Service tailler haies à 78670 Médan

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='jardinage'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=38

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('78' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='78670' AND ville_nom like '%medan%' 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 '%taille%de%haies%' OR ssrubr_title like '%taille%de%haies%' OR ssrubr_slug like '%taille%de%haies%') AND cate_id='38' 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='78670'

12. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.770135678816 AND ville_latitude_deg<49.129864321184 AND ville_longitude_deg>1.7261156472466 AND ville_longitude_deg<2.2738843527534 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='taille haie; taille de haies'

14. 0.0002

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='3' AND cate_id='38' AND ssrubr_id='530' AND wish_visu IN (1,6,10) AND wish_cp like '78670%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=38

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='3' AND (ssrubr_keywords='taille haie; taille de haies' OR ssrubr_slug='taille-haie;-taille-de-haies' OR (ssrubr_title like '%taille haie; taille de haies%')) AND cate_id='38' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='taille-de-haies' AND cate_id='38'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78670'

19. 0.0024

    SELECT ville_cp, ROUND((((acos(sin((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.770135678816 AND ville_latitude_deg<49.129864321184 AND ville_longitude_deg>1.7261156472466 AND ville_longitude_deg<2.2738843527534 HAVING distance <= 20 ORDER BY distance ASC

20. 0.015

    SELECT ville_cp, ROUND((((acos(sin((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.500339197041 AND ville_latitude_deg<49.399660802959 AND ville_longitude_deg>1.3152832137498 AND ville_longitude_deg<2.6847167862502 HAVING distance <= 50 ORDER BY distance ASC

21. 0.003

    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((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- 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='38' AND ssrubr_id='530' AND wish_visu IN (1,6,10) AND wish_cp IN (78670,78670,78670,78540,78955,78510,78480,78630,78300,78570,78130,78260,78630,78240,78240,78920,78570,78580,78780,95000,95180,78410,95280,78740,78700,78100,78130,78740,78112,78121,95000,78250,78230,95800,78600,95490,78810,78250,78750,78580,78410,95450,78580,78110,95610,78250,78250,95000,78810,78620,78600,78160,78410,78126,95650,78860,78450,78124,78560,78250,78360,78580,95450,78590,78410,78410,78124,78820,78430,78850,78870,78450,95650,78400,95300,95220,78680,78500,95450,78380,78290,78590,95530,95520,95450,95370,78420,95310,95480,78250,78440,78970,78650,95650,95650,95450,78340,95300,78640,95240,78800,78370,78330,78770,78150,95450,78440,95650,78170,92000,95870,78440,95450,78580,78770,95250,92500,78440,95450,78640,78150,78390,78440,95450,78640,78440,78930,78440,78770,78210,95130,78930,78440,95450,78640,95430,78650,95130,92380,95300,92430,92420,95100,95550,95150,78770,95110,78770,78190,95830,95830,78770,92700,78440,78770,78990,92250,95450,95810,78490,95450,95300,78000,95740,92400,92150,92800,95450,95540,78930,95320,92410,95120,78520,92270,92210,95450,78760) 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 (126874,130446,194520,228646,21593,249432,203646,287801,288665,401773,287643,546939)

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 = 126874 AND W.type_id = 1) OR (W.util_id <> 126874 AND W.type_id = 2)) AND (M.post_util_id = 126874 OR M.dest_util_id = 126874) 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=126874 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 = 130446 AND W.type_id = 1) OR (W.util_id <> 130446 AND W.type_id = 2)) AND (M.post_util_id = 130446 OR M.dest_util_id = 130446) 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=130446 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 = 194520 AND W.type_id = 1) OR (W.util_id <> 194520 AND W.type_id = 2)) AND (M.post_util_id = 194520 OR M.dest_util_id = 194520) 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=194520 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 = 228646 AND W.type_id = 1) OR (W.util_id <> 228646 AND W.type_id = 2)) AND (M.post_util_id = 228646 OR M.dest_util_id = 228646) 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=228646 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 = 21593 AND W.type_id = 1) OR (W.util_id <> 21593 AND W.type_id = 2)) AND (M.post_util_id = 21593 OR M.dest_util_id = 21593) 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=21593 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 = 249432 AND W.type_id = 1) OR (W.util_id <> 249432 AND W.type_id = 2)) AND (M.post_util_id = 249432 OR M.dest_util_id = 249432) 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=249432 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 = 203646 AND W.type_id = 1) OR (W.util_id <> 203646 AND W.type_id = 2)) AND (M.post_util_id = 203646 OR M.dest_util_id = 203646) 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=203646 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 = 287801 AND W.type_id = 1) OR (W.util_id <> 287801 AND W.type_id = 2)) AND (M.post_util_id = 287801 OR M.dest_util_id = 287801) 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=287801 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 = 288665 AND W.type_id = 1) OR (W.util_id <> 288665 AND W.type_id = 2)) AND (M.post_util_id = 288665 OR M.dest_util_id = 288665) 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=288665 AND note_visu IN (1,3,4)

41. 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 = 401773 AND W.type_id = 1) OR (W.util_id <> 401773 AND W.type_id = 2)) AND (M.post_util_id = 401773 OR M.dest_util_id = 401773) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

42. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=401773 AND note_visu IN (1,3,4)

43. 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 = 287643 AND W.type_id = 1) OR (W.util_id <> 287643 AND W.type_id = 2)) AND (M.post_util_id = 287643 OR M.dest_util_id = 287643) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

44. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=287643 AND note_visu IN (1,3,4)

45. 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 = 546939 AND W.type_id = 1) OR (W.util_id <> 546939 AND W.type_id = 2)) AND (M.post_util_id = 546939 OR M.dest_util_id = 546939) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

46. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=546939 AND note_visu IN (1,3,4)

47. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78670'

48. 0.0019

    SELECT ville_cp, ROUND((((acos(sin((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.770135678816 AND ville_latitude_deg<49.129864321184 AND ville_longitude_deg>1.7261156472466 AND ville_longitude_deg<2.2738843527534 HAVING distance <= 20 ORDER BY distance ASC

49. 0.014

    SELECT ville_cp, ROUND((((acos(sin((48.95*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.95*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.500339197041 AND ville_latitude_deg<49.399660802959 AND ville_longitude_deg>1.3152832137498 AND ville_longitude_deg<2.6847167862502 HAVING distance <= 50 ORDER BY distance ASC

50. 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 (530)

51. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (401773,203646,287801,228646,249432,194520,287643,130446,546939,126874,21593,288665)

52. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (401773,203646,287801,228646,249432,194520,287643,130446,546939,126874,21593,288665)

53. 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='taille haie; taille de haies' OR ssrubr_slug like '%taille haie; taille de haies%' OR MATCH (ssrubr_slug) AGAINST ('(+taille +haie; +taille +de +haies)')) AND sk.ssrubr_id='530' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

54. 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 = 38 AND ss.ssrubr_id <> 530 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

55. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='530' AND actu_niveau=0 ORDER BY actu_ordre DESC

56. 0

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

57. 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

58. 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 (38) ORDER BY ssrubr_order ASC

59. 0.001

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

60. 0.0221

    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'

61. 0.0164

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

61 requetes sql en 0.085