Location valise diagnostic à 91170 Viry-châtillon

1. 0.0002

   SELECT cate_title_slug FROM category WHERE fami_id IN (3,5) AND cate_title_slug<>'' AND cate_title_slug IS NOT NULL

2. 0.0001

   SELECT cate_id FROM category WHERE fami_id='5' AND cate_title_slug='outillage-mecanique-automobile'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=227

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('91' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='91170' AND ville_nom like '%viry%chatillon%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0004

   SELECT DISTINCT ssrubr_slug FROM ssrubr WHERE ssrubr_visu=1 AND fami_id IN (3,5) AND ssrubr_slug IS NOT NULL AND ssrubr_slug<>''

7. 0.0001

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%valise%diag%auto%' OR ssrubr_title like '%valise%diag%auto%' OR ssrubr_slug like '%valise%diag%auto%') AND cate_id='227' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SHOW TABLES LIKE 'pays'

9. 0.0002

   SHOW COLUMNS FROM pays LIKE 'pays_tel_%'

10. 0.0002

    SELECT pays_code, pays_nom, pays_actif, pays_NDD, pays_drapeau, pays_lang, pays_tel, pays_nb_annonces, pays_tel_masque, pays_tel_max, pays_tel_fmt_paires, pays_tel_mode FROM pays ORDER BY pays_nom ASC

11. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='91170'

12. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.486835678816 AND ville_latitude_deg<48.846564321184 AND ville_longitude_deg>2.1109886664695 AND ville_longitude_deg<2.6556713335305 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='valise diagnostique; valise diag auto; valise diag'

14. 0.0023

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp like '91170%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=227

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug='valise-diagnostique;-valise-diag-auto;-valise-diag' OR (ssrubr_title like '%valise diagnostique; valise diag auto; valise diag%')) AND cate_id='227' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='valise-diag-auto' AND cate_id='227'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='91170'

19. 0.0024

    SELECT ville_cp, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.486835678816 AND ville_latitude_deg<48.846564321184 AND ville_longitude_deg>2.1109886664695 AND ville_longitude_deg<2.6556713335305 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0056

    SELECT ville_cp, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.217039197041 AND ville_latitude_deg<49.116360802959 AND ville_longitude_deg>1.7024707950714 AND ville_longitude_deg<3.0641892049286 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0023

    SELECT wish.*, ui.util_photo, ui.util_prenom, ui.util_nom, ui.stripe_account_id, ui.util_verify, ville_cp,ville_nom,ville_latitude_deg,ville_longitude_deg, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM wish LEFT JOIN util_info ui ON wish.util_id=ui.util_id LEFT JOIN villes v ON wish.wish_cp=v.ville_cp WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp IN (91170,91170,91260,91350,91600,91390,91130,91210,91000,91360,91700,91270,91360,91420,91700,91450,91070,91200,91080,91550,94480,91230,91090,91000,91700,91160,91380,91240,91450,91160,91220,91560,91220,94290,91090,91310,91320,91160,91620,94190,91250,91160,91800,94310,94390,91250,91310,91310,94150,91860,91330,91280,91300,94450,91100,91140,94260,91100,91480,94460,92160,94320,91140,91620,91800,91810,91540,91310,91120,91250,94550,94600,91460,91540,91540,91630,91180,94440,91370,91290,91630,94520,94520,77127,92340,91480,94400,91540,91710,94380,77380,94237,94239,94470,94230,94231,94232,94233,94234,94235,94236,94238,94240,91290,92290,91250,91630,91830,91430,94440,94000,94440,91630,94800,92260,92330,94140,91400,94110,94700,91770,91750,91570,91430,91520,91340,91680,92350,91630,94380,94370,91610,77170,91940,91940,92220,91440,77176,92320,91830,94205,94200,94270,94220,77550,91760,94250,94210,94340,94100,92140,77170,91640,91750,92120,91400,94410,92240,94430,94340,91850,94880,94880,94490,77240,91790,91640,77176,91650,91940,91190,91730,77166,77150,91680,77550,94160,91590,92130,91510,91510,92190,92360,77310,91190,94500,78350,91650,77240,92170,94510,91400,77150,94130) AND type_id=1 GROUP BY wish_id

22. 0.0001

    SELECT util_id, util_photo, util_prenom, util_nom, stripe_account_id, util_verify FROM util_info WHERE util_id IN (97147,129294,279594,339734,277618,460499,529840,548137)

23. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 97147 AND W.type_id = 1) OR (W.util_id <> 97147 AND W.type_id = 2)) AND (M.post_util_id = 97147 OR M.dest_util_id = 97147) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

24. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=97147 AND note_visu IN (1,3,4)

25. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 129294 AND W.type_id = 1) OR (W.util_id <> 129294 AND W.type_id = 2)) AND (M.post_util_id = 129294 OR M.dest_util_id = 129294) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

26. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=129294 AND note_visu IN (1,3,4)

27. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 279594 AND W.type_id = 1) OR (W.util_id <> 279594 AND W.type_id = 2)) AND (M.post_util_id = 279594 OR M.dest_util_id = 279594) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

28. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=279594 AND note_visu IN (1,3,4)

29. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 339734 AND W.type_id = 1) OR (W.util_id <> 339734 AND W.type_id = 2)) AND (M.post_util_id = 339734 OR M.dest_util_id = 339734) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

30. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=339734 AND note_visu IN (1,3,4)

31. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 277618 AND W.type_id = 1) OR (W.util_id <> 277618 AND W.type_id = 2)) AND (M.post_util_id = 277618 OR M.dest_util_id = 277618) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

32. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=277618 AND note_visu IN (1,3,4)

33. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 460499 AND W.type_id = 1) OR (W.util_id <> 460499 AND W.type_id = 2)) AND (M.post_util_id = 460499 OR M.dest_util_id = 460499) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

34. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=460499 AND note_visu IN (1,3,4)

35. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 529840 AND W.type_id = 1) OR (W.util_id <> 529840 AND W.type_id = 2)) AND (M.post_util_id = 529840 OR M.dest_util_id = 529840) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

36. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=529840 AND note_visu IN (1,3,4)

37. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 548137 AND W.type_id = 1) OR (W.util_id <> 548137 AND W.type_id = 2)) AND (M.post_util_id = 548137 OR M.dest_util_id = 548137) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

38. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=548137 AND note_visu IN (1,3,4)

39. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='91170'

40. 0.0017

    SELECT ville_cp, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.486835678816 AND ville_latitude_deg<48.846564321184 AND ville_longitude_deg>2.1109886664695 AND ville_longitude_deg<2.6556713335305 HAVING distance <= 20 ORDER BY distance ASC

41. 0.0059

    SELECT ville_cp, ROUND((((acos(sin((48.6667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.6667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.38333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.217039197041 AND ville_latitude_deg<49.116360802959 AND ville_longitude_deg>1.7024707950714 AND ville_longitude_deg<3.0641892049286 HAVING distance <= 50 ORDER BY distance ASC

42. 0.0001

    SELECT ssr.ssrubr_id, ssr.ssrubr_slug, ssr.ssrubr_mail, ssr.ssrubr_mail_bis, ssr.ssrubr_keywords, ssr.ssrubr_bt2, ssr.ssrubr_photo, c.cate_title_slug, f.fami_url FROM ssrubr ssr, category c, family f WHERE ssr.cate_id=c.cate_id AND c.fami_id=f.fami_id AND ssr.ssrubr_id IN (874)

43. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (339734,529840,277618,97147,129294,279594,548137,460499)

44. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (339734,529840,277618,97147,129294,279594,548137,460499)

45. 0.0002

    SELECT ss.fami_id, fami_url, ss.cate_id, cate_title_slug, keywords_title FROM `ssrubr_keywords` sk, ssrubr ss, category c, family f WHERE sk.ssrubr_id=ss.ssrubr_id AND ss.cate_id=c.cate_id AND c.fami_id=f.fami_id AND (ssrubr_slug='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug like '%valise diagnostique; valise diag auto; valise diag%' OR MATCH (ssrubr_slug) AGAINST ('(+valise +diagnostique; +valise +diag +auto; +valise +diag)')) AND sk.ssrubr_id='874' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

46. 0.0003

    SELECT ss.ssrubr_id, ss.ssrubr_slug, ss.ssrubr_title, ss.ssrubr_keywords, ss.ssrubr_mail, c.cate_title_slug FROM ssrubr ss INNER JOIN category c ON ss.cate_id = c.cate_id WHERE ss.ssrubr_visu = 1 AND ss.fami_id = 5 AND ss.cate_id = 227 AND ss.ssrubr_id <> 874 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

47. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='874' AND actu_niveau=0 ORDER BY actu_ordre DESC

48. 0.0001

    SELECT fami_id as id, fami_title as title, fami_tutotitle, fami_tutodesc, fami_buttontitle, fami_url as slug FROM `family`

49. 0.0001

    SELECT cate_id as id, cate_title as title, cate_title_slug as slug, fami_id FROM `category` WHERE cate_visu=1 AND fami_id='5' AND cate_cate_id IS NULL ORDER BY cate_order ASC

50. 0.0001

    SELECT ssrubr_id AS id, ssrubr_title as title, ssrubr_slug as slug, ssrubr_photo, cate_id, fami_id FROM ssrubr WHERE ssrubr_visu=1 AND cate_id IN (227) ORDER BY ssrubr_order ASC

51. 0.0009

    SELECT AVG(note) as note_moy FROM note WHERE note_visu IN (1,2,3,4) AND post_util_id<>7

52. 0.0242

    SELECT COUNT(*) AS nbavis FROM note n INNER JOIN util_info dest ON n.dest_util_id=dest.util_id INNER JOIN util_info post ON n.post_util_id=post.util_id INNER JOIN wish w ON n.wish_id=w.wish_id WHERE n.note_visu IN (1,2,3,4) AND n.post_util_id<>'7'

53. 0.0181

    SELECT count(*) as nbwish FROM wish WHERE wish_visu IN (1,6,10)

53 requetes sql en 0.071