Location taille haie à 50700 Valognes

1. 0.0001

   SELECT cate_id FROM category WHERE fami_id='5' AND cate_title_slug='materiel-jardinage'

2. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=88

3. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='50'

4. 0.0002

   SELECT ville_nom FROM villes WHERE ville_cp='50700' AND ville_nom like '%valognes%' ORDER BY ville_population_2012 DESC LIMIT 0,1

5. 0.0001

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%taille%haie%' OR ssrubr_title like '%taille%haie%' OR ssrubr_slug like '%taille%haie%') AND cate_id='88' ORDER BY ssrubr_id LIMIT 0,1

6. 0.0001

   SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='50700'

7. 0.0013

   SELECT ville_cp, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.370135678816 AND ville_latitude_deg<49.729864321184 AND ville_longitude_deg>-1.8605633398045 AND ville_longitude_deg<-1.3060966601955 HAVING distance <= 20 ORDER BY distance ASC

8. 0.0001

   SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='taille haie'

9. 0.0003

   SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='88'AND MATCH (wish_title,wish_desc) AGAINST ('+taille haie*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '50700%'

10. 0.0001

    SELECT * FROM texte WHERE cate_id=88

11. 0.0003

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='taille haie' OR ssrubr_slug='taille-haie' OR (ssrubr_title like '%taille haie%')) AND cate_id='88' ORDER BY ssrubr_id LIMIT 0,1

12. 0.0001

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

13. 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

14. 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 (88) ORDER BY ssrubr_order ASC

15. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='taille-haie' AND cate_id='88'

16. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='50700'

17. 0.001

    SELECT ville_cp, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.370135678816 AND ville_latitude_deg<49.729864321184 AND ville_longitude_deg>-1.8605633398045 AND ville_longitude_deg<-1.3060966601955 HAVING distance <= 20 ORDER BY distance ASC

18. 0.0023

    SELECT ville_cp, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.100339197041 AND ville_latitude_deg<49.999660802959 AND ville_longitude_deg>-2.2764193260749 AND ville_longitude_deg<-0.89024067392514 HAVING distance <= 50 ORDER BY distance ASC

19. 0.0937

    SELECT count(wish_id) as nbwish FROM wish WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='88' AND MATCH (wish_desc) AGAINST ('(+taille +haie*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (50700,50700,50260,50470,50700,50690,50470,50260,50690,50110,50690,50260,50260,50260,50690,50690,50700,50700,50110,50260,50700,50700,50260,50340,50700,50110,50260,50690,50260,50690,50340,50130,50100,50130,50690,50700,50690,50340,50330,50700,50700,50260,50310,50340,50700,50460,50440,50390,50310,50700,50440,50120,50340,50700,50340,50260,50330,50390,50630,50390,50390,50460,50390,50700,50260,50390,50630,50340,50340,50310,50330,50330,50440,50270,50340,50310,50310,50340,50330,50310,50270,50340,50840,50390,50310,50630,50310,50310,50440,50460,50630,50440,50310,50840,50270,50390,50310,50390,50480,50330,50310,50270,50360,50630,50580,50390,50340,50360)

20. 0.0533

    SELECT wish.*, ui.util_photo, ui.util_prenom, ui.util_nom, ui.stripe_account_id, ville_cp,ville_nom,ville_latitude_deg,ville_longitude_deg, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- 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='88' AND MATCH (wish_desc) AGAINST ('(+taille +haie*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (50700,50700,50260,50470,50700,50690,50470,50260,50690,50110,50690,50260,50260,50260,50690,50690,50700,50700,50110,50260,50700,50700,50260,50340,50700,50110,50260,50690,50260,50690,50340,50130,50100,50130,50690,50700,50690,50340,50330,50700,50700,50260,50310,50340,50700,50460,50440,50390,50310,50700,50440,50120,50340,50700,50340,50260,50330,50390,50630,50390,50390,50460,50390,50700,50260,50390,50630,50340,50340,50310,50330,50330,50440,50270,50340,50310,50310,50340,50330,50310,50270,50340,50840,50390,50310,50630,50310,50310,50440,50460,50630,50440,50310,50840,50270,50390,50310,50390,50480,50330,50310,50270,50360,50630,50580,50390,50340,50360) AND type_id=1 GROUP BY wish_id

21. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='50700'

22. 0.001

    SELECT ville_cp, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.370135678816 AND ville_latitude_deg<49.729864321184 AND ville_longitude_deg>-1.8605633398045 AND ville_longitude_deg<-1.3060966601955 HAVING distance <= 20 ORDER BY distance ASC

23. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((49.55*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.55*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-1.58333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.100339197041 AND ville_latitude_deg<49.999660802959 AND ville_longitude_deg>-2.2764193260749 AND ville_longitude_deg<-0.89024067392514 HAVING distance <= 50 ORDER BY distance ASC

24. 0.0002

    SELECT M.match_step FROM `match` AS M LEFT JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 109173 AND W.type_id = 1) OR (W.util_id != 109173 AND W.type_id = 2)) AND (`post_util_id` = 109173 OR `dest_util_id` = 109173) AND buy_stripe_pi_id != '' AND buy_stripe_pi_id IS NOT NULL

25. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=109173 AND note_visu IN (1,3,4)

26. 0.0001

    SELECT M.match_step FROM `match` AS M LEFT JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 119988 AND W.type_id = 1) OR (W.util_id != 119988 AND W.type_id = 2)) AND (`post_util_id` = 119988 OR `dest_util_id` = 119988) AND buy_stripe_pi_id != '' AND buy_stripe_pi_id IS NOT NULL

27. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=119988 AND note_visu IN (1,3,4)

28. 0.0001

    SELECT ssrubr_slug, ssrubr_mail, ssrubr_mail_bis, ssrubr_keywords, ssrubr_bt2, cate_title_slug, fami_url, ssrubr_photo 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='2' LIMIT 0,1

29. 0.0001

    SELECT abo_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id = 119988

30. 0.0001

    SELECT ssrubr_slug, ssrubr_mail, ssrubr_mail_bis, ssrubr_keywords, ssrubr_bt2, cate_title_slug, fami_url, ssrubr_photo 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='14' LIMIT 0,1

31. 0.0001

    SELECT M.match_step FROM `match` AS M LEFT JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 109173 AND W.type_id = 1) OR (W.util_id != 109173 AND W.type_id = 2)) AND (`post_util_id` = 109173 OR `dest_util_id` = 109173) AND buy_stripe_pi_id != '' AND buy_stripe_pi_id IS NOT NULL

32. 0.0001

    SELECT abo_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id = 109173

33. 0.0003

    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=88 AND ss.fami_id=5 ORDER BY ssrubr_order LIMIT 6,100

34. 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' OR ssrubr_slug like '%taille haie%' OR MATCH (ssrubr_slug) AGAINST ('(+taille +haie)')) AND sk.ssrubr_id='14' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

35. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='14' AND actu_niveau=0 ORDER BY actu_ordre DESC

36. 0.0009

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

37. 0

    SELECT count(*) as nbwish FROM wish

38. 0.0495

    SELECT note.*, post.util_prenom as postp, post.util_nom as postn, dest.util_prenom as destp, dest.util_nom as destn, w.wish_id, w.wish_desc, w.fami_id FROM note, util_info dest, util_info post, wish w WHERE note.wish_id=w.wish_id AND note.post_util_id=post.util_id AND note.dest_util_id=dest.util_id AND note_visu IN (1,2,3,4) AND post_util_id<>'7' ORDER BY note_date DESC, note_hour DESC

38 requetes sql en 0.2089