Service tailler haies à 14370 Argences

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

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='14'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='14370' AND ville_nom like '%argences%' 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. 0.0003

    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='14370'

12. 0.0033

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-0.47480365067191 AND ville_longitude_deg<0.074803650671909 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. 0.0004

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='3' AND cate_id='38'AND MATCH (wish_title,wish_desc) AGAINST ('+taille haie; taille de haies*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '14370%'

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='14370'

19. 0.0035

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-0.47480365067191 AND ville_longitude_deg<0.074803650671909 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0212

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.667039197041 AND ville_latitude_deg<49.566360802959 AND ville_longitude_deg>-0.88701505086448 AND ville_longitude_deg<0.48701505086448 HAVING distance <= 50 ORDER BY distance ASC

21. 0.042

    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((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- 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 MATCH (wish_desc) AGAINST ('(+taille +haie; +taille +de +haies*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (14370,14370,14370,14370,14370,14370,14370,14630,14540,14630,14370,14540,14370,14630,14190,14670,14540,14540,14270,14670,14540,14540,14540,14370,14940,14940,14940,14670,14540,14190,14370,14270,14670,14670,14670,14190,14370,14540,14370,14540,14840,14840,14190,14190,14730,14270,14680,14270,14270,14120,14123,14270,14270,14123,14320,14190,14850,14190,14670,14850,14460,14190,14680,14270,14190,14190,14320,14270,14270,14680,14430,14320,14200,14860,14860,14000,14430,14190,14430,14320,14680,14860,14123,14320,14340,14430,14111,14430,14550,14190,14190,14390,14860,14320,14420,14320,14390,14170,14220,14170,14340,14340,14930,14970,14112,14340,14430,14270,14170,14170,14280,14220,14610,14170,14160,14760,14810,14220,14170,14121,14420,14430,14430,14340,14930,14170,14430,14170,14930,14170,14210,14220,14220,14420,14430,14970,14190,14810,14270,14340,14160,14280,14340,14790,14790,14340,14700,14610,14220,14170,14170,14170,14220,14150,14340,14140,14430,14920,14220,14280,14210,14610,14210,14420,14650,14340,14340,14220,14210,14140,14880,14160,14160,14112,14610,14170) AND type_id=1 GROUP BY wish_id

22. 0.0003

    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 = 65046 AND W.type_id = 1) OR (W.util_id <> 65046 AND W.type_id = 2)) AND (M.post_util_id = 65046 OR M.dest_util_id = 65046) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

23. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=65046 AND note_visu IN (1,3,4)

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 = 134823 AND W.type_id = 1) OR (W.util_id <> 134823 AND W.type_id = 2)) AND (M.post_util_id = 134823 OR M.dest_util_id = 134823) 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=134823 AND note_visu IN (1,3,4)

26. 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 = 165900 AND W.type_id = 1) OR (W.util_id <> 165900 AND W.type_id = 2)) AND (M.post_util_id = 165900 OR M.dest_util_id = 165900) 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=165900 AND note_visu IN (1,3,4)

28. 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 = 171206 AND W.type_id = 1) OR (W.util_id <> 171206 AND W.type_id = 2)) AND (M.post_util_id = 171206 OR M.dest_util_id = 171206) 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=171206 AND note_visu IN (1,3,4)

30. 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 = 357393 AND W.type_id = 1) OR (W.util_id <> 357393 AND W.type_id = 2)) AND (M.post_util_id = 357393 OR M.dest_util_id = 357393) 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=357393 AND note_visu IN (1,3,4)

32. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='14370'

33. 0.0029

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-0.47480365067191 AND ville_longitude_deg<0.074803650671909 HAVING distance <= 20 ORDER BY distance ASC

34. 0.0206

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.667039197041 AND ville_latitude_deg<49.566360802959 AND ville_longitude_deg>-0.88701505086448 AND ville_longitude_deg<0.48701505086448 HAVING distance <= 50 ORDER BY distance ASC

35. 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)

36. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (165900,134823,171206,357393,65046)

37. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (165900,134823,171206,357393,65046)

38. 0.0002

    SELECT ssrubr_id, ssrubr_title, ssrubr_slug, ssrubr_photo, cate_title_slug FROM ssrubr ss, category c WHERE ss.cate_id=c.cate_id AND ssrubr_visu=1 AND ss.cate_id=38 AND ss.fami_id=3 ORDER BY ssrubr_order LIMIT 6,100

39. 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

40. 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

41. 0.0001

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

42. 0.0001

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

43. 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

44. 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

45. 0.001

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

46. 0.0247

    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'

47. 0.0174

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

47 requetes sql en 0.1424