Location remorque vélo à 14000 Caen

1. 0.0002

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

2. 0.0001

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=95

3. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='14'

4. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='14000' AND ville_nom like '%caen%' ORDER BY ville_population_2012 DESC LIMIT 0,1

5. 0.0014

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%remorque%velo%' OR ssrubr_title like '%remorque%velo%' OR ssrubr_slug like '%remorque%velo%') AND cate_id='95' 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='14000'

7. 0.0026

   SELECT ville_cp, ROUND((((acos(sin((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.003435678816 AND ville_latitude_deg<49.363164321184 AND ville_longitude_deg>-0.62517330879638 AND ville_longitude_deg<-0.074826691203624 HAVING distance <= 20 ORDER BY distance ASC

8. 0.0001

   SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='remorque vélo'

9. 0.0008

   SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='95'AND MATCH (wish_title,wish_desc) AGAINST ('+remorque vélo*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '14000%'

10. 0.0001

    SELECT * FROM texte WHERE cate_id=95

11. 0.0003

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='remorque vélo' OR ssrubr_slug='remorque-vélo' OR (ssrubr_title like '%remorque vélo%')) AND cate_id='95' 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 (95) ORDER BY ssrubr_order ASC

15. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='remorque-velo' AND cate_id='95'

16. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='14000'

17. 0.0014

    SELECT ville_cp, ROUND((((acos(sin((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.003435678816 AND ville_latitude_deg<49.363164321184 AND ville_longitude_deg>-0.62517330879638 AND ville_longitude_deg<-0.074826691203624 HAVING distance <= 20 ORDER BY distance ASC

18. 0.0043

    SELECT ville_cp, ROUND((((acos(sin((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.733639197041 AND ville_latitude_deg<49.632960802959 AND ville_longitude_deg>-1.0379392041447 AND ville_longitude_deg<0.33793920414469 HAVING distance <= 50 ORDER BY distance ASC

19. 0.036

    SELECT count(wish_id) as nbwish FROM wish WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='95' AND MATCH (wish_desc) AGAINST ('(+remorque +vélo*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (14000,14000,14200,14120,14111,14123,14280,14610,14460,14123,14730,14760,14280,14123,14112,14840,14540,14610,14840,14540,14280,14540,14550,14610,14930,14650,14930,14320,14920,14320,14610,14630,14850,14790,14790,14540,14540,14320,14970,14740,14860,14980,14850,14320,14630,14112,14320,14540,14940,14940,14940,14610,14740,14860,14790,14610,14630,14540,14970,14610,14740,14930,14440,14440,14210,14370,14210,14860,14880,14320,14440,14320,14880,14610,14670,14610,14370,14210,14210,14670,14740,14210,14121,14540,14440,14210,14530,14680,14370,14780,14610,14150,14860,14740,14210,14480,14740,14220,14540,14210,14210,14210,14210,14370,14210,14670,14740,14670,14540,14680,14830,14810,14670,14390,14480,14810,14480,14370,14220,14470,14740,14370,14210,14680,14220,14250,14480,14390,14210,14190,14220,14370,14210,14250,14670,14250,14670,14750,14190,14680,14370,14210,14480,14480,14250,14250,14990,14480,14210,14190,14220,14210,14190,14480,14470,14250,14480,14210,14480,14220,14430,14370,14250,14470,14480,14740,14480,14480,14190,14210,14310,14250,14250,14190,14190,14160,14740,14310,14370,14270,14250,14210)

20. 0.0385

    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((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- 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='95' AND MATCH (wish_desc) AGAINST ('(+remorque +vélo*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (14000,14000,14200,14120,14111,14123,14280,14610,14460,14123,14730,14760,14280,14123,14112,14840,14540,14610,14840,14540,14280,14540,14550,14610,14930,14650,14930,14320,14920,14320,14610,14630,14850,14790,14790,14540,14540,14320,14970,14740,14860,14980,14850,14320,14630,14112,14320,14540,14940,14940,14940,14610,14740,14860,14790,14610,14630,14540,14970,14610,14740,14930,14440,14440,14210,14370,14210,14860,14880,14320,14440,14320,14880,14610,14670,14610,14370,14210,14210,14670,14740,14210,14121,14540,14440,14210,14530,14680,14370,14780,14610,14150,14860,14740,14210,14480,14740,14220,14540,14210,14210,14210,14210,14370,14210,14670,14740,14670,14540,14680,14830,14810,14670,14390,14480,14810,14480,14370,14220,14470,14740,14370,14210,14680,14220,14250,14480,14390,14210,14190,14220,14370,14210,14250,14670,14250,14670,14750,14190,14680,14370,14210,14480,14480,14250,14250,14990,14480,14210,14190,14220,14210,14190,14480,14470,14250,14480,14210,14480,14220,14430,14370,14250,14470,14480,14740,14480,14480,14190,14210,14310,14250,14250,14190,14190,14160,14740,14310,14370,14270,14250,14210) 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='14000'

22. 0.0015

    SELECT ville_cp, ROUND((((acos(sin((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.003435678816 AND ville_latitude_deg<49.363164321184 AND ville_longitude_deg>-0.62517330879638 AND ville_longitude_deg<-0.074826691203624 HAVING distance <= 20 ORDER BY distance ASC

23. 0.0043

    SELECT ville_cp, ROUND((((acos(sin((49.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.35- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.733639197041 AND ville_latitude_deg<49.632960802959 AND ville_longitude_deg>-1.0379392041447 AND ville_longitude_deg<0.33793920414469 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 = 135113 AND W.type_id = 1) OR (W.util_id != 135113 AND W.type_id = 2)) AND (`post_util_id` = 135113 OR `dest_util_id` = 135113) 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=135113 AND note_visu IN (1,3,4)

26. 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='736' LIMIT 0,1

27. 0.0002

    SELECT abo_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id = 135113

28. 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=95 AND ss.fami_id=5 ORDER BY ssrubr_order LIMIT 6,100

29. 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='remorque vélo' OR ssrubr_slug like '%remorque vélo%' OR MATCH (ssrubr_slug) AGAINST ('(+remorque +vélo)')) AND sk.ssrubr_id='736' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

30. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='736' AND actu_niveau=0 ORDER BY actu_ordre DESC

31. 0.0009

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

32. 0

    SELECT count(*) as nbwish FROM wish

33. 0.0456

    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

33 requetes sql en 0.1401