Location karcher à 50810 Saint-jean-des-baisants

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-nettoyage'

3. 0.0001

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

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('50' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0002

   SELECT ville_nom FROM villes WHERE ville_cp='50810' AND ville_nom like '%saint%jean%des%baisants%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0007

   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 '%nettoyeur%haute%pression%' OR ssrubr_title like '%nettoyeur%haute%pression%' OR ssrubr_slug like '%nettoyeur%haute%pression%') AND cate_id='110' 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. 0.0002

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='50810'

12. 0.003

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-1.2414706506719 AND ville_longitude_deg<-0.69186334932809 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='nettoyeur haute pression; karcher; kärcher; nettoy'

14. 0.0002

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='110' AND ssrubr_id='745' AND wish_visu IN (1,6,10) AND wish_cp like '50810%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=110

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='nettoyeur haute pression; karcher; kärcher; nettoy' OR ssrubr_slug='nettoyeur-haute-pression;-karcher;-kärcher;-nettoy' OR (ssrubr_title like '%nettoyeur haute pression; karcher; kärcher; nettoy%')) AND cate_id='110' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

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

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='50810'

19. 0.0025

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-1.2414706506719 AND ville_longitude_deg<-0.69186334932809 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0196

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.667039197041 AND ville_latitude_deg<49.566360802959 AND ville_longitude_deg>-1.6536820508645 AND ville_longitude_deg<-0.27965194913552 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0079

    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((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- 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 ssrubr_id='745' AND wish_visu IN (1,6,10) AND wish_cp IN (50810,50810,50810,50810,50810,50680,50810,50680,50810,50810,50810,50810,50810,14490,50160,50680,50160,14490,50160,50000,50000,14490,50000,14240,14240,50160,50890,50680,50750,14240,50750,50000,50680,50160,50680,50180,14240,14490,14350,50680,50160,50680,50160,14240,14240,50750,50160,14330,50420,14490,14350,14240,50880,14330,14330,50420,50880,14490,50620,50750,50000,14240,50680,14350,14350,50750,14240,50750,50180,14240,50180,50620,50860,14710,50160,50420,50860,14490,14330,50420,14490,14240,50420,14710,14330,14330,50620,50750,14490,50750,14330,14710,50420,14490,50860,14350,50570,14350,50620,14240,50420,50620,14330,50880,14350,50750,14240,50420,50570,14260,14490,14710,14350,14310,14230,14350,14330,14490,14330,14400,14230,14260,50750,14490,50620,50570,14710,14240,14310,50750,14250,50570,14230,14350,50420,14260) 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 (120837,115542,335456,395200,366057)

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 = 120837 AND W.type_id = 1) OR (W.util_id <> 120837 AND W.type_id = 2)) AND (M.post_util_id = 120837 OR M.dest_util_id = 120837) 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=120837 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 = 115542 AND W.type_id = 1) OR (W.util_id <> 115542 AND W.type_id = 2)) AND (M.post_util_id = 115542 OR M.dest_util_id = 115542) 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=115542 AND note_visu IN (1,3,4)

27. 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 = 335456 AND W.type_id = 1) OR (W.util_id <> 335456 AND W.type_id = 2)) AND (M.post_util_id = 335456 OR M.dest_util_id = 335456) 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=335456 AND note_visu IN (1,3,4)

29. 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 = 395200 AND W.type_id = 1) OR (W.util_id <> 395200 AND W.type_id = 2)) AND (M.post_util_id = 395200 OR M.dest_util_id = 395200) 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=395200 AND note_visu IN (1,3,4)

31. 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 = 366057 AND W.type_id = 1) OR (W.util_id <> 366057 AND W.type_id = 2)) AND (M.post_util_id = 366057 OR M.dest_util_id = 366057) 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=366057 AND note_visu IN (1,3,4)

33. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='50810'

34. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.936835678816 AND ville_latitude_deg<49.296564321184 AND ville_longitude_deg>-1.2414706506719 AND ville_longitude_deg<-0.69186334932809 HAVING distance <= 20 ORDER BY distance ASC

35. 0.0179

    SELECT ville_cp, ROUND((((acos(sin((49.1167*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.1167*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((-0.966667- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.667039197041 AND ville_latitude_deg<49.566360802959 AND ville_longitude_deg>-1.6536820508645 AND ville_longitude_deg<-0.27965194913552 HAVING distance <= 50 ORDER BY distance ASC

36. 0.0002

    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 (745)

37. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (115542,366057,395200,120837,335456)

38. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (115542,366057,395200,120837,335456)

39. 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='nettoyeur haute pression; karcher; kärcher; nettoy' OR ssrubr_slug like '%nettoyeur haute pression; karcher; kärcher; nettoy%' OR MATCH (ssrubr_slug) AGAINST ('(+nettoyeur +haute +pression; +karcher; +kärcher; +nettoy)')) AND sk.ssrubr_id='745' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

40. 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 = 5 AND ss.cate_id = 110 AND ss.ssrubr_id <> 745 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

41. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='745' AND actu_niveau=0 ORDER BY actu_ordre DESC

42. 0.0001

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

43. 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

44. 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

45. 0.0009

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

46. 0.0227

    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'

47. 0.016

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

47 requetes sql en 0.0989