Location nettoyeur vitres à 75017 Paris

1. 0.0001

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

2. 0.0001

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=110

3. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='75'

4. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='75017' AND ville_nom like '%paris%' 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 '%nettoyeur%vitres%' OR ssrubr_title like '%nettoyeur%vitres%' OR ssrubr_slug like '%nettoyeur%vitres%') AND cate_id='110' 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='75017'

7. 0.0027

   SELECT ville_cp, ROUND((((acos(sin((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.680135678816 AND ville_latitude_deg<49.039864321184 AND ville_longitude_deg>2.0710584569437 AND ville_longitude_deg<2.6178415430563 HAVING distance <= 20 ORDER BY distance ASC

8. 0.0001

   SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='nettoyeur vitre; nettoyeur vitres'

9. 0.0014

   SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='110'AND MATCH (wish_title,wish_desc) AGAINST ('+nettoyeur vitre; nettoyeur vitres*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '75017%'

10. 0.0001

    SELECT * FROM texte WHERE cate_id=110

11. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='nettoyeur vitre; nettoyeur vitres' OR ssrubr_slug='nettoyeur-vitre;-nettoyeur-vitres' OR (ssrubr_title like '%nettoyeur vitre; nettoyeur vitres%')) AND cate_id='110' 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. 0.0002

    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='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 (110) ORDER BY ssrubr_order ASC

15. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='nettoyeur-vitres' AND cate_id='110'

16. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='75017'

17. 0.0009

    SELECT ville_cp, ROUND((((acos(sin((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.797047487586 AND ville_latitude_deg<48.922952512414 AND ville_longitude_deg>2.2487630978401 AND ville_longitude_deg<2.4401369021599 HAVING distance <= 7 ORDER BY distance ASC

18. 0.0072

    SELECT ville_cp, ROUND((((acos(sin((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.410339197041 AND ville_latitude_deg<49.309660802959 AND ville_longitude_deg>1.6609652486165 AND ville_longitude_deg<3.0279347513835 HAVING distance <= 50 ORDER BY distance ASC

19. 0.0903

    SELECT count(wish_id) as nbwish FROM wish WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='110' AND MATCH (wish_desc) AGAINST ('(+nettoyeur +vitre; +nettoyeur +vitres*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (75017,75007,75002,75000,75001,75017,75006,75116,75020,75018,75015,75019,75003,75004,75014,75013,75012,75011,75010,75009,75008,75016,75005,92170,93400,93310,94250,94270,92120,93170,92110,94205,94200,92240,93500,94160,92200,92300,93100,94300,94110,94800,93120,93300,93230,93260,92600,94220,92220,92130,92100,92400,92320,92800,92150,93450,92390,92250,93200,93210,92270,94140,94233,94235,94231,94232,94236,94237,94234,94230,94239,94238,94240,92140,92230,93000,93130,94700,92700,94400,92360,92190,92210,94410,92260,92330,92340,93350,93140,94340,93110,94120,92350,93800,94550,93240,94130,94320,92500,93430,93700,93150,93440,94170,92000,92310,94600,93250,92290,92410,95360,92380,93380,95880,95100,94150,78800,94000,95870,94260,92370,93360,92160,95218,95210,92420,92430,94390,94310,94360,95140,94100,94210,94340,78420,93320,93340,91370,94500,95500,78140,95410,95110,95170,93330,93220,95230,91320,94430,78170,78400,94380,78220,95400,91300,95120,94290,94460,94350,91570,78500,78290,78380,78360,95160,95350,95500,95400,95200,95580,95580,95130,91550,93270,94190,93600,95600,93460,93190,93390,93160,91200,78150,78350,78430,95530,94480,78000,93370,78560,91430,78150,94420,78110,94380,94370,95240,94490,94880,94880,91120,78600,94450,95350,95130,94470,91430,95440,91560,91420,95500,95680,78600,95370,91160,91380,93410,93420,95390,78230,91270,93470,77181,95500,95720,78530,78350,91160,77420,95320,77500,91140,78160,78870,91400,78750,95330,95460,91230,94510,95190,91330,78100,91260,95720)

20. 0.0538

    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((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- 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='110' AND MATCH (wish_desc) AGAINST ('(+nettoyeur +vitre; +nettoyeur +vitres*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (75017,75007,75002,75000,75001,75017,75006,75116,75020,75018,75015,75019,75003,75004,75014,75013,75012,75011,75010,75009,75008,75016,75005,92170,93400,93310,94250,94270,92120,93170,92110,94205,94200,92240,93500,94160,92200,92300,93100,94300,94110,94800,93120,93300,93230,93260,92600,94220,92220,92130,92100,92400,92320,92800,92150,93450,92390,92250,93200,93210,92270,94140,94233,94235,94231,94232,94236,94237,94234,94230,94239,94238,94240,92140,92230,93000,93130,94700,92700,94400,92360,92190,92210,94410,92260,92330,92340,93350,93140,94340,93110,94120,92350,93800,94550,93240,94130,94320,92500,93430,93700,93150,93440,94170,92000,92310,94600,93250,92290,92410,95360,92380,93380,95880,95100,94150,78800,94000,95870,94260,92370,93360,92160,95218,95210,92420,92430,94390,94310,94360,95140,94100,94210,94340,78420,93320,93340,91370,94500,95500,78140,95410,95110,95170,93330,93220,95230,91320,94430,78170,78400,94380,78220,95400,91300,95120,94290,94460,94350,91570,78500,78290,78380,78360,95160,95350,95500,95400,95200,95580,95580,95130,91550,93270,94190,93600,95600,93460,93190,93390,93160,91200,78150,78350,78430,95530,94480,78000,93370,78560,91430,78150,94420,78110,94380,94370,95240,94490,94880,94880,91120,78600,94450,95350,95130,94470,91430,95440,91560,91420,95500,95680,78600,95370,91160,91380,93410,93420,95390,78230,91270,93470,77181,95500,95720,78530,78350,91160,77420,95320,77500,91140,78160,78870,91400,78750,95330,95460,91230,94510,95190,91330,78100,91260,95720) 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='75017'

22. 0.0006

    SELECT ville_cp, ROUND((((acos(sin((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.797047487586 AND ville_latitude_deg<48.922952512414 AND ville_longitude_deg>2.2487630978401 AND ville_longitude_deg<2.4401369021599 HAVING distance <= 7 ORDER BY distance ASC

23. 0.0056

    SELECT ville_cp, ROUND((((acos(sin((48.86*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.86*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.34445- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.410339197041 AND ville_latitude_deg<49.309660802959 AND ville_longitude_deg>1.6609652486165 AND ville_longitude_deg<3.0279347513835 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 = 471981 AND W.type_id = 1) OR (W.util_id != 471981 AND W.type_id = 2)) AND (`post_util_id` = 471981 OR `dest_util_id` = 471981) 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=471981 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 = 493176 AND W.type_id = 1) OR (W.util_id != 493176 AND W.type_id = 2)) AND (`post_util_id` = 493176 OR `dest_util_id` = 493176) 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=493176 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='1017' 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 = 471981

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='1017' 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 = 493176 AND W.type_id = 1) OR (W.util_id != 493176 AND W.type_id = 2)) AND (`post_util_id` = 493176 OR `dest_util_id` = 493176) 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 = 493176

33. 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=110 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='nettoyeur vitre; nettoyeur vitres' OR ssrubr_slug like '%nettoyeur vitre; nettoyeur vitres%' OR MATCH (ssrubr_slug) AGAINST ('(+nettoyeur +vitre; +nettoyeur +vitres)')) AND sk.ssrubr_id='1017' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

35. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='1017' 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. 0.0514

    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 0.2181