Service peneur chien à 30000 Nîmes

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='3' AND cate_title_slug='garde-d-animaux'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=45

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('30' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='30000' AND ville_nom like '%nimes%' 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 '%peneur%chien%' OR ssrubr_title like '%peneur%chien%' OR ssrubr_slug like '%peneur%chien%') AND cate_id='45' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SELECT cate_title_form, cate_title FROM category WHERE cate_title='peneur%chien' OR cate_title_aff='peneur%chien' LIMIT 0,1

9. 0.0001

   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='30000'

13. 0.002

    SELECT ville_cp, ROUND((((acos(sin((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>37.394535678816 AND ville_latitude_deg<37.754264321184 AND ville_longitude_deg>43.513859299065 AND ville_longitude_deg<43.967740700935 HAVING distance <= 20 ORDER BY distance ASC

14. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='peneur chien'

15. 0.001

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='3' AND cate_id='45' AND wish_visu IN (1,6,10) AND wish_cp like '30000%'

16. 0.0001

    SELECT * FROM texte WHERE cate_id=45

17. 0.0001

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='3' AND (ssrubr_keywords='peneur chien' OR ssrubr_slug='peneur-chien' OR (ssrubr_title like '%peneur chien%')) AND cate_id='45' ORDER BY ssrubr_id LIMIT 0,1

18. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='peneur-chien' AND cate_id='45'

19. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='30000'

20. 0.0014

    SELECT ville_cp, ROUND((((acos(sin((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>37.394535678816 AND ville_latitude_deg<37.754264321184 AND ville_longitude_deg>43.513859299065 AND ville_longitude_deg<43.967740700935 HAVING distance <= 20 ORDER BY distance ASC

21. 0.0045

    SELECT ville_cp, ROUND((((acos(sin((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>37.124739197041 AND ville_latitude_deg<38.024060802959 AND ville_longitude_deg>43.173443355302 AND ville_longitude_deg<44.308156644698 HAVING distance <= 50 ORDER BY distance ASC

22. 0.0376

    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((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- 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='3' AND cate_id='45' AND wish_visu IN (1,6,10) AND wish_cp IN (30000,30000,30110,30110,30110,30110,30110,30110,30110,30110,30300,30110,30110,30110,30110,30110,30110,30110,30110) 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 (21250,180571,221984,242772,283688,260012,330924,304033,189472,234655,235041,523167)

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 = 21250 AND W.type_id = 1) OR (W.util_id <> 21250 AND W.type_id = 2)) AND (M.post_util_id = 21250 OR M.dest_util_id = 21250) 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=21250 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 = 180571 AND W.type_id = 1) OR (W.util_id <> 180571 AND W.type_id = 2)) AND (M.post_util_id = 180571 OR M.dest_util_id = 180571) 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=180571 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 = 221984 AND W.type_id = 1) OR (W.util_id <> 221984 AND W.type_id = 2)) AND (M.post_util_id = 221984 OR M.dest_util_id = 221984) 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=221984 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 = 242772 AND W.type_id = 1) OR (W.util_id <> 242772 AND W.type_id = 2)) AND (M.post_util_id = 242772 OR M.dest_util_id = 242772) 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=242772 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 = 283688 AND W.type_id = 1) OR (W.util_id <> 283688 AND W.type_id = 2)) AND (M.post_util_id = 283688 OR M.dest_util_id = 283688) 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=283688 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 = 260012 AND W.type_id = 1) OR (W.util_id <> 260012 AND W.type_id = 2)) AND (M.post_util_id = 260012 OR M.dest_util_id = 260012) 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=260012 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 = 330924 AND W.type_id = 1) OR (W.util_id <> 330924 AND W.type_id = 2)) AND (M.post_util_id = 330924 OR M.dest_util_id = 330924) 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=330924 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 = 304033 AND W.type_id = 1) OR (W.util_id <> 304033 AND W.type_id = 2)) AND (M.post_util_id = 304033 OR M.dest_util_id = 304033) 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=304033 AND note_visu IN (1,3,4)

40. 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 = 189472 AND W.type_id = 1) OR (W.util_id <> 189472 AND W.type_id = 2)) AND (M.post_util_id = 189472 OR M.dest_util_id = 189472) 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=189472 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 = 234655 AND W.type_id = 1) OR (W.util_id <> 234655 AND W.type_id = 2)) AND (M.post_util_id = 234655 OR M.dest_util_id = 234655) 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=234655 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 = 235041 AND W.type_id = 1) OR (W.util_id <> 235041 AND W.type_id = 2)) AND (M.post_util_id = 235041 OR M.dest_util_id = 235041) 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=235041 AND note_visu IN (1,3,4)

46. 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 = 523167 AND W.type_id = 1) OR (W.util_id <> 523167 AND W.type_id = 2)) AND (M.post_util_id = 523167 OR M.dest_util_id = 523167) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

47. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=523167 AND note_visu IN (1,3,4)

48. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='30000'

49. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>37.394535678816 AND ville_latitude_deg<37.754264321184 AND ville_longitude_deg>43.513859299065 AND ville_longitude_deg<43.967740700935 HAVING distance <= 20 ORDER BY distance ASC

50. 0.0052

    SELECT ville_cp, ROUND((((acos(sin((37.5744*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((37.5744*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((43.7408- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>37.124739197041 AND ville_latitude_deg<38.024060802959 AND ville_longitude_deg>43.173443355302 AND ville_longitude_deg<44.308156644698 HAVING distance <= 50 ORDER BY distance ASC

51. 0.0002

    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 (951,1210,1016,950,953,952,1070)

52. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (283688,304033,189472,523167,235041,330924,242772,234655,260012,221984,180571,21250)

53. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (283688,304033,189472,523167,235041,330924,242772,234655,260012,221984,180571,21250)

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

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 = 'peneur-chien' AND ss.cate_id = 45 LIMIT 1

56. 0.0002

    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 = 3 AND ss.cate_id = 45 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

57. 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 = 'peneur-chien' AND ss.cate_id = 45 LIMIT 1

58. 0.0001

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

59. 0.0001

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

60. 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='3' AND cate_cate_id IS NULL ORDER BY cate_order ASC

61. 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 (45) ORDER BY ssrubr_order ASC

62. 0.0016

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

63. 0.032

    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'

64. 0.0292

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

64 requetes sql en 0.1245