Planner — IMDB — JOB-15B

SELECT MIN(mi.info) AS release_date,
       MIN(t.title) AS youtube_movie
FROM job.aka_title AS aka_t,
     job.company_name AS cn,
     job.company_type AS ct,
     job.info_type AS it1,
     job.keyword AS k,
     job.movie_companies AS mc,
     job.movie_info AS mi,
     job.movie_keyword AS mk,
     job.title AS t
WHERE cn.country_code = '[us]'
  AND cn.name = 'YouTube'
  AND it1.info = 'release dates'
  AND mc.note LIKE '%(200%)%'
  AND mc.note LIKE '%(worldwide)%'
  AND mi.note LIKE '%internet%'
  AND mi.info LIKE 'USA:% 200%'
  AND t.production_year BETWEEN 2005 AND 2010
  AND t.id = aka_t.movie_id
  AND t.id = mi.movie_id
  AND t.id = mk.movie_id
  AND t.id = mc.movie_id
  AND mk.movie_id = mi.movie_id
  AND mk.movie_id = mc.movie_id
  AND mk.movie_id = aka_t.movie_id
  AND mi.movie_id = mc.movie_id
  AND mi.movie_id = aka_t.movie_id
  AND mc.movie_id = aka_t.movie_id
  AND k.id = mk.keyword_id
  AND it1.id = mi.info_type_id
  AND cn.id = mc.company_id
  AND ct.id = mc.company_type_id;

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 4,658,534 4.7M Rank		Estimation Error Est Err 4,658,713 4.7M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,233 1.2K Rank	Estimation Error Est Err 37 37 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 5,799,178 5.8M Rank		Estimation Error Est Err 5,799,177 5.8M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 3,658 3.7K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 5,532,147 5.5M Rank		Estimation Error Est Err 5,398,474 5.4M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 135,634 136K Rank	Estimation Error Est Err 38 38 Rank	Estimation Error Est Err 134,934 135K Rank
Estimation Error Est Err 10,885,098 11M Rank		Estimation Error Est Err 4,217,359 4.2M Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 361,574 362K Rank	Estimation Error Est Err 47 47 Rank	Estimation Error Est Err 546,152 546K Rank
Estimation Error Est Err 86,710 87K Rank		Estimation Error Est Err 86,709 87K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 666 666 Rank	Estimation Error Est Err 37 37 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 1,338 1.3K Rank	Estimation Error Est Err 1,337 1.3K Rank	Estimation Error Est Err 1,615 1.6K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 1,615 1.6K Rank	Estimation Error Est Err 37 37 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 3,188 3.2K Rank	Estimation Error Est Err 3,187 3.2K Rank	Estimation Error Est Err 3,462 3.5K Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 3,187 3.2K Rank	Estimation Error Est Err 37 37 Rank	Estimation Error Est Err 0 Rank
Estimation Error Est Err 5,376,213 5.4M Rank		Estimation Error Est Err 126 126 Rank	Estimation Error Est Err 0 0 Rank	Estimation Error Est Err 5,376,214 5.4M Rank	Estimation Error Est Err 53 53 Rank	Estimation Error Est Err 5,376,226 5.4M Rank

Actual Query Plans

Query Plan per Engine ?
	Query Plan
	Estimate Actual Operator 1 1 AGGREGATE min, min 1 37 INNER JOIN HASH ON id37 = movie_id65 2 151 │└INNER JOIN HASH ON id58 = keyword_id 2 151 │ │└INNER JOIN HASH ON id37 = movie_id53 1 74 │ │ │└INNER JOIN HASH ON id = company_type_id 4 4 │ │ │ │└TABLE SCAN company_type 1 74 │ │ │ INNER JOIN HASH ON id37 = movie_id 1 75 │ │ │ │└INNER JOIN HASH ON id6 = info_type_id 1 1 │ │ │ │ │└TABLE SCAN info_type WHERE info = release dates 1 75 │ │ │ │ INNER JOIN HASH ON movie_id30 = movie_id 1 278 │ │ │ │ │└INNER JOIN HASH ON id11 = company_id 1 1 │ │ │ │ │ │└TABLE SCAN company_name WHERE name = YouTube AND country_code = us 59940 278 │ │ │ │ │ TABLE SCAN movie_companies WHERE note LIKE '%(worldwide)%' AND note LIKE '%(200%)%' 5129 75 │ │ │ │ TABLE SCAN movie_info WHERE info) USA : AND note33 LIKE '%internet%' AND info32 LIKE '% 200%' 775283 73 │ │ │ TABLE SCAN title WHERE production_year BETWEEN 2005 AND 2010 4523930 4523930 │ │ TABLE SCAN movie_keyword 134170 134170 │ TABLE SCAN keyword 361379 2 TABLE SCAN aka_title
	Estimate Actual Operator - 1 PROJECT a1 AS release_date, a2 AS youtube_movie - 1 AGGREGATE MIN(info) AS a1, MIN(title) AS a2 - 0 PROJECT info, title - 0 PROJECT info, title - 0 INNER JOIN HASH ON tuple(PROJECTION_884.movie_id,PROJECTION_884.movie_id,PROJECTION_884.movie_id,PROJECTION_884.movie_id,PROJECTION_884.id,PROJECTION_884.id) = tuple(PROJECTION_869.movie_id,PROJECTION_869.movie_id,PROJECTION_869.movie_id,PROJECTION_869.movie_id,PROJECTION_869.movie_id,PROJECTION_869.movie_id) - 116 │└PROJECT movie_id_right, movie_id AS movie_id_right_2, info - 116 │ PROJECT movie_id, info, movie_id - 116 │ INNER JOIN HASH ON PROJECTION_881.movie_id = PROJECTION_872.movie_id - 1771 │ │└PROJECT movie_id AS movie_id_right, info - 1771 │ │ PROJECT info, movie_id - 1771 │ │ INNER JOIN HASH ON PROJECTION_878.info_type_id = PROJECTION_875.id - 1 │ │ │└PROJECT id - 1 │ │ │ PROJECT id - 1 │ │ │ TABLE SCAN info_type WHERE info = 'release dates' - 1771 │ │ PROJECT info_type_id, info, movie_id - 1771 │ │ PROJECT movie_id, info, info_type_id - 1771 │ │ TABLE SCAN movie_info WHERE note LIKE '%internet%' AND info LIKE 'USA:% 200%' - 361379 │ PROJECT movie_id AS movie_id_left - 361379 │ PROJECT movie_id - 361379 │ TABLE SCAN aka_title - 0 PROJECT movie_id AS movie_id_left, movie_id AS movie_id_left_2, id, title - 0 PROJECT movie_id, movie_id, title, id - 0 INNER JOIN HASH ON tuple(PROJECTION_914.id,PROJECTION_914.id) = tuple(PROJECTION_887.movie_id,PROJECTION_887.movie_id) - 0 │└PROJECT movie_id, movie_id - 0 │ PROJECT movie_id, movie_id - 0 │ INNER JOIN HASH ON PROJECTION_911.id = PROJECTION_890.keyword_id - 0 │ │└PROJECT keyword_id, movie_id, movie_id - 0 │ │ PROJECT movie_id, movie_id, keyword_id - 0 │ │ INNER JOIN HASH ON PROJECTION_908.movie_id = PROJECTION_893.movie_id - 0 │ │ │└PROJECT movie_id AS movie_id_right - 0 │ │ │ PROJECT movie_id - 0 │ │ │ INNER JOIN HASH ON PROJECTION_905.id = PROJECTION_896.company_type_id - 0 │ │ │ │└PROJECT company_type_id, movie_id - 0 │ │ │ │ PROJECT movie_id, company_type_id - 0 │ │ │ │ INNER JOIN HASH ON PROJECTION_902.company_id = PROJECTION_899.id - 0 │ │ │ │ │└PROJECT id - 0 │ │ │ │ │ PROJECT id - 0 │ │ │ │ │ TABLE SCAN company_name WHERE (country_code = 'us') AND (name = 'YouTube') - 61664 │ │ │ │ PROJECT company_id, movie_id, company_type_id - 61664 │ │ │ │ PROJECT movie_id, company_id, company_type_id - 61664 │ │ │ │ TABLE SCAN movie_companies WHERE note LIKE '%(200%)%' AND note LIKE '%(worldwide)%' - 4 │ │ │ PROJECT id - 4 │ │ │ PROJECT id - 4 │ │ │ TABLE SCAN company_type - 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 - 716259 PROJECT id, title - 716259 PROJECT id, title - 716259 TABLE SCAN title WHERE (production_year >= 2005) AND (production_year <= 2010)
	Estimate Actual Operator - 1 AGGREGATE MIN(#0), MIN(#1) 0 37 PROJECT info, title 0 37 INNER JOIN HASH ON id = keyword_id 0 37 │└INNER JOIN HASH ON movie_id = movie_id 0 3 │ │└INNER JOIN HASH ON id = company_type_id 0 3 │ │ │└INNER JOIN HASH ON id = movie_id 0 3 │ │ │ │└INNER JOIN HASH ON id = info_type_id 0 3 │ │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 0 27 │ │ │ │ │ │└INNER JOIN HASH ON movie_id = movie_id 4 278 │ │ │ │ │ │ │└INNER JOIN HASH ON company_id = id 2 1 │ │ │ │ │ │ │ │└TABLE SCAN company_name WHERE country_code = 'us' AND name = 'YouTube' 521825 278 │ │ │ │ │ │ │ FILTER movie_id BETWEEN 50 AND 2525672 521825 278 │ │ │ │ │ │ │ TABLE SCAN movie_companies WHERE (note LIKE '%(200%)%') AND contains(note,'(worldwide)') 361379 2881 │ │ │ │ │ │ TABLE SCAN aka_title 2967144 4 │ │ │ │ │ FILTER (movie_id BETWEEN 50 AND 2525672) AND (info LIKE 'USA:% 200%') 2967144 9 │ │ │ │ │ TABLE SCAN movie_info WHERE contains(note,'internet') AND info >= 'USA:' AND info < 'USA;' 2 1 │ │ │ │ FILTER id <= 110 2 1 │ │ │ │ TABLE SCAN info_type WHERE info = 'release dates' 505662 83466 │ │ │ FILTER id BETWEEN 50 AND 2525672 505662 83466 │ │ │ TABLE SCAN title WHERE production_year >= 2005 AND production_year <= 2010 4 1 │ │ TABLE SCAN company_type WHERE id <= 2 4523930 37 │ TABLE SCAN movie_keyword WHERE movie_id >= 50 AND movie_id <= 2525672 134170 36 TABLE SCAN keyword
	Estimate Actual Operator 1 1 PROJECT release_date, youtube_movie 1 1 AGGREGATE MIN(info), MIN(title) 15112 10 DISTRIBUTE GATHER 15112 10 AGGREGATE MIN(info), MIN(title) 15112 37 INNER JOIN HASH ON movie_id = CAST(t.id AS Int64) AND movie_id = id AND movie_id = id AND movie_id = id 15112 37 │└DISTRIBUTE GATHER 15112 37 │ INNER JOIN HASH ON keyword_id = id 15112 37 │ │└DISTRIBUTE GATHER 15112 37 │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = movie_id AND movie_id = CAST(mk.movie_id AS Int64) 15112 3 │ │ │└DISTRIBUTE GATHER 15112 3 │ │ │ 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' 72276 3 │ │ │ INNER JOIN HASH ON movie_id = movie_id AND movie_id = CAST(mi.movie_id AS Int64) 72276 27 │ │ │ │└DISTRIBUTE GATHER 72276 27 │ │ │ │ INNER JOIN HASH ON id = company_type_id 4 4 │ │ │ │ │└TABLE SCAN company_type 72276 27 │ │ │ │ INNER JOIN HASH ON id = company_id 47000 1 │ │ │ │ │└DISTRIBUTE GATHER 47000 1 │ │ │ │ │ FILTER (country_code = 'us') AND (name = 'YouTube') 234997 234997 │ │ │ │ │ TABLE SCAN company_name WHERE (country_code = 'us') AND (name = 'YouTube') 361379 20965 │ │ │ │ INNER JOIN HASH ON movie_id = CAST(mc.movie_id AS Int64) 361379 361379 │ │ │ │ │└DISTRIBUTE HASH ON movie_id 361379 361379 │ │ │ │ │ TABLE SCAN aka_title 521826 61664 │ │ │ │ DISTRIBUTE HASH ON CAST(mc.movie_id AS Int64) 521826 61664 │ │ │ │ PROJECT movie_id, company_id, company_type_id, CAST(movie_id AS INT64) 521826 61664 │ │ │ │ FILTER note LIKE '%(200%)%' AND note LIKE '%(worldwide)%' 2609129 2609129 │ │ │ │ TABLE SCAN movie_companies WHERE (((note LIKE '%(200%)%' AND note LIKE '%(worldwide)%') AND CASE MOD(HASH_REPARTITION(CAST(movie_id AS INT64)),10) WHEN 0 THEN (((CAST(movie_id AS INT64) >= 826) AND (CAST(movie_id AS INT64) <= 2525588)) AND TRUE) WHEN 1 THEN (((CAST(movie_id AS INT64) >= 596) AND (CAST(movie_id AS INT64) <= 2525544)) AND TRUE) WHEN 2 THEN (((CAST(movie_id AS INT64) >= 902) AND (CAST(movie_id AS INT64) <= 2525574)) AND TRUE) WHEN 3 THEN (((CA... 2967144 1771 │ │ │ PROJECT movie_id, info_type_id, info, CAST(movie_id AS INT64) 2967144 1771 │ │ │ FILTER note LIKE '%internet%' AND info LIKE 'USA:% 200%' 14835720 3212639 │ │ │ TABLE SCAN movie_info WHERE ((note LIKE '%internet%' AND info LIKE 'USA:% 200%') AND ((((movie_id >= 316212) AND (movie_id <= 2456520)) AND ((CAST(movie_id AS INT64) >= 316212) AND (CAST(movie_id AS INT64) <= 2456520))) AND struct(movie_id,CAST(movie_id AS INT64)) IN( < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > ... 4523930 3908285 │ │ TABLE SCAN movie_keyword WHERE ((((movie_id >= 1659687) AND (movie_id <= 2456520)) AND ((movie_id >= 1659687) AND (movie_id <= 2456520))) AND ((CAST(movie_id AS INT64) >= 1659687) AND (CAST(movie_id AS INT64) <= 2456520))) AND struct(movie_id,movie_id,CAST(movie_id AS INT64)) IN( < expr > , < expr > , < expr > ) 134170 122880 │ DISTRIBUTE ROUND ROBIN 134170 122880 │ TABLE SCAN keyword WHERE ((id >= 1) AND (id <= 102271)) AND id IN(1648,2488,7637,1,102271,1532,835,7477,8720,4925,8661,7861,4926,36062,1116,1732,58415,7755,7633,1535,6188,12236,7637,16496,784,1859,58631,1613,1876,2109,2905,62682,34675,1768,30750,875,1482) 108357 101764 PROJECT id, title, CAST(id AS INT64) 108357 101764 FILTER (production_year >= 2005) AND (production_year <= 2010) 2528312 435672 TABLE SCAN title WHERE ((production_year >= 2005) AND (production_year <= 2010)) AND ((((((CAST(id AS INT64) >= 2247120) AND (CAST(id AS INT64) <= 2456520)) AND ((id >= 2247120) AND (id <= 2456520))) AND ((id >= 2247120) AND (id <= 2456520))) AND ((id >= 2247120) AND (id <= 2456520))) AND struct(CAST(id AS INT64),id,id,id) IN( < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < expr > , < exp...
	Estimate Actual Operator 1 1 AGGREGATE MIN(mi.info), MIN(t.title) 1 1 DISTRIBUTE GATHER 1 1 AGGREGATE MIN(mi.info), MIN(t.title) 1610 37 INNER JOIN HASH ON mc.movie_id = aka_t.movie_id 1610 151 │└DISTRIBUTE GATHER 766 151 │ INNER JOIN HASH ON mk.keyword_id = k.id 766 134170 │ │└DISTRIBUTE GATHER 235000 134170 │ │ TABLE SCAN keyword 735 151 │ INNER JOIN HASH ON mc.movie_id = mk.movie_id 735 74 │ │└DISTRIBUTE GATHER 82 74 │ │ INNER JOIN HASH ON mi.info_type_id = it1.id 82 1 │ │ │└DISTRIBUTE GATHER 2530000 1 │ │ │ TABLE SCAN info_type WHERE it1.info = 'release dates' 82 74 │ │ INNER JOIN HASH ON mc.movie_id = mi.movie_id 82 254 │ │ │└DISTRIBUTE GATHER 13 254 │ │ │ INNER JOIN HASH ON mc.movie_id = t.id 13 278 │ │ │ │└DISTRIBUTE GATHER 12 278 │ │ │ │ INNER JOIN HASH ON mc.company_type_id = ct.id 12 4 │ │ │ │ │└DISTRIBUTE GATHER 4520000 4 │ │ │ │ │ TABLE SCAN company_type 12 278 │ │ │ │ INNER JOIN HASH ON mc.company_id = cn.id 12 1 │ │ │ │ │└DISTRIBUTE GATHER 361000 1 │ │ │ │ │ TABLE SCAN company_name WHERE (cn.country_code IS NOT NULL) AND (cn.country_code = 'us') AND (cn.name = 'YouTube') 134000 61386 │ │ │ │ TABLE SCAN movie_companies WHERE (mc.note IS NOT NULL) AND mc.note LIKE '%(200%)%' AND contains(mc.note,'(worldwide)') 113 711648 │ │ │ TABLE SCAN title WHERE (t.production_year IS NOT NULL) AND (t.production_year >= 2005L) AND (t.production_year <= 2010L) 14800000 1765 │ │ TABLE SCAN movie_info WHERE (mi.note IS NOT NULL) AND contains(mi.note,'internet') AND mi.info LIKE 'USA:% 200%' 4 4515744 │ TABLE SCAN movie_keyword 2610000 107428 TABLE SCAN aka_title WHERE aka_t.movie_id IS NOT NULL
	Estimate Actual Operator 1 1 AGGREGATE MIN(info as info) AS Expr1018, MIN(title as title) AS Expr1019 1 37 INNER JOIN LOOP ON t.id = mk.movie_id 17 37 │└TABLE SEEK movie_keyword AS mk 1 3 INNER JOIN LOOP ON Bmk1016 = Bmk1016 0 3 │└TABLE SEEK title AS t WHERE production_year as production_year >= 2005 AND production_year as production_year <= 2010 1 3 PROJECT BmkToPage Bmk1016 AS Expr1036 1 3 INNER JOIN LOOP ON mi.movie_id = t.id 1 3 │└TABLE SEEK title AS t 1 3 INNER JOIN LOOP ON mi.movie_id = aka_t.movie_id 1 3 │└TABLE SEEK aka_title AS aka_t 1 75 FILTER info as info = 'release dates' 1 75 INNER JOIN LOOP ON Bmk1006 = Bmk1006 1 75 │└TABLE SEEK info_type AS it1 1 75 INNER JOIN LOOP ON mi.info_type_id = it1.id 1 75 │└TABLE SEEK info_type AS it1 1 75 INNER JOIN LOOP ON mc.movie_id = mi.movie_id 1 75 │└TABLE SEEK movie_info AS mi WHERE note as note LIKE '%internet%' AND info as info LIKE 'USA:% 200%' 1 278 FILTER note as note LIKE '%(200%)%' AND note as note LIKE '%(worldwide)%' 44 1458 INNER JOIN LOOP ON Bmk1010 = Bmk1010 1 1458 │└TABLE SEEK movie_companies AS mc 44 1458 PROJECT BmkToPage Bmk1010 AS Expr1034 44 1458 INNER JOIN LOOP ON cn.id = mc.company_id 44 1458 │└TABLE SEEK movie_companies AS mc 1 1 TABLE SCAN company_name AS cn WHERE country_code as country_code = 'us' AND name as name = 'YouTube'
	Estimate Actual Operator 1 ∞ PROJECT min AS release_date, min_50 AS youtube_movie 1 1 AGGREGATE MIN(min_51) AS min, MIN(min_52) AS min_50 - 16 DISTRIBUTE GATHER - 16 AGGREGATE MIN(info_26) AS min_51, MIN(title_37) AS min_52 - 37 INNER JOIN HASH ON movie_id = id_36 88353 716259 │└DISTRIBUTE HASH ON id_36 88353 716259 │ PROJECT id AS id_36, title AS title_37 88353 716259 │ FILTER production_year BETWEEN 2005 AND 2010 88353 716259 │ TABLE SCAN title - 37 INNER JOIN HASH ON keyword_id = id_13 134170 134170 │└DISTRIBUTE GATHER 134170 134170 │ PROJECT id AS id_13 134170 134170 │ TABLE SCAN keyword - 37 INNER JOIN HASH ON movie_id = movie_id_32 4523930 4523930 │└DISTRIBUTE HASH ON movie_id_32 4523930 4523930 │ PROJECT movie_id AS movie_id_32, keyword_id 4523930 4523930 │ TABLE SCAN movie_keyword - 3 INNER JOIN HASH ON info_type_id = id_9 113 1 │└DISTRIBUTE GATHER 113 1 │ PROJECT id AS id_9 113 1 │ FILTER info = 'release dates' 113 1 │ TABLE SCAN info_type - 3 INNER JOIN HASH ON movie_id = movie_id_25 13352148 1771 │└DISTRIBUTE HASH ON movie_id_25 13352148 1771 │ PROJECT movie_id AS movie_id_25, info_type_id, info AS info_26 13352148 1771 │ FILTER (info >= 'USA:') AND (info < 'USA;') AND (note LIKE '%internet%') AND (info LIKE 'USA:% 200%') 13352148 1771 │ TABLE SCAN movie_info - 3 INNER JOIN HASH ON company_type_id = id_5 4 4 │└DISTRIBUTE GATHER 4 4 │ PROJECT id AS id_5 4 4 │ TABLE SCAN company_type - 3 INNER JOIN HASH ON company_id = id_0 234997 1 │└DISTRIBUTE GATHER 234997 1 │ PROJECT id AS id_0 234997 1 │ FILTER (country_code = 'us') AND (name = 'YouTube') 234997 1 │ TABLE SCAN company_name - 3 INNER JOIN HASH ON movie_id = movie_id_19 2348216 74 │└DISTRIBUTE HASH ON movie_id_19 2348216 74 │ PROJECT movie_id AS movie_id_19, company_id, company_type_id 2348216 74 │ FILTER (note LIKE '%(200%)%') AND (note LIKE '%(worldwide)%') 2348216 74 │ TABLE SCAN movie_companies 361379 3 TABLE SCAN aka_title
	Estimate Actual Operator 1 1 AGGREGATE MIN(info), MIN(title) 9 37 INNER JOIN LOOP ON movie_id = id 3 151 │└INNER JOIN LOOP ON id = keyword_id 3 151 │ │└INNER JOIN LOOP ON movie_id = id 1 74 │ │ │└INNER JOIN LOOP ON id = info_type_id 1 74 │ │ │ │└INNER JOIN LOOP ON movie_id = id 1 254 │ │ │ │ │└INNER JOIN LOOP ON id = movie_id 1 278 │ │ │ │ │ │└INNER JOIN LOOP ON id = company_type_id AND (id = company_type_id) 1 278 │ │ │ │ │ │ │└INNER JOIN LOOP ON company_id = id 1 1 │ │ │ │ │ │ │ │└TABLE SEEK company_name AS cn WHERE cn.country_code = 'us' 1 278 │ │ │ │ │ │ │ TABLE SEEK movie_companies AS mc WHERE (mc.note LIKE '%(200%)%') AND (mc.note LIKE '%(worldwide)%') 4 1 │ │ │ │ │ │ TABLE SCAN company_type AS ct 278 278 │ │ │ │ │ TABLE SEEK title AS t WHERE (t.production_year >= 2005) AND (t.production_year <= 2010) 254 254 │ │ │ │ TABLE SEEK movie_info AS mi WHERE (mi.note LIKE '%internet%') AND (mi.info LIKE 'USA:% 200%') 74 74 │ │ │ TABLE SEEK info_type AS it1 WHERE it1.info = 'release dates' 3330 150 │ │ TABLE SEEK movie_keyword AS mk 151 151 │ TABLE SEEK keyword AS k 453 151 TABLE SEEK aka_title AS aka_t