Location taille haie à 78520 Limay

1. 0.0002

   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='materiel-jardinage'

3. 0.0001

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

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='78'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='78520' AND ville_nom like '%limay%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0006

   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%haie%' OR ssrubr_title like '%taille%haie%' OR ssrubr_slug like '%taille%haie%') AND cate_id='88' 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. 0.0003

    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='78520'

12. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.4256573344263 AND ville_longitude_deg<1.9743426655737 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='taille haie'

14. 0.0006

    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 '78520%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=88

16. 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

17. 0.0001

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

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78520'

19. 0.0024

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.4256573344263 AND ville_longitude_deg<1.9743426655737 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0152

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.583639197041 AND ville_latitude_deg<49.482960802959 AND ville_longitude_deg>1.0141374218189 AND ville_longitude_deg<2.3858625781811 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0547

    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((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- 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 (78520,78520,78520,78440,95780,78270,78840,95510,78270,95510,78520,78440,95510,78200,78200,95780,78520,78710,78440,78270,78200,95510,78440,78440,95780,78200,78711,78200,78840,95510,78200,95510,78270,78440,78440,78930,27620,78270,78440,78440,78930,95710,78200,95420,95420,78270,78440,78200,27630,78200,27620,78970,78270,78250,78440,78930,78930,95420,78200,78930,78270,78820,95710,78200,95420,78200,78930,95450,95420,78980,78270,78270,78680,78980,95420,27620,95450,95710,78790,78200,78410,95450,78410,78410,78250,95420,78930,78270,95420,78250,95450,78410,27630,95420,78580,78250,78790,78790,78790,78790,78250,27630,27630,27620,78980,78980,95450,95420,78790,95450,78126,27630,95420,78270,78250,78270,78111,78130,78270,78410,78980,78580,78980,78790,95770,27200,27630,95420,78580,78790,27630,95450,27640,78770,95450,27120,27510,95450,27630,95450,95450,78740,95450,27120,78920,95420,78980,78910,78910,78130,95770,95770,95750,28260,27420,60240,78790,78770,78790,78910,28260,78124,60240,95640,95450,27120,78910,78770,27510,28260,78740,27950,60240,27420,78770,27510,78580) 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 = 209164 AND W.type_id = 1) OR (W.util_id <> 209164 AND W.type_id = 2)) AND (M.post_util_id = 209164 OR M.dest_util_id = 209164) 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=209164 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 = 330483 AND W.type_id = 1) OR (W.util_id <> 330483 AND W.type_id = 2)) AND (M.post_util_id = 330483 OR M.dest_util_id = 330483) 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=330483 AND note_visu IN (1,3,4)

26. 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 = 260400 AND W.type_id = 1) OR (W.util_id <> 260400 AND W.type_id = 2)) AND (M.post_util_id = 260400 OR M.dest_util_id = 260400) 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=260400 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 = 133249 AND W.type_id = 1) OR (W.util_id <> 133249 AND W.type_id = 2)) AND (M.post_util_id = 133249 OR M.dest_util_id = 133249) 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=133249 AND note_visu IN (1,3,4)

30. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78520'

31. 0.002

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.4256573344263 AND ville_longitude_deg<1.9743426655737 HAVING distance <= 20 ORDER BY distance ASC

32. 0.0145

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((1.7- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.583639197041 AND ville_latitude_deg<49.482960802959 AND ville_longitude_deg>1.0141374218189 AND ville_longitude_deg<2.3858625781811 HAVING distance <= 50 ORDER BY distance ASC

33. 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 (14,23)

34. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (209164,133249,260400,330483)

35. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (209164,133249,260400,330483)

36. 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

37. 0.0003

    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

38. 0.0003

    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 = 88 AND ss.ssrubr_id <> 14 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

39. 0.0001

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

40. 0.0001

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

41. 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

42. 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

43. 0.0011

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

44. 0.0229

    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'

45. 0.0176

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

45 requetes sql en 0.1388