Location voiture à 31380 Montastruc-la-conseillère

1. 0.0001

   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='voiture'

3. 0.0001

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=81

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('31' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='31380' AND ville_nom like '%montastruc%la%conseillere%' 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. 0.0019

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%voitures%' OR ssrubr_title like '%voitures%' OR ssrubr_slug like '%voitures%') AND cate_id='81' 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. 0.0003

    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

11. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='31380'

12. 0.0019

    SELECT ville_cp, ROUND((((acos(sin((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>43.520135678816 AND ville_latitude_deg<43.879864321184 AND ville_longitude_deg>1.3845432914728 AND ville_longitude_deg<1.8821167085272 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='voiture; voitures; renault; citroen; citroën; peug'

14. 0.0003

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='81' AND ssrubr_id='985' AND wish_visu IN (1,6,10) AND wish_cp like '31380%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=81

16. 0.0003

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='voiture; voitures; renault; citroen; citroën; peug' OR ssrubr_slug='voiture;-voitures;-renault;-citroen;-citroën;-peug' OR (ssrubr_title like '%voiture; voitures; renault; citroen; citroën; peug%')) AND cate_id='81' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0002

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='voitures' AND cate_id='81'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='31380'

19. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>43.520135678816 AND ville_latitude_deg<43.879864321184 AND ville_longitude_deg>1.3845432914728 AND ville_longitude_deg<1.8821167085272 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0062

    SELECT ville_cp, ROUND((((acos(sin((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>43.250339197041 AND ville_latitude_deg<44.149660802959 AND ville_longitude_deg>1.0113578653675 AND ville_longitude_deg<2.2553021346325 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0117

    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((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- 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='81' AND ssrubr_id='985' AND wish_visu IN (1,6,10) AND wish_cp IN (31380,31380,31380,31590,31380,31380,31380,31380,31380,31590,31590,31380,31380,81500,81500,31590,31590,81500,31180,31850,81500,81370,31660,31590,31180,81800,31380,31180,31380,31850,31130,31280,31570,31660,81500,31240,31280,81500,81500,31140,31180,31140,31380,31130,81500,31240,81500,81800,31140,31620,31340,31570,31620,81500,31340,31130,31460,31340,31460,81500,81500,31140,31140,31570,31570,31280,81500,81500,81500,31130,31340,81800,81800,31780,31150,31340,81500,31140,31570,31460,31460,81500,31620,31140,31650,31650,81800,31460,31150,81500,31340,81800,81470,31650,81500,31570,81630,31150,31620,31460,31790,31400,31090,31004,31000,31043,31200,31100,31300,31500,31620) 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 (33351,42232,73455,62403,210600,268900,434405,454781,469202)

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 = 33351 AND W.type_id = 1) OR (W.util_id <> 33351 AND W.type_id = 2)) AND (M.post_util_id = 33351 OR M.dest_util_id = 33351) 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=33351 AND note_visu IN (1,3,4)

25. 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 = 42232 AND W.type_id = 1) OR (W.util_id <> 42232 AND W.type_id = 2)) AND (M.post_util_id = 42232 OR M.dest_util_id = 42232) 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=42232 AND note_visu IN (1,3,4)

27. 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 = 73455 AND W.type_id = 1) OR (W.util_id <> 73455 AND W.type_id = 2)) AND (M.post_util_id = 73455 OR M.dest_util_id = 73455) 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=73455 AND note_visu IN (1,3,4)

29. 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 = 62403 AND W.type_id = 1) OR (W.util_id <> 62403 AND W.type_id = 2)) AND (M.post_util_id = 62403 OR M.dest_util_id = 62403) 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=62403 AND note_visu IN (1,3,4)

31. 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 = 210600 AND W.type_id = 1) OR (W.util_id <> 210600 AND W.type_id = 2)) AND (M.post_util_id = 210600 OR M.dest_util_id = 210600) 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=210600 AND note_visu IN (1,3,4)

33. 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 = 268900 AND W.type_id = 1) OR (W.util_id <> 268900 AND W.type_id = 2)) AND (M.post_util_id = 268900 OR M.dest_util_id = 268900) 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=268900 AND note_visu IN (1,3,4)

35. 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 = 434405 AND W.type_id = 1) OR (W.util_id <> 434405 AND W.type_id = 2)) AND (M.post_util_id = 434405 OR M.dest_util_id = 434405) 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=434405 AND note_visu IN (1,3,4)

37. 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 = 454781 AND W.type_id = 1) OR (W.util_id <> 454781 AND W.type_id = 2)) AND (M.post_util_id = 454781 OR M.dest_util_id = 454781) 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=454781 AND note_visu IN (1,3,4)

39. 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 = 469202 AND W.type_id = 1) OR (W.util_id <> 469202 AND W.type_id = 2)) AND (M.post_util_id = 469202 OR M.dest_util_id = 469202) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

40. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=469202 AND note_visu IN (1,3,4)

41. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='31380'

42. 0.0019

    SELECT ville_cp, ROUND((((acos(sin((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>43.520135678816 AND ville_latitude_deg<43.879864321184 AND ville_longitude_deg>1.3845432914728 AND ville_longitude_deg<1.8821167085272 HAVING distance <= 20 ORDER BY distance ASC

43. 0.007

    SELECT ville_cp, ROUND((((acos(sin((43.7*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((43.7*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.63333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>43.250339197041 AND ville_latitude_deg<44.149660802959 AND ville_longitude_deg>1.0113578653675 AND ville_longitude_deg<2.2553021346325 HAVING distance <= 50 ORDER BY distance ASC

44. 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 (985)

45. 0.0003

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (268900,62403,434405,469202,454781,210600,73455,42232,33351)

46. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (268900,62403,434405,469202,454781,210600,73455,42232,33351)

47. 0.0003

    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='voiture; voitures; renault; citroen; citroën; peug' OR ssrubr_slug like '%voiture; voitures; renault; citroen; citroën; peug%' OR MATCH (ssrubr_slug) AGAINST ('(+voiture; +voitures; +renault; +citroen; +citroën; +peug)')) AND sk.ssrubr_id='985' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

48. 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 = 81 AND ss.ssrubr_id <> 985 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

49. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='985' AND actu_niveau=0 ORDER BY actu_ordre DESC

50. 0.0001

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

51. 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

52. 0.0003

    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 (81) ORDER BY ssrubr_order ASC

53. 0.0016

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

54. 0.0325

    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'

55. 0.0236

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

55 requetes sql en 0.0985