Service tailler haies à 94450 Limeil-brévannes

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='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 filtre_dpt='94'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='94450' AND ville_nom like '%limeil%brevannes%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0004

   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='94450'

12. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.553435678816 AND ville_latitude_deg<48.913164321184 AND ville_longitude_deg>2.2106280876317 AND ville_longitude_deg<2.7560319123683 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. 0.0006

    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 '94450%'

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='94450'

19. 0.0027

    SELECT ville_cp, ROUND((((acos(sin((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.553435678816 AND ville_latitude_deg<48.913164321184 AND ville_longitude_deg>2.2106280876317 AND ville_longitude_deg<2.7560319123683 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0078

    SELECT ville_cp, ROUND((((acos(sin((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.283639197041 AND ville_latitude_deg<49.182960802959 AND ville_longitude_deg>1.8015693402035 AND ville_longitude_deg<3.1650906597965 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0427

    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((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- 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 (94450,94450,91330,94460,94190,91560,94470,94380,91800,94440,91230,94290,94440,94370,94380,94480,94000,91860,94520,91270,94520,94600,91200,94390,94440,94310,91800,94490,94880,91210,94880,94340,94210,94100,77170,94430,94320,91480,94400,94700,91480,91550,94140,94510,91260,94340,94410,91450,94500,77380,77150,94150,91170,94550,91000,91130,94220,91320,77150,94420,94130,91250,91450,77170,94800,91090,91000,94360,77340,91420,91350,94200,94205,94350,94160,77127,91600,91390,94230,94231,94236,94233,94240,94234,94235,94232,94237,94238,94239,94260,94270,91250,94120,91280,94170,92340,94110,91360,77184,94300,93330,77173,92160,77330,91160,91380,91700,77166,77680,91360,93160,91080,94250,77166,91300,77185,91100,93110,91250,91070,93360,93100,92120,92220,77550,77420,91090,93170,91700,92330,92260,91370,93460,92290,91160,92240,91700,92320,91160,93250,93130,92350,91160,91100,77186,93260,93220,93230,91120,77111,75018,75010,75116,75011,75012,75001,75013,75014,75015,75019,75016,75017,75009,75020,75004,75005,75006,75002,75007,75000,75008,75003,77183,92170,77090,91240,91140,92140,77135,77170,77550,93310,77176,77200,91220,91220,77220,92130,91620,91310,91250,91830,93140,77550,93320,93000,93340,77500,91540,91540,77164,91140,77360,91310,91310,77111,93500,91540,93370,91430,77600,92360,92190,77550,91570,77220,77176,77177) AND type_id=1 GROUP BY wish_id

22. 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 = 97670 AND W.type_id = 1) OR (W.util_id <> 97670 AND W.type_id = 2)) AND (M.post_util_id = 97670 OR M.dest_util_id = 97670) 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=97670 AND note_visu IN (1,3,4)

24. 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 = 97933 AND W.type_id = 1) OR (W.util_id <> 97933 AND W.type_id = 2)) AND (M.post_util_id = 97933 OR M.dest_util_id = 97933) 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=97933 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 = 123254 AND W.type_id = 1) OR (W.util_id <> 123254 AND W.type_id = 2)) AND (M.post_util_id = 123254 OR M.dest_util_id = 123254) 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=123254 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 = 216300 AND W.type_id = 1) OR (W.util_id <> 216300 AND W.type_id = 2)) AND (M.post_util_id = 216300 OR M.dest_util_id = 216300) 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=216300 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 = 246630 AND W.type_id = 1) OR (W.util_id <> 246630 AND W.type_id = 2)) AND (M.post_util_id = 246630 OR M.dest_util_id = 246630) 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=246630 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 = 25762 AND W.type_id = 1) OR (W.util_id <> 25762 AND W.type_id = 2)) AND (M.post_util_id = 25762 OR M.dest_util_id = 25762) 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=25762 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 = 337238 AND W.type_id = 1) OR (W.util_id <> 337238 AND W.type_id = 2)) AND (M.post_util_id = 337238 OR M.dest_util_id = 337238) 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=337238 AND note_visu IN (1,3,4)

36. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='94450'

37. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.553435678816 AND ville_latitude_deg<48.913164321184 AND ville_longitude_deg>2.2106280876317 AND ville_longitude_deg<2.7560319123683 HAVING distance <= 20 ORDER BY distance ASC

38. 0.0059

    SELECT ville_cp, ROUND((((acos(sin((48.7333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.7333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.48333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.283639197041 AND ville_latitude_deg<49.182960802959 AND ville_longitude_deg>1.8015693402035 AND ville_longitude_deg<3.1650906597965 HAVING distance <= 50 ORDER BY distance ASC

39. 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)

40. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (337238,246630,97670,123254,25762,216300,97933)

41. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (337238,246630,97670,123254,25762,216300,97933)

42. 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

43. 0.0001

    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

44. 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_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

45. 0.0001

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

46. 0

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

47. 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

48. 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

49. 0.001

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

50. 0.0249

    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'

51. 0.0205

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

51 requetes sql en 0.1163