Service montage meubles à 74800 Saint-sixt

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='3' AND cate_title_slug='bricolage'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=50

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('74' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='74800' AND ville_nom like '%saint%sixt%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0005

   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. 0.0002

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%montage%de%meubles%' OR ssrubr_title like '%montage%de%meubles%' OR ssrubr_slug like '%montage%de%meubles%') AND cate_id='50' 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. 0.0002

    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

11. 0.0002

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='74800'

12. 0.0033

    SELECT ville_cp, ROUND((((acos(sin((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.886835678816 AND ville_latitude_deg<46.246564321184 AND ville_longitude_deg>6.0740920288166 AND ville_longitude_deg<6.5925679711834 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='montage meuble; montage de meubles; lit cabane'

14. 0.0004

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='3' AND cate_id='50' AND ssrubr_id='600' AND wish_visu IN (1,6,10) AND wish_cp like '74800%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=50

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='3' AND (ssrubr_keywords='montage meuble; montage de meubles; lit cabane' OR ssrubr_slug='montage-meuble;-montage-de-meubles;-lit-cabane' OR (ssrubr_title like '%montage meuble; montage de meubles; lit cabane%')) AND cate_id='50' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='montage-de-meubles' AND cate_id='50'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='74800'

19. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.886835678816 AND ville_latitude_deg<46.246564321184 AND ville_longitude_deg>6.0740920288166 AND ville_longitude_deg<6.5925679711834 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0063

    SELECT ville_cp, ROUND((((acos(sin((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.617039197041 AND ville_latitude_deg<46.516360802959 AND ville_longitude_deg>5.6852294834199 AND ville_longitude_deg<6.9814305165801 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0081

    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((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- 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='3' AND cate_id='50' AND ssrubr_id='600' AND wish_visu IN (1,6,10) AND wish_cp IN (74800,74800,74800,74800,74800,74800,74800,74800,74800,74930,74130,74800,74130,74930,74130,74250,74130,74250,74570,74130,74930,74130,74250,74380,74930,74380,74250,74250,74250,74250,74570,74380,74560,74350,74130,74100,74570,74130,74350,74380,74350,74130,74490,74350,74570,74970,74380,74100,74450,74560,74460,74300,74420,74240,74160,74370,74100,74100,1255,74100,74250,74160,74950,74230,74160,74160,74100,74350,74350,74490,74370,1256,74450,1226,1243,1241,74420,1225,1231,1234,74440,74370,74950,74350,74420,74140,1224,74420,1257,74370,74160,74230,1206,74350,74300,1254,1208,74490,1227,74220,74160,1244,74300,1253,1228) AND type_id=1 GROUP BY wish_id

22. 0.0001

    SELECT util_id, util_photo, util_prenom, util_nom, stripe_account_id, util_verify FROM util_info WHERE util_id IN (141848,171816,202338,203674,218666,476553,312883,503215,549322)

23. 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 = 141848 AND W.type_id = 1) OR (W.util_id <> 141848 AND W.type_id = 2)) AND (M.post_util_id = 141848 OR M.dest_util_id = 141848) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

24. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=141848 AND note_visu IN (1,3,4)

25. 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 = 171816 AND W.type_id = 1) OR (W.util_id <> 171816 AND W.type_id = 2)) AND (M.post_util_id = 171816 OR M.dest_util_id = 171816) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

26. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=171816 AND note_visu IN (1,3,4)

27. 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 = 202338 AND W.type_id = 1) OR (W.util_id <> 202338 AND W.type_id = 2)) AND (M.post_util_id = 202338 OR M.dest_util_id = 202338) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

28. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=202338 AND note_visu IN (1,3,4)

29. 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 = 203674 AND W.type_id = 1) OR (W.util_id <> 203674 AND W.type_id = 2)) AND (M.post_util_id = 203674 OR M.dest_util_id = 203674) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

30. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=203674 AND note_visu IN (1,3,4)

31. 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 = 218666 AND W.type_id = 1) OR (W.util_id <> 218666 AND W.type_id = 2)) AND (M.post_util_id = 218666 OR M.dest_util_id = 218666) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

32. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=218666 AND note_visu IN (1,3,4)

33. 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 = 476553 AND W.type_id = 1) OR (W.util_id <> 476553 AND W.type_id = 2)) AND (M.post_util_id = 476553 OR M.dest_util_id = 476553) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

34. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=476553 AND note_visu IN (1,3,4)

35. 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 = 312883 AND W.type_id = 1) OR (W.util_id <> 312883 AND W.type_id = 2)) AND (M.post_util_id = 312883 OR M.dest_util_id = 312883) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

36. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=312883 AND note_visu IN (1,3,4)

37. 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 = 503215 AND W.type_id = 1) OR (W.util_id <> 503215 AND W.type_id = 2)) AND (M.post_util_id = 503215 OR M.dest_util_id = 503215) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

38. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=503215 AND note_visu IN (1,3,4)

39. 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 = 549322 AND W.type_id = 1) OR (W.util_id <> 549322 AND W.type_id = 2)) AND (M.post_util_id = 549322 OR M.dest_util_id = 549322) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

40. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=549322 AND note_visu IN (1,3,4)

41. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='74800'

42. 0.002

    SELECT ville_cp, ROUND((((acos(sin((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.886835678816 AND ville_latitude_deg<46.246564321184 AND ville_longitude_deg>6.0740920288166 AND ville_longitude_deg<6.5925679711834 HAVING distance <= 20 ORDER BY distance ASC

43. 0.0061

    SELECT ville_cp, ROUND((((acos(sin((46.0667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.0667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.33333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.617039197041 AND ville_latitude_deg<46.516360802959 AND ville_longitude_deg>5.6852294834199 AND ville_longitude_deg<6.9814305165801 HAVING distance <= 50 ORDER BY distance ASC

44. 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 (600)

45. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (503215,202338,171816,203674,549322,312883,141848,218666,476553)

46. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (503215,202338,171816,203674,549322,312883,141848,218666,476553)

47. 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='montage meuble; montage de meubles; lit cabane' OR ssrubr_slug like '%montage meuble; montage de meubles; lit cabane%' OR MATCH (ssrubr_slug) AGAINST ('(+montage +meuble; +montage +de +meubles; +lit +cabane)')) AND sk.ssrubr_id='600' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

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 = 3 AND ss.cate_id = 50 AND ss.ssrubr_id <> 600 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

49. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='600' AND actu_niveau=0 ORDER BY actu_ordre DESC

50. 0

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

51. 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='3' AND cate_cate_id IS NULL ORDER BY cate_order ASC

52. 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 (50) ORDER BY ssrubr_order ASC

53. 0.0009

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

54. 0.0254

    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'

55. 0.0172

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

55 requetes sql en 0.0776