Service tailler haies à 38170 Seyssinet-pariset

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. 0.0002

   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('38' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0002

   SELECT ville_nom FROM villes WHERE ville_cp='38170' AND ville_nom like '%seyssinet%pariset%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0006

   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. 0.0002

    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='38170'

12. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.986835678816 AND ville_latitude_deg<45.346564321184 AND ville_longitude_deg>5.3948897069247 AND ville_longitude_deg<5.9051102930753 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 '38170%'

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='38170'

19. 0.0032

    SELECT ville_cp, ROUND((((acos(sin((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.986835678816 AND ville_latitude_deg<45.346564321184 AND ville_longitude_deg>5.3948897069247 AND ville_longitude_deg<5.9051102930753 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0078

    SELECT ville_cp, ROUND((((acos(sin((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.717039197041 AND ville_latitude_deg<45.616360802959 AND ville_longitude_deg>5.0122187676742 AND ville_longitude_deg<6.2877812323258 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((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- 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 (38170,38170,38250,38600,38360,38180,38360,38100,38000,38640,38950,38130,38800,38700,38250,38120,38880,38320,38320,38800,38400,38760,38320,38120,38360,38112,38610,38700,38560,38950,38320,38760,38120,38113,38610,38220,38120,38210,38240,38210,38560,38410,38320,38220,38450,38420,38470,38700,38250,38330,38330,38220,38410,38420,38470,38340,38410,38210,38700,38450,38680,38220,38340,38470,38450,38420,38210,38330,38450,38470,38420,38220,38250,38470,38220,38470,38330,38220,38500,38420,38210,38430,38220,38430,38210,38190,38210,38410) 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 (98293,48568,75790,149831,89254,311344,326105,534353)

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 = 98293 AND W.type_id = 1) OR (W.util_id <> 98293 AND W.type_id = 2)) AND (M.post_util_id = 98293 OR M.dest_util_id = 98293) 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=98293 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 = 48568 AND W.type_id = 1) OR (W.util_id <> 48568 AND W.type_id = 2)) AND (M.post_util_id = 48568 OR M.dest_util_id = 48568) 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=48568 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 = 75790 AND W.type_id = 1) OR (W.util_id <> 75790 AND W.type_id = 2)) AND (M.post_util_id = 75790 OR M.dest_util_id = 75790) 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=75790 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 = 149831 AND W.type_id = 1) OR (W.util_id <> 149831 AND W.type_id = 2)) AND (M.post_util_id = 149831 OR M.dest_util_id = 149831) 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=149831 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 = 89254 AND W.type_id = 1) OR (W.util_id <> 89254 AND W.type_id = 2)) AND (M.post_util_id = 89254 OR M.dest_util_id = 89254) 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=89254 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 = 311344 AND W.type_id = 1) OR (W.util_id <> 311344 AND W.type_id = 2)) AND (M.post_util_id = 311344 OR M.dest_util_id = 311344) 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=311344 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 = 326105 AND W.type_id = 1) OR (W.util_id <> 326105 AND W.type_id = 2)) AND (M.post_util_id = 326105 OR M.dest_util_id = 326105) 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=326105 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 = 534353 AND W.type_id = 1) OR (W.util_id <> 534353 AND W.type_id = 2)) AND (M.post_util_id = 534353 OR M.dest_util_id = 534353) 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=534353 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='38170'

40. 0.0024

    SELECT ville_cp, ROUND((((acos(sin((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.986835678816 AND ville_latitude_deg<45.346564321184 AND ville_longitude_deg>5.3948897069247 AND ville_longitude_deg<5.9051102930753 HAVING distance <= 20 ORDER BY distance ASC

41. 0.008

    SELECT ville_cp, ROUND((((acos(sin((45.1667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((45.1667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((5.65- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>44.717039197041 AND ville_latitude_deg<45.616360802959 AND ville_longitude_deg>5.0122187676742 AND ville_longitude_deg<6.2877812323258 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 (530)

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 (75790,311344,534353,326105,48568,98293,149831,89254)

44. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (75790,311344,534353,326105,48568,98293,149831,89254)

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='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

46. 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

47. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='530' 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. 0.0002

    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

50. 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

51. 0.0015

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

52. 0.0389

    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. 0.0389

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

53 requetes sql en 0.1129