Location bissell spotclean à 33000 Bordeaux

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='materiel-nettoyage'

3. 0.0001

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=110

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('33' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='33000' AND ville_nom like '%bordeaux%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0005

   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 '%bissell%spotclean%' OR ssrubr_title like '%bissell%spotclean%' OR ssrubr_slug like '%bissell%spotclean%') AND cate_id='110' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SELECT cate_title_form, cate_title FROM category WHERE cate_title='bissell%spotclean' OR cate_title_aff='bissell%spotclean' LIMIT 0,1

9. 0.0002

   SHOW TABLES LIKE 'pays'

10. 0.0002

    SHOW COLUMNS FROM pays LIKE 'pays_tel_%'

11. 0.0003

    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

12. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='33000'

13. 0.0044

    SELECT ville_cp, ROUND((((acos(sin((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.653435678816 AND ville_latitude_deg<45.013164321184 AND ville_longitude_deg>-0.82029712703074 AND ville_longitude_deg<-0.31303687296926 HAVING distance <= 20 ORDER BY distance ASC

14. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='bissell spotclean'

15. 0.0019

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='110'AND MATCH (wish_title,wish_desc) AGAINST ('+bissell spotclean*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '33000%'

16. 0.0001

    SELECT * FROM texte WHERE cate_id=110

17. 0.0003

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='bissell spotclean' OR ssrubr_slug='bissell-spotclean' OR (ssrubr_title like '%bissell spotclean%')) AND cate_id='110' ORDER BY ssrubr_id LIMIT 0,1

18. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='bissell-spotclean' AND cate_id='110'

19. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='33000'

20. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.653435678816 AND ville_latitude_deg<45.013164321184 AND ville_longitude_deg>-0.82029712703074 AND ville_longitude_deg<-0.31303687296926 HAVING distance <= 20 ORDER BY distance ASC

21. 0.0115

    SELECT ville_cp, ROUND((((acos(sin((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.383639197041 AND ville_latitude_deg<45.282960802959 AND ville_longitude_deg>-1.2007477853052 AND ville_longitude_deg<0.067413785305233 HAVING distance <= 50 ORDER BY distance ASC

22. 0.0973

    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((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- 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='110' AND MATCH (wish_desc) AGAINST ('(+bissell +spotclean*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (33000,33000,33800,33300,33100,33200,33072,33270,33400,33150,33270,33370,33130,33310,33700,33600,33114,33110,33520,33140,33360,33560,33370,33170,33530,33320,33360,33360,33370,33140,33370,33185,33610,33360,33290,33370,33360,33320,33560,33850,33360,33440,33370,33290,33450,33880,33670,33370,33440,33650,33370,33670,33450,33750,33610,33880,33640,33160,33160,33650,33290,33750,33127,33880,33450,33670,33640,33440,33290,33650,33670,33127,33640,33240,33240,33550,33670,33550,33450,33550,33750,33640,33640,33650,33750,33750,33240) AND type_id=1 GROUP BY wish_id

23. 0.0001

    SELECT util_id, util_photo, util_prenom, util_nom, stripe_account_id, util_verify FROM util_info WHERE util_id IN (192214,252888,282425,243473,314952,333585,345550,324436,445129,422795,7305)

24. 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 = 192214 AND W.type_id = 1) OR (W.util_id <> 192214 AND W.type_id = 2)) AND (M.post_util_id = 192214 OR M.dest_util_id = 192214) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

25. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=192214 AND note_visu IN (1,3,4)

26. 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 = 252888 AND W.type_id = 1) OR (W.util_id <> 252888 AND W.type_id = 2)) AND (M.post_util_id = 252888 OR M.dest_util_id = 252888) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

27. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=252888 AND note_visu IN (1,3,4)

28. 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 = 282425 AND W.type_id = 1) OR (W.util_id <> 282425 AND W.type_id = 2)) AND (M.post_util_id = 282425 OR M.dest_util_id = 282425) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

29. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=282425 AND note_visu IN (1,3,4)

30. 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 = 243473 AND W.type_id = 1) OR (W.util_id <> 243473 AND W.type_id = 2)) AND (M.post_util_id = 243473 OR M.dest_util_id = 243473) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

31. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=243473 AND note_visu IN (1,3,4)

32. 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 = 314952 AND W.type_id = 1) OR (W.util_id <> 314952 AND W.type_id = 2)) AND (M.post_util_id = 314952 OR M.dest_util_id = 314952) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

33. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=314952 AND note_visu IN (1,3,4)

34. 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 = 333585 AND W.type_id = 1) OR (W.util_id <> 333585 AND W.type_id = 2)) AND (M.post_util_id = 333585 OR M.dest_util_id = 333585) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

35. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=333585 AND note_visu IN (1,3,4)

36. 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 = 345550 AND W.type_id = 1) OR (W.util_id <> 345550 AND W.type_id = 2)) AND (M.post_util_id = 345550 OR M.dest_util_id = 345550) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

37. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=345550 AND note_visu IN (1,3,4)

38. 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 = 324436 AND W.type_id = 1) OR (W.util_id <> 324436 AND W.type_id = 2)) AND (M.post_util_id = 324436 OR M.dest_util_id = 324436) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

39. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=324436 AND note_visu IN (1,3,4)

40. 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 = 445129 AND W.type_id = 1) OR (W.util_id <> 445129 AND W.type_id = 2)) AND (M.post_util_id = 445129 OR M.dest_util_id = 445129) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

41. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=445129 AND note_visu IN (1,3,4)

42. 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 = 422795 AND W.type_id = 1) OR (W.util_id <> 422795 AND W.type_id = 2)) AND (M.post_util_id = 422795 OR M.dest_util_id = 422795) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

43. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=422795 AND note_visu IN (1,3,4)

44. 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 = 7305 AND W.type_id = 1) OR (W.util_id <> 7305 AND W.type_id = 2)) AND (M.post_util_id = 7305 OR M.dest_util_id = 7305) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

45. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=7305 AND note_visu IN (1,3,4)

46. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='33000'

47. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.653435678816 AND ville_latitude_deg<45.013164321184 AND ville_longitude_deg>-0.82029712703074 AND ville_longitude_deg<-0.31303687296926 HAVING distance <= 20 ORDER BY distance ASC

48. 0.0112

    SELECT ville_cp, ROUND((((acos(sin((44.8333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((44.8333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.566667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.383639197041 AND ville_latitude_deg<45.282960802959 AND ville_longitude_deg>-1.2007477853052 AND ville_longitude_deg<0.067413785305233 HAVING distance <= 50 ORDER BY distance ASC

49. 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 (747,1076,746)

50. 0.0003

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (345550,192214,243473,314952,7305,333585,422795,282425,445129,252888,324436)

51. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (345550,192214,243473,314952,7305,333585,422795,282425,445129,252888,324436)

52. 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='bissell spotclean' OR ssrubr_slug like '%bissell spotclean%' OR MATCH (ssrubr_slug) AGAINST ('(+bissell +spotclean)')) AND sk.ssrubr_id='' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

53. 0.0001

    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_slug = 'bissell-spotclean' AND ss.cate_id = 110 LIMIT 1

54. 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 = 110 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

55. 0.0001

    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_slug = 'bissell-spotclean' AND ss.cate_id = 110 LIMIT 1

56. 0.0001

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

57. 0.0001

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

58. 0.0002

    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

59. 0.0002

    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 (110) ORDER BY ssrubr_order ASC

60. 0.0015

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

61. 0.0519

    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'

62. 0.0391

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

62 requetes sql en 0.2324