Location poussette avec cosy à 49000 Angers

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='5' AND cate_title_slug='equipement-pour-bebe'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=228

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('49' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='49000' AND ville_nom like '%angers%' 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 '%poussette%avec%cosy%' OR ssrubr_title like '%poussette%avec%cosy%' OR ssrubr_slug like '%poussette%avec%cosy%') AND cate_id='228' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SELECT cate_title_form, cate_title FROM category WHERE cate_title='poussette%avec%cosy' OR cate_title_aff='poussette%avec%cosy' LIMIT 0,1

9. 0.0001

   SHOW TABLES LIKE 'pays'

10. 0.0002

    SHOW COLUMNS FROM pays LIKE 'pays_tel_%'

11. 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

12. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='49000'

13. 0.0016

    SELECT ville_cp, ROUND((((acos(sin((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>47.353435678816 AND ville_latitude_deg<47.713164321184 AND ville_longitude_deg>-0.79973532318015 AND ville_longitude_deg<-0.26693067681985 HAVING distance <= 20 ORDER BY distance ASC

14. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='poussette avec cosy'

15. 0.0004

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='228' AND wish_visu IN (1,6,10) AND wish_cp like '49000%'

16. 0.0001

    SELECT * FROM texte WHERE cate_id=228

17. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='poussette avec cosy' OR ssrubr_slug='poussette-avec-cosy' OR (ssrubr_title like '%poussette avec cosy%')) AND cate_id='228' ORDER BY ssrubr_id LIMIT 0,1

18. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='poussette-avec-cosy' AND cate_id='228'

19. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='49000'

20. 0.0016

    SELECT ville_cp, ROUND((((acos(sin((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>47.353435678816 AND ville_latitude_deg<47.713164321184 AND ville_longitude_deg>-0.79973532318015 AND ville_longitude_deg<-0.26693067681985 HAVING distance <= 20 ORDER BY distance ASC

21. 0.0047

    SELECT ville_cp, ROUND((((acos(sin((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>47.083639197041 AND ville_latitude_deg<47.982960802959 AND ville_longitude_deg>-1.1993445510203 AND ville_longitude_deg<0.13267855102027 HAVING distance <= 50 ORDER BY distance ASC

22. 0.0152

    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((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- 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='5' AND cate_id='228' AND wish_visu IN (1,6,10) AND wish_cp IN (49000,49000,49460,49125,49240,49460,49480,49460,49460,49112,49000,49100,49124,49124,49140,49140,49460,49125,49220,49220,49220,49800,49125,49330,49070,49770,49140,49800,49130,49070,49070,49800,49130,49330,49220,49140,49800,49140,49080,49130,49130,49220,49330,49800,49330,49610,49170,49630,49320,49370,49800,49320,49140,49170,49330,49140,49320,49220,49190,49220,49430,49330,49140,49220,49220,49610,49610,49140,49170,49170,49140,49320,49330,49140) 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 (52242,116778,184904,243215,311242,330078,418347,525321)

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 = 52242 AND W.type_id = 1) OR (W.util_id <> 52242 AND W.type_id = 2)) AND (M.post_util_id = 52242 OR M.dest_util_id = 52242) 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=52242 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 = 116778 AND W.type_id = 1) OR (W.util_id <> 116778 AND W.type_id = 2)) AND (M.post_util_id = 116778 OR M.dest_util_id = 116778) 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=116778 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 = 184904 AND W.type_id = 1) OR (W.util_id <> 184904 AND W.type_id = 2)) AND (M.post_util_id = 184904 OR M.dest_util_id = 184904) 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=184904 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 = 243215 AND W.type_id = 1) OR (W.util_id <> 243215 AND W.type_id = 2)) AND (M.post_util_id = 243215 OR M.dest_util_id = 243215) 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=243215 AND note_visu IN (1,3,4)

32. 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 = 311242 AND W.type_id = 1) OR (W.util_id <> 311242 AND W.type_id = 2)) AND (M.post_util_id = 311242 OR M.dest_util_id = 311242) 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=311242 AND note_visu IN (1,3,4)

34. 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 = 330078 AND W.type_id = 1) OR (W.util_id <> 330078 AND W.type_id = 2)) AND (M.post_util_id = 330078 OR M.dest_util_id = 330078) 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=330078 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 = 418347 AND W.type_id = 1) OR (W.util_id <> 418347 AND W.type_id = 2)) AND (M.post_util_id = 418347 OR M.dest_util_id = 418347) 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=418347 AND note_visu IN (1,3,4)

38. 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 = 525321 AND W.type_id = 1) OR (W.util_id <> 525321 AND W.type_id = 2)) AND (M.post_util_id = 525321 OR M.dest_util_id = 525321) 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=525321 AND note_visu IN (1,3,4)

40. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='49000'

41. 0.0016

    SELECT ville_cp, ROUND((((acos(sin((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>47.353435678816 AND ville_latitude_deg<47.713164321184 AND ville_longitude_deg>-0.79973532318015 AND ville_longitude_deg<-0.26693067681985 HAVING distance <= 20 ORDER BY distance ASC

42. 0.0048

    SELECT ville_cp, ROUND((((acos(sin((47.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((47.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.533333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>47.083639197041 AND ville_latitude_deg<47.982960802959 AND ville_longitude_deg>-1.1993445510203 AND ville_longitude_deg<0.13267855102027 HAVING distance <= 50 ORDER BY distance ASC

43. 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 (800,728,802,798,857,804)

44. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (52242,418347,330078,311242,116778,243215,184904,525321)

45. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (52242,418347,330078,311242,116778,243215,184904,525321)

46. 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='poussette avec cosy' OR ssrubr_slug like '%poussette avec cosy%' OR MATCH (ssrubr_slug) AGAINST ('(+poussette +avec +cosy)')) AND sk.ssrubr_id='' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

47. 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 = 'poussette-avec-cosy' AND ss.cate_id = 228 LIMIT 1

48. 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 = 5 AND ss.cate_id = 228 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

49. 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 = 'poussette-avec-cosy' AND ss.cate_id = 228 LIMIT 1

50. 0.0001

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

51. 0

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

52. 0.0001

    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='5' AND cate_cate_id IS NULL ORDER BY cate_order ASC

53. 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 (228) ORDER BY ssrubr_order ASC

54. 0.0013

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

55. 0.0258

    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'

56. 0.0181

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

56 requetes sql en 0.0807