_3954.movie_id,PROJECTION_3954.movie_id,PROJECTION_3954.id,PROJECTION_3954.id,PROJECTION_3954.id,PROJECTION_3954.id) - 249 │└PROJECT movie_id AS movie_id_right, id, title - 249 │ PROJECT movie_id, title, id - 249 │ INNER JOIN HASH ON PROJECTION_3966.id = PROJECTION_3957.movie_id - 414 │ │└PROJECT movie_id - 414 │ │ PROJECT movie_id - 414 │ │ INNER JOIN HASH ON PROJECTION_3963.keyword_id = PROJECTION_3960.id - 1 │ │ │└PROJECT id - 1 │ │ │ FILTER (1 AND keyword = 'computer-animation'_String) AS a81 - 1 │ │ │ TABLE SCAN keyword WHERE keyword = 'computer-animation' - 4523930 │ │ PROJECT keyword_id, movie_id - 4523930 │ │ PROJECT movie_id, keyword_id - 4523930 │ │ TABLE SCAN movie_keyword - 1042800 │ PROJECT id, title - 1042800 │ FILTER (1 AND production_year >= 2000_UInt16 AND production_year <= 2010_UInt16) AS a72 - 1042800 │ TABLE SCAN title WHERE (production_year >= 2000) AND (production_year <= 2010) - ∞ PROJECT movie_id_left, movie_id_left_2, movie_id_left_3, movie_id_right AS movie_id_left_4, name, name - ∞ PROJECT movie_id_left_2, movie_id_left, name, movie_id_left_3, movie_id_right, name - ∞ INNER JOIN HASH ON tuple(PROJECTION_3987.person_id,PROJECTION_3987.person_id,PROJECTION_3987.person_id) = tuple(PROJECTION_3972.id,PROJECTION_3972.id,PROJECTION_3972.person_id) - ∞ │└PROJECT id, person_id AS person_id_right, name AS name_right - ∞ │ PROJECT name, id, person_id - ∞ │ INNER JOIN HASH ON PROJECTION_3978.info_type_id = PROJECTION_3975.id - 1 │ │└PROJECT id AS id_right - 1 │ │ FILTER (1 AND info = 'trivia'_String) AS a67 - 1 │ │ TABLE SCAN info_type WHERE info = 'trivia' - ∞ │ PROJECT info_type_id, name, id AS id_left, person_id - ∞ │ PROJECT name, id, person_id, info_type_id - ∞ │ INNER JOIN HASH ON PROJECTION_3984.id = PROJECTION_3981.person_id - 2963664 │ │└PROJECT person_id, info_type_id - 2963664 │ │ PROJECT person_id, info_type_id - 2963664 │ │ TABLE SCAN person_info - ∞ │ PROJECT id, name - ∞ │ FILTER (1 AND LIKE (name,'%An%'_String) AND gender = 'f'_String) AS a59 - 50011 │ TABLE SCAN name WHERE (gender = 'f') AND name LIKE '%An%' - ∞ PROJECT person_id AS person_id_left, person_id AS person_id_left_2, movie_id, movie_id, name AS name_left, movie_id, movie_id - ∞ PROJECT person_id, person_id, movie_id, movie_id, name, movie_id, movie_id - ∞ INNER JOIN HASH ON PROJECTION_3993.role_id = PROJECTION_3990.id - 1 │└PROJECT id - 1 │ FILTER (1 AND role = 'actress'_String) AS a53 - 1 │ TABLE SCAN role_type WHERE role = 'actress' - ∞ PROJECT role_id, person_id, person_id, movie_id, movie_id, name, movie_id, movie_id - ∞ PROJECT person_id, person_id, movie_id, role_id, movie_id, name, movie_id, movie_id - ∞ INNER JOIN HASH ON PROJECTION_3999.info_type_id = PROJECTION_3996.id - 1 │└PROJECT id - 1 │ FILTER (1 AND info = 'release dates'_String) AS a49 - 1 │ TABLE SCAN info_type WHERE info = 'release dates' - ∞ PROJECT info_type_id, person_id, person_id, movie_id, role_id, movie_id, name, movie_id, movie_id - ∞ PROJECT person_id, person_id, movie_id, role_id, movie_id, name, movie_id, movie_id, info_type_id - ∞ INNER JOIN HASH ON tuple(PROJECTION_4005.movie_id,PROJECTION_4005.movie_id,PROJECTION_4005.movie_id) = tuple(PROJECTION_4002.movie_id,PROJECTION_4002.movie_id,PROJECTION_4002.movie_id) - ∞ │└PROJECT movie_id AS movie_id_right, info_type_id - ∞ │ FILTER (1 AND OR ( LIKE (info,'Japan:%200%'_String), LIKE (info,'USA:%200%'_String))) AS a41 - 451104 │ TABLE SCAN movie_info WHERE info LIKE 'Japan:%200%' OR info LIKE 'USA:%200%' - ∞ PROJECT movie_id AS movie_id_left, movie_id AS movie_id_left_2, movie_id AS movie_id_left_3, person_id, person_id, role_id, name - ∞ PROJECT person_id, person_id, movie_id, role_id, movie_id, name, movie_id - ∞ INNER JOIN HASH ON PROJECTION_4047.id = PROJECTION_4008.company_id - ∞ │└PROJECT company_id, person_id, person_id, movie_id, role_id, movie_id, name, movie_id - ∞ │ PROJECT person_id, person_id, movie_id, role_id, movie_id, name, movie_id, company_id - ∞ │ INNER JOIN HASH ON tuple(PROJECTION_4044.movie_id,PROJECTION_4044.movie_id) = tuple(PROJECTION_4011.movie_id,PROJECTION_4011.movie_id) - ∞ │ │└PROJECT movie_id_right, movie_id AS movie_id_right_2, person_id, person_id, role_id, name - ∞ │ │ PROJECT person_id, person_id, movie_id, role_id, movie_id, name - ∞ │ │ INNER JOIN HASH ON PROJECTION_4041.id = PROJECTION_4014.person_role_id - ∞ │ │ │└PROJECT person_role_id, person_id, person_id, movie_id, role_id, movie_id - ∞ │ │ │ PROJECT person_id, person_id, movie_id, person_role_id, role_id, movie_id - ∞ │ │ │ INNER JOIN HASH ON PROJECTION_4038.person_id = PROJECTION_4017.person_id - ∞ │ │ │ │└PROJECT person_id AS person_id_right, movie_id, person_role_id, role_id, movie_id - ∞ │ │ │ │ PROJECT person_id, movie_id, person_role_id, role_id, movie_id - ∞ │ │ │ │ INNER JOIN HASH ON PROJECTION_4035.movie_id = PROJECTION_4020.movie_id - 17879 │ │ │ │ │└PROJECT movie_id AS movie_id_right - 17879 │ │ │ │ │ PROJECT movie_id - 17879 │ │ │ │ │ INNER JOIN HASH ON PROJECTION_4026.status_id = PROJECTION_4023.id - 1 │ │ │ │ │ │└PROJECT id - 1 │ │ │ │ │ │ FILTER (1 AND kind = 'complete+verified'_String) AS a37 - 1 │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'complete+verified' - 85941 │ │ │ │ │ PROJECT status_id, movie_id - 85941 │ │ │ │ │ PROJECT movie_id, status_id - 85941 │ │ │ │ │ INNER JOIN HASH ON PROJECTION_4032.subject_id = PROJECTION_4029.id - 1 │ │ │ │ │ │└PROJECT id - 1 │ │ │ │ │ │ FILTER (1 AND kind = 'cast'_String) AS a33 - 1 │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'cast' - 135086 │ │ │ │ │ PROJECT subject_id, movie_id, status_id - 135086 │ │ │ │ │ PROJECT movie_id, subject_id, status_id - 135086 │ │ │ │ │ TABLE SCAN complete_cast - ∞ │ │ │ │ PROJECT movie_id AS movie_id_left, person_id, person_role_id, role_id - ∞ │ │ │ │ FILTER (in(note,__set_String_6680244196204786103_17565861716447275384) AND 1) AS a27 - 36244344 │ │ │ │ TABLE SCAN cast_info WHERE TRUE - 901343 │ │ │ PROJECT person_id AS person_id_left - 901343 │ │ │ PROJECT person_id - 901343 │ │ │ TABLE SCAN aka_name - 3140339 │ │ PROJECT id, name - 3140339 │ │ PROJECT name, id - 3140339 │ │ TABLE SCAN char_name - 2609129 │ PROJECT movie_id AS movie_id_left, company_id - 2609129 │ PROJECT movie_id, company_id - 2609129 │ TABLE SCAN movie_companies - 0 PROJECT id - 0 FILTER (1 AND country_code = 'us'_String) AS a17 - 0 TABLE SCAN company_name WHERE country_code = 'us'
	Estimate Actual Operator - 1 AGGREGATE MIN(#0), MIN(#1), MIN(#2) 0 16308 PROJECT name, name, title 0 16308 INNER JOIN HASH ON id = person_role_id 0 16740 │└INNER JOIN HASH ON id = info_type_id 0 69744 │ │└INNER JOIN HASH ON person_id = id 0 216 │ │ │└INNER JOIN HASH ON id = person_id 0 4490 │ │ │ │└INNER JOIN HASH ON person_id = person_id 0 2088 │ │ │ │ │└INNER JOIN HASH ON id = role_id 0 8963 │ │ │ │ │ │└INNER JOIN HASH ON movie_id = id 0 337 │ │ │ │ │ │ │└INNER JOIN HASH ON id = info_type_id 0 337 │ │ │ │ │ │ │ │└INNER JOIN HASH ON movie_id = id 0 92 │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id = company_id 0 415 │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON movie_id = id 0 18 │ │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id = status_id 0 55 │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id = subject_id 0 61 │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON id = movie_id 3 90 │ │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 69 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN HASH ON keyword_id = id 2 1 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │└TABLE SCAN keyword WHERE keyword = 'computer-animation' 4523930 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ FILTER movie_id <= 2525745 4523930 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SCAN movie_keyword WHERE movie_id >= 285 135086 421 │ │ │ │ │ │ │ │ │ │ │ │ │ │ FILTER movie_id <= 2525745 135086 421 │ │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SCAN complete_cast WHERE movie_id <= 2525971 505662 1291 │ │ │ │ │ │ │ │ │ │ │ │ │ FILTER id BETWEEN 285 AND 2525745 505662 1291 │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SCAN title WHERE production_year >= 2000 AND production_year <= 2010 1 1 │ │ │ │ │ │ │ │ │ │ │ │ FILTER id <= 2 1 1 │ │ │ │ │ │ │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'cast' 1 1 │ │ │ │ │ │ │ │ │ │ │ FILTER id >= 3 1 1 │ │ │ │ │ │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'complete+verified' 2609129 415 │ │ │ │ │ │ │ │ │ │ TABLE SCAN movie_companies WHERE movie_id >= 285 1644 80 │ │ │ │ │ │ │ │ │ TABLE SCAN company_name WHERE country_code = 'us' 2967144 76 │ │ │ │ │ │ │ │ FILTER movie_id BETWEEN 285 AND 2525745 2967144 76 │ │ │ │ │ │ │ │ TABLE SCAN movie_info WHERE (info IS NOT NULL) AND ((info LIKE 'Japan:%200%') OR (info LIKE 'USA:%200%')) 2 1 │ │ │ │ │ │ │ FILTER id <= 110 2 1 │ │ │ │ │ │ │ TABLE SCAN info_type WHERE info = 'release dates' 7248868 541 │ │ │ │ │ │ FILTER (person_id >= 4) AND (movie_id BETWEEN 285 AND 2525745) 7248868 541 │ │ │ │ │ │ FILTER (note = '(voice)') OR (note = '(voice: Japanese version)') OR (note = '(voice) (uncredited)') OR (note = '(voice: English version)') 36244344 2948 │ │ │ │ │ │ TABLE SCAN cast_info WHERE note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)') 1 1 │ │ │ │ │ FILTER id <= 11 1 1 │ │ │ │ │ TABLE SCAN role_type WHERE role = 'actress' 901343 217 │ │ │ │ TABLE SCAN aka_name WHERE person_id <= 4061926 2083746 4 │ │ │ FILTER id BETWEEN 4 AND 4061926 2083746 4 │ │ │ TABLE SCAN "name" WHERE gender = 'f' AND contains(name,'An') 2963664 1041 │ │ TABLE SCAN person_info WHERE person_id <= 4061926 2 1 │ FILTER id BETWEEN 15 AND 39 2 1 │ TABLE SCAN info_type WHERE info = 'trivia' 3140339 3 TABLE SCAN char_name
	Estimate Actual Operator 1 1 PROJECT voiced_char, voicing_actress, voiced_animation 1 1 AGGREGATE MIN(name), MIN(name), MIN(title) 3849 10 DISTRIBUTE GATHER 3849 10 AGGREGATE MIN(name), MIN(name), MIN(title) 3849 16308 INNER JOIN HASH ON movie_id = id AND movie_id = id AND movie_id = id AND movie_id = id AND movie_id = id 3849 16368 │└DISTRIBUTE GATHER 3849 16368 │ INNER JOIN HASH ON id = role_id 3 1 │ │└DISTRIBUTE GATHER 3 1 │ │ FILTER role = 'actress' 12 12 │ │ DISTRIBUTE ROUND ROBIN 12 12 │ │ TABLE SCAN role_type WHERE role = 'actress' 14113 16368 │ INNER JOIN HASH ON id = info_type_id 23 1 │ │└DISTRIBUTE GATHER 23 1 │ │ FILTER info = 'trivia' 113 113 │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ TABLE SCAN info_type WHERE info = 'trivia' 15341 68232 │ INNER JOIN HASH ON id = person_id AND person_id = person_id 15341 204 │ │└DISTRIBUTE GATHER 15341 204 │ │ INNER JOIN HASH ON person_id = id AND person_id = id 15341 4191 │ │ │└DISTRIBUTE GATHER 15341 4191 │ │ │ INNER JOIN HASH ON keyword_id = id 15341 2894735 │ │ │ │└DISTRIBUTE GATHER 15341 2894735 │ │ │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id AND movie_id = movie_id AND movie_id = movie_id 8566 24509 │ │ │ │ │└DISTRIBUTE GATHER 8566 24509 │ │ │ │ │ INNER JOIN HASH ON id = info_type_id 23 1 │ │ │ │ │ │└DISTRIBUTE GATHER 23 1 │ │ │ │ │ │ FILTER info = 'release dates' 113 113 │ │ │ │ │ │ DISTRIBUTE ROUND ROBIN 113 113 │ │ │ │ │ │ TABLE SCAN info_type WHERE info = 'release dates' 40970 24509 │ │ │ │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id AND movie_id = movie_id 34885 14994 │ │ │ │ │ │└DISTRIBUTE GATHER 34885 14994 │ │ │ │ │ │ INNER JOIN HASH ON company_id = id 34885 46526 │ │ │ │ │ │ │└DISTRIBUTE GATHER 34885 46526 │ │ │ │ │ │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id 33771 2444 │ │ │ │ │ │ │ │└DISTRIBUTE GATHER 33771 2444 │ │ │ │ │ │ │ │ INNER JOIN HASH ON person_role_id = id 33771 2737 │ │ │ │ │ │ │ │ │└DISTRIBUTE GATHER 33771 2737 │ │ │ │ │ │ │ │ │ INNER JOIN HASH ON id = status_id 1 1 │ │ │ │ │ │ │ │ │ │└DISTRIBUTE GATHER 1 1 │ │ │ │ │ │ │ │ │ │ FILTER kind = 'complete+verified' 4 4 │ │ │ │ │ │ │ │ │ │ DISTRIBUTE ROUND ROBIN 4 4 │ │ │ │ │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'complete+verified' 67543 20415 │ │ │ │ │ │ │ │ │ INNER JOIN HASH ON id = subject_id 1 1 │ │ │ │ │ │ │ │ │ │└DISTRIBUTE GATHER 1 1 │ │ │ │ │ │ │ │ │ │ FILTER kind = 'cast' 4 4 │ │ │ │ │ │ │ │ │ │ DISTRIBUTE ROUND ROBIN 4 4 │ │ │ │ │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE kind = 'cast' 135086 28521 │ │ │ │ │ │ │ │ │ PROJECT person_id, person_id, movie_id, person_role_id, role_id, movie_id, subject_id, status_id 135086 28521 │ │ │ │ │ │ │ │ │ INNER JOIN HASH ON movie_id = movie_id 135086 122880 │ │ │ │ │ │ │ │ │ │└DISTRIBUTE HASH ON movie_id 135086 122880 │ │ │ │ │ │ │ │ │ │ TABLE SCAN complete_cast WHERE (((subject_id >= 1) AND (subject_id <= 1)) AND subject_id IN 1) AND (((status_id >= 4) AND (status_id <= 4)) AND status_id IN 4) 1608526 517803 │ │ │ │ │ │ │ │ │ DISTRIBUTE HASH ON movie_id 1608526 517803 │ │ │ │ │ │ │ │ │ INNER JOIN HASH ON person_id = person_id 901343 901343 │ │ │ │ │ │ │ │ │ │└DISTRIBUTE HASH ON person_id 901343 901343 │ │ │ │ │ │ │ │ │ │ TABLE SCAN aka_name 7248869 280995 │ │ │ │ │ │ │ │ │ DISTRIBUTE HASH ON person_id 7248869 280995 │ │ │ │ │ │ │ │ │ FILTER note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)') 36244344 7656546 │ │ │ │ │ │ │ │ │ TABLE SCAN cast_info WHERE ((note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)') AND CASE MOD(HASH_REPARTITION person_id,10) WHEN 0 THEN (((person_id >= 5) AND (person_id <= 4167489)) AND TRUE) WHEN 1 THEN (((person_id >= 15) AND (person_id <= 4167473)) AND TRUE) WHEN 2 THEN (((person_id >= 69) AND (person_id <= 4167478)) AND TRUE) WHEN 3 THEN (((person_id >= 161) AND (person_id <= 4167352)) A... 3140339 3140339 │ │ │ │ │ │ │ │ TABLE SCAN char_name WHERE ((id >= 21) AND (id <= 3129993)) AND TRUE 2609129 2609129 │ │ │ │ │ │ │ TABLE SCAN movie_companies WHERE (((movie_id >= 34050) AND (movie_id <= 2524105)) AND ((movie_id >= 34050) AND (movie_id <= 2524105))) AND TRUE 47000 84843 │ │ │ │ │ │ FILTER country_code = 'us' 234997 234997 │ │ │ │ │ │ TABLE SCAN company_name WHERE (country_code = 'us') AND (((id >= 5) AND (id <= 234478)) AND TRUE) 2967144 451039 │ │ │ │ │ FILTER info IS NOT NULL AND (info LIKE 'Japan:%200%' OR info LIKE 'USA:%200%') 14835720 3212639 │ │ │ │ │ TABLE SCAN movie_info WHERE ((info IS NOT NULL AND (info LIKE 'Japan:%200%' OR info LIKE 'USA:%200%')) AND (((((movie_id >= 34050) AND (movie_id <= 2524105)) AND ((movie_id >= 34050) AND (movie_id <= 2524105))) AND ((movie_id >= 34050) AND (movie_id <= 2524105))) AND TRUE)) AND (((info_type_id >= 16) AND (info_type_id <= 16)) AND info_type_id IN 16) 4523930 4523930 │ │ │ │ TABLE SCAN movie_keyword WHERE (((((movie_id >= 96313) AND (movie_id <= 2524105)) AND ((movie_id >= 96313) AND (movie_id <= 2524105))) AND ((movie_id >= 96313) AND (movie_id <= 2524105))) AND ((movie_id >= 96313) AND (movie_id <= 2524105))) AND TRUE 26834 1 │ │ │ FILTER keyword = 'computer-animation' 134170 134170 │ │ │ DISTRIBUTE ROUND ROBIN 134170 134170 │ │ │ TABLE SCAN keyword WHERE (keyword = 'computer-animation') AND (((id >= 1) AND (id <= 132531)) AND TRUE) 833499 50011 │ │ FILTER (gender = 'f') AND name LIKE '%An%' 4167491 983636 │ │ TABLE SCAN name WHERE ((gender = 'f') AND name LIKE '%An%') AND ((((id >= 293010) AND (id <= 2694909)) AND ((id >= 293010) AND (id <= 2694909))) AND struct(id,id) IN( < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < exp... 2963664 2963664 │ TABLE SCAN person_info WHERE ((((person_id >= 1763943) AND (person_id <= 2430857)) AND ((person_id >= 1763943) AND (person_id <= 2430857))) AND struct(person_id,person_id) IN( < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , ... 198654 227876 FILTER (production_year >= 2000) AND (production_year <= 2010) 2528312 682170 TABLE SCAN title WHERE ((production_year >= 2000) AND (production_year <= 2010)) AND (((((((id >= 1957163) AND (id <= 2445635)) AND ((id >= 1957163) AND (id <= 2445635))) AND ((id >= 1957163) AND (id <= 2445635))) AND ((id >= 1957163) AND (id <= 2445635))) AND ((id >= 1957163) AND (id <= 2445635))) AND TRUE)
	Estimate Actual Operator 142 0 SEQUENCE 1 1 ├─AGGREGATE MIN(chn.name), MIN(n.name), MIN(t.title) 1 2 │ DISTRIBUTE GATHER 1 2 │ AGGREGATE MIN(chn.name), MIN(n.name), MIN(t.title) 29900 16308 │ INNER JOIN HASH ON ci.movie_id = t.id 29900 1042800 │ │└DISTRIBUTE GATHER 36200000 1042800 │ │ TABLE SCAN title WHERE (t.production_year IS NOT NULL) AND (t.production_year >= 2000L) AND (t.production_year <= 2010L) 28500 16368 │ INNER JOIN HASH ON n.id = pi.person_id 28500 620526 │ │└DISTRIBUTE GATHER 5350 620526 │ │ INNER JOIN HASH ON pi.info_type_id = it3.id 5350 1 │ │ │└DISTRIBUTE GATHER 4 1 │ │ │ TABLE SCAN info_type WHERE it3.info = 'trivia' 135000 2957199 │ │ TABLE SCAN person_info 28500 204 │ INNER JOIN HASH ON ci.person_id = n.id 28500 4191 │ │└DISTRIBUTE GATHER 5350 4191 │ │ INNER JOIN HASH ON mc.movie_id = mk.movie_id 5350 414 │ │ │└DISTRIBUTE GATHER 5350 414 │ │ │ INNER JOIN HASH ON mk.keyword_id = k.id 5350 1 │ │ │ │└DISTRIBUTE GATHER 235000 1 │ │ │ │ TABLE SCAN keyword WHERE k.keyword = 'computer-animation' 3140000 4503451 │ │ │ TABLE SCAN movie_keyword 5350 24426 │ │ INNER JOIN HASH ON mi.info_type_id = it.id 5350 1 │ │ │└DISTRIBUTE GATHER 2610000 1 │ │ │ TABLE SCAN info_type WHERE it.info = 'release dates' 849 24426 │ │ INNER JOIN HASH ON mc.movie_id = mi.movie_id 849 14965 │ │ │└DISTRIBUTE GATHER 332 14965 │ │ │ INNER JOIN HASH ON ci.movie_id = mc.movie_id 332 2436 │ │ │ │└DISTRIBUTE GATHER 332 2436 │ │ │ │ INNER JOIN HASH ON ci.person_role_id = chn.id 332 2436 │ │ │ │ │└DISTRIBUTE GATHER 332 2436 │ │ │ │ │ INNER JOIN HASH ON cc.status_id = cct2.id 332 1 │ │ │ │ │ │└DISTRIBUTE GATHER 4170000 1 │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE cct2.kind = 'complete+verified' 226 18889 │ │ │ │ │ INNER JOIN HASH ON cc.subject_id = cct1.id 226 1 │ │ │ │ │ │└DISTRIBUTE GATHER 2960000 1 │ │ │ │ │ │ TABLE SCAN comp_cast_type WHERE cct1.kind = 'cast' 12100 29582 │ │ │ │ │ INNER JOIN HASH ON ci.movie_id = cc.movie_id 12100 135086 │ │ │ │ │ │└DISTRIBUTE GATHER 113 135086 │ │ │ │ │ │ TABLE SCAN complete_cast WHERE cc.movie_id IS NOT NULL 71 483319 │ │ │ │ │ INNER JOIN HASH ON an.person_id = ci.person_id 71 255651 │ │ │ │ │ │└DISTRIBUTE GATHER 135000 255651 │ │ │ │ │ │ INNER JOIN HASH ON ci.role_id = rt.id 135000 1 │ │ │ │ │ │ │└DISTRIBUTE GATHER - 1 │ │ │ │ │ │ │ TABLE SCAN role_type WHERE rt.role = 'actress' 2530000 255651 │ │ │ │ │ │ TABLE SCAN cast_info WHERE (ci.note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)')) AND (ci.person_role_id IS NOT NULL) 12 897302 │ │ │ │ │ TABLE SCAN aka_name 4520000 3132154 │ │ │ │ TABLE SCAN char_name 332 1142114 │ │ │ INNER JOIN HASH ON mc.company_id = cn.id 332 84843 │ │ │ │└DISTRIBUTE GATHER 134000 84843 │ │ │ │ TABLE SCAN company_name WHERE (cn.country_code IS NOT NULL) AND (cn.country_code = 'us') 113 2584557 │ │ │ TABLE SCAN movie_companies 135000 29376 │ │ FILTER 14800000 434546 │ │ TABLE SCAN movie_info WHERE mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%' 4 39153 │ TABLE SCAN name WHERE (n.gender IS NOT NULL) AND (n.gender = 'f') AND contains(n.name,'An') 142 0 └─FILTER 28500 1 DISTRIBUTE HASH 28500 1 AGGREGATE bloom_filter_agg(bloom_expr(ci.movie_id,ci.movie_id),255651L,2097152L) 901000 255651 DISTRIBUTE HASH 901000 255651 DISTRIBUTE HASH 901000 255651 TABLE SCAN cast_info WHERE (ci.note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)')) AND (ci.person_role_id IS NOT NULL)
	Estimate Actual Operator 1 1 AGGREGATE MIN(name as name) AS Expr1034, MIN(name as name) AS Expr1035, MIN(title as title) AS Expr1036 1 22402 INNER JOIN LOOP ON Bmk1008 = Bmk1008 1 22402 │└TABLE SEEK char_name AS chn 1 22402 PROJECT BmkToPage Bmk1008 AS Expr1158 1 22402 INNER JOIN LOOP ON ci.person_role_id = chn.id 1 22402 │└TABLE SEEK char_name AS chn 15 23444 INNER JOIN HASH ON pi.info_type_id = it3.id 1 1 │└TABLE SCAN info_type AS it3 WHERE info as info = 'trivia' 33 23444 INNER JOIN LOOP ON Bmk1028 = Bmk1028 1 23444 │└TABLE SEEK person_info AS pi WHERE BLOOM(info_type_id as info_type_id) 330 94229 PROJECT BmkToPage Bmk1028 AS Expr1156 330 94229 INNER JOIN LOOP ON n.id = pi.person_id 46 94229 │└TABLE SEEK person_info AS pi 7 1321 FILTER country_code as country_code = 'us' 19 5994 INNER JOIN LOOP ON Bmk1012 = Bmk1012 1 5994 │└TABLE SEEK company_name AS cn 19 5994 INNER JOIN LOOP ON mc.company_id = cn.id 1 5994 │└TABLE SEEK company_name AS cn 19 5994 INNER JOIN LOOP ON Bmk1020 = Bmk1020 1 5994 │└TABLE SEEK movie_companies AS mc 19 5994 PROJECT BmkToPage Bmk1020 AS Expr1155 19 5994 INNER JOIN LOOP ON t.id = mc.movie_id 9 5994 │└TABLE SEEK movie_companies AS mc 1 247 INNER JOIN LOOP ON Bmk1032 = Bmk1032 0 247 │└TABLE SEEK title AS t WHERE production_year as production_year >= 2000 AND production_year as production_year <= 2010 4 289 PROJECT BmkToPage Bmk1032 AS Expr1154 4 289 INNER JOIN LOOP ON mk.movie_id = t.id 1 289 │└TABLE SEEK title AS t 4 289 INNER JOIN LOOP ON n.id = an.person_id 4 289 │└TABLE SEEK aka_name AS an 1 126 FILTER name as name LIKE '%An%' AND gender as gender = 'f' 1 437 INNER JOIN LOOP ON Bmk1026 = Bmk1026 1 437 │└TABLE SEEK name AS n 1 437 PROJECT BmkToPage Bmk1026 AS Expr1153 1 437 INNER JOIN LOOP ON ci.person_id = n.id 1 437 │└TABLE SEEK name AS n 1 437 FILTER role as role = 'actress' 1 1879 INNER JOIN LOOP ON Bmk1030 = Bmk1030 1 1879 │└TABLE SEEK role_type AS rt 1 1879 INNER JOIN LOOP ON ci.role_id = rt.id 1 1879 │└TABLE SEEK role_type AS rt 1 1879 FILTER note as note = '(voice)' OR note as note = '(voice) (uncredited)' OR note as note = '(voice: English version)' OR note as note = '(voice: Japanese version)' 30 10256 INNER JOIN LOOP ON Bmk1010 = Bmk1010 1 10256 │└TABLE SEEK cast_info AS ci 30 10256 PROJECT BmkToPage Bmk1010 AS Expr1151 30 10256 INNER JOIN LOOP ON mk.movie_id = ci.movie_id 30 10256 │└TABLE SEEK cast_info AS ci 1 63 INNER JOIN HASH ON mi.info_type_id = it.id 1 1 │└TABLE SCAN info_type AS it WHERE info as info = 'release dates' 1 63 INNER JOIN LOOP ON mk.movie_id = mi.movie_id 1 63 │└TABLE SEEK movie_info AS mi WHERE (info as info LIKE 'Japan:%200%' OR info as info LIKE 'USA:%200%') AND BLOOM(info_type_id as info_type_id) 32 23 INNER JOIN HASH ON cc.subject_id = cct1.id 1 1 │└TABLE SCAN comp_cast_type AS cct1 WHERE kind as kind = 'cast' 65 23 INNER JOIN HASH ON cc.status_id = cct2.id 1 1 │└TABLE SCAN comp_cast_type AS cct2 WHERE kind as kind = 'complete+verified' 131 23 INNER JOIN LOOP ON Bmk1002 = Bmk1002 1 23 │└TABLE SEEK complete_cast AS cc WHERE BLOOM(status_id as status_id) AND BLOOM(subject_id as subject_id) 131 90 INNER JOIN LOOP ON mk.movie_id = cc.movie_id 1 90 │└TABLE SEEK complete_cast AS cc 90 414 INNER JOIN LOOP ON Bmk1024 = Bmk1024 1 414 │└TABLE SEEK movie_keyword AS mk 90 414 INNER JOIN LOOP ON k.id = mk.keyword_id 90 414 │└TABLE SEEK movie_keyword AS mk 1 1 TABLE SCAN keyword AS k WHERE keyword as keyword = 'computer-animation'
	Estimate Actual Operator 1 ∞ PROJECT min AS voiced_char, min_98 AS voicing_actress, min_99 AS voiced_animation 1 1 AGGREGATE MIN(min_100) AS min, MIN(min_101) AS min_98, MIN(min_102) AS min_99 - 16 DISTRIBUTE GATHER - 16 AGGREGATE MIN(name_14) AS min_100, MIN(name_68) AS min_101, MIN(title) AS min_102 - 16308 INNER JOIN HASH ON movie_id_24 = id_90 176706 1042800 │└DISTRIBUTE HASH ON id_90 176706 1042800 │ PROJECT id AS id_90, title 176706 1042800 │ FILTER production_year BETWEEN 2000 AND 2010 176706 1042800 │ TABLE SCAN title - 16368 INNER JOIN HASH ON role_id = id_86 12 1 │└DISTRIBUTE GATHER 12 1 │ PROJECT id AS id_86 12 1 │ FILTER role = 'actress' 12 1 │ TABLE SCAN role_type - 16368 INNER JOIN HASH ON info_type_id_80 = id_40 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_40 113 1 │ FILTER info = 'trivia' 113 1 │ TABLE SCAN info_type - 16368 INNER JOIN HASH ON person_id_23 = person_id_79 2963664 620526 │└DISTRIBUTE HASH ON person_id_79 2963664 620526 │ PROJECT person_id AS person_id_79, info_type_id AS info_type_id_80 2963664 620526 │ TABLE SCAN person_info - 204 INNER JOIN HASH ON person_id_23 = id_67 3750742 3136 │└DISTRIBUTE HASH ON id_67 3750742 3136 │ PROJECT id AS id_67, name AS name_68 3750742 3136 │ FILTER (gender = 'f') AND (name LIKE '%An%') 3750742 3136 │ TABLE SCAN name - 204 INNER JOIN HASH ON keyword_id = id_45 134170 1 │└DISTRIBUTE GATHER 134170 1 │ PROJECT id AS id_45 134170 1 │ FILTER keyword = 'computer-animation' 134170 1 │ TABLE SCAN keyword - 204 INNER JOIN HASH ON movie_id_24 = movie_id_63 4523930 414 │└DISTRIBUTE HASH ON movie_id_63 4523930 414 │ PROJECT movie_id AS movie_id_63, keyword_id 4523930 414 │ TABLE SCAN movie_keyword - 204 INNER JOIN HASH ON info_type_id = id_36 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_36 113 1 │ FILTER info = 'release dates' 113 1 │ TABLE SCAN info_type - 204 INNER JOIN HASH ON movie_id_24 = movie_id_56 13352148 374 │└DISTRIBUTE HASH ON movie_id_56 13352148 374 │ PROJECT movie_id AS movie_id_56, info_type_id 13352148 374 │ FILTER (((info >= 'Japan:') AND (info < 'Japan;')) OR ((info >= 'USA:') AND (info < 'USA;'))) AND ((info LIKE 'Japan:%200%') OR (info LIKE 'USA:%200%')) 13352148 374 │ TABLE SCAN movie_info - 83 INNER JOIN HASH ON company_id = id_28 234997 84843 │└DISTRIBUTE GATHER 234997 84843 │ PROJECT id AS id_28 234997 84843 │ FILTER country_code = 'us' 234997 84843 │ TABLE SCAN company_name - 83 INNER JOIN HASH ON movie_id_24 = movie_id_50 2609129 632 │└DISTRIBUTE HASH ON movie_id_50 2609129 632 │ PROJECT movie_id AS movie_id_50, company_id 2609129 632 │ TABLE SCAN movie_companies - 13 INNER JOIN HASH ON person_role_id = id_13 3140339 3140339 │└DISTRIBUTE HASH ON id_13 3140339 3140339 │ PROJECT id AS id_13, name AS name_14 3140339 3140339 │ TABLE SCAN char_name - 16 INNER JOIN HASH ON status_id = id_8 4 1 │└DISTRIBUTE GATHER 4 1 │ PROJECT id AS id_8 4 1 │ FILTER kind = 'complete+verified' 4 1 │ TABLE SCAN comp_cast_type - 16 INNER JOIN HASH ON subject_id = id_4 4 1 │└DISTRIBUTE GATHER 4 1 │ PROJECT id AS id_4 4 1 │ FILTER kind = 'cast' 4 1 │ TABLE SCAN comp_cast_type - 16 INNER JOIN HASH ON movie_id_24 = movie_id 135086 20 │└DISTRIBUTE GATHER 135086 20 │ TABLE SCAN complete_cast - 16 INNER JOIN HASH ON person_id_23 = person_id 901343 3464 │└DISTRIBUTE GATHER 901343 3464 │ TABLE SCAN aka_name 32619910 5 PROJECT person_id AS person_id_23, movie_id AS movie_id_24, person_role_id, role_id 32619910 5 FILTER note IN('(voice)','(voice) (uncredited)','(voice: English version)','(voice: Japanese version)') 32619910 5 TABLE SCAN cast_info
	Estimate Actual Operator 1 1 AGGREGATE MIN(name), MIN(name), MIN(title) 1 16308 INNER JOIN LOOP ON id = person_role_id 1 16740 │└INNER JOIN LOOP ON person_id = person_id AND person_id = id AND (person_id = id) 1 3966 │ │└INNER JOIN LOOP ON id = info_type_id 1 3966 │ │ │└INNER JOIN LOOP ON id = info_type_id 1 15982 │ │ │ │└INNER JOIN LOOP ON person_id = person_id AND id = person_id AND (id = person_id) 1 55 │ │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 20 │ │ │ │ │ │└INNER JOIN LOOP ON id = role_id 1 20 │ │ │ │ │ │ │└INNER JOIN LOOP ON id = status_id 1 135 │ │ │ │ │ │ │ │└INNER JOIN LOOP ON id = subject_id 1 135 │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON movie_id = id 1 186 │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON id = company_id 1 786 │ │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 1 40 │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON id = person_id 5 3429 │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON movie_id = movie_id AND movie_id = id AND (movie_id = id) 14 249 │ │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON id = movie_id 34 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │└INNER JOIN LOOP ON keyword_id = id 1 1 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │└TABLE SEEK keyword AS k 305 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SEEK movie_keyword AS mk 414 414 │ │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SEEK title AS t WHERE (t.production_year >= 2000) AND (t.production_year <= 2010) 249 3428 │ │ │ │ │ │ │ │ │ │ │ │ │ TABLE SEEK cast_info AS ci WHERE ci.note IN('(voice)','(voice: Japanese version)','(voice) (uncredited)','(voice: English version)') 3429 3429 │ │ │ │ │ │ │ │ │ │ │ │ TABLE SEEK name AS n WHERE (n.name LIKE '%An%') AND (n.gender = 'f') 200 786 │ │ │ │ │ │ │ │ │ │ │ TABLE SEEK movie_companies AS mc 786 786 │ │ │ │ │ │ │ │ │ │ TABLE SEEK company_name AS cn WHERE cn.country_code = 'us' 372 186 │ │ │ │ │ │ │ │ │ TABLE SEEK complete_cast AS cc 135 135 │ │ │ │ │ │ │ │ TABLE SEEK comp_cast_type AS cct1 WHERE cct1.kind = 'cast' 135 135 │ │ │ │ │ │ │ TABLE SEEK comp_cast_type AS cct2 WHERE cct2.kind = 'complete+verified' 20 20 │ │ │ │ │ │ TABLE SEEK role_type AS rt WHERE rt.role = 'actress' 40 55 │ │ │ │ │ TABLE SEEK movie_info AS mi WHERE (mi.info LIKE 'Japan:%200%') OR (mi.info LIKE 'USA:%200%') 1375 15981 │ │ │ │ TABLE SEEK person_info AS pi 15982 15982 │ │ │ TABLE SEEK info_type AS it3 WHERE it3.info = 'trivia' 3966 3966 │ │ TABLE SEEK info_type AS it WHERE it.info = 'release dates' 7932 16736 │ TABLE SEEK aka_name AS an 16740 16740 TABLE SEEK char_name AS chn