Location nettoyeur vitres à 92380 Garches

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

   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('92' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='92380' AND ville_nom like '%garches%' 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 '%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

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='92380'

12. 0.0026

    SELECT ville_cp, ROUND((((acos(sin((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.661835678816 AND ville_latitude_deg<49.021564321184 AND ville_longitude_deg>1.9100383622724 AND ville_longitude_deg<2.4566216377276 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

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

14. 0.0006

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='110' AND ssrubr_id='1017' AND wish_visu IN (1,6,10) AND wish_cp like '92380%'

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 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

17. 0.0001

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

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='92380'

19. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.661835678816 AND ville_latitude_deg<49.021564321184 AND ville_longitude_deg>1.9100383622724 AND ville_longitude_deg<2.4566216377276 HAVING distance <= 20 ORDER BY distance ASC

20. 0.008

    SELECT ville_cp, ROUND((((acos(sin((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.392039197041 AND ville_latitude_deg<49.291360802959 AND ville_longitude_deg>1.500095014092 AND ville_longitude_deg<2.866564985908 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0021

    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((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- 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='1017' AND wish_visu IN (1,6,10) AND wish_cp IN (92380,92380,92420,92430,92410,92210,78170,92310,78290,92150,92800,78380,78140,78150,92500,92370,78220,78150,92100,78400,78430,92190,92360,78000,92000,92130,78560,78870,92200,92140,78160,92400,92250,78110,78420,78350,78800,78590,92170,78750,92320,78360,78230,92350,92240,78620,78530,78350,92700,78112,78210,92220,92300,78100,92260,92330,78590,92120,78330,92290,92270,95870,91570,92110,92600,78117,94250,78600,91370,94110,78280,75006,75015,75012,75014,75009,75008,75010,75011,75013,75007,75005,75020,75001,75019,75018,75017,75116,75000,75016,75002,75004,75003,78500,91400,91430,78450,78860,92340,78600,91430,93400,78240,94240,94231,94230,94233,94239,94237,94234,94235,94236,94238,94232,95100,78390,92230,92160,78117,94270,78180,78240,95530,78300,91300,94260,78960,94800,91190,78450,91190,91120,95110,94550,78114,94200,94205,78340,78190,92390,93450,93800,78470,95210,95218,95370,91400,95240,91440,94150,78810,95130,78955,78260,91320,93210,93200,91140,93310,78630,93120,93300,94320,95120,78700,91160,95880,94160,93500,94400,78470,93170,78370,94220,78470,93430,95220,94140,91940,78570,95230,91380,91160,95130,91140,91190,91940,78670,78670,78990,94300,95360,93100,78810,78460,91160,94310,94390,78121,93260,93230,94700,93240,94600,95600,95170,78570,91420,93380,91550,95250,91940,95480,78850,95580,78780,95580,93350,78320,95410,78320) 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 (68798,122442,269803,309478,343909,377769,429944)

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 = 68798 AND W.type_id = 1) OR (W.util_id <> 68798 AND W.type_id = 2)) AND (M.post_util_id = 68798 OR M.dest_util_id = 68798) 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=68798 AND note_visu IN (1,3,4)

25. 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 = 122442 AND W.type_id = 1) OR (W.util_id <> 122442 AND W.type_id = 2)) AND (M.post_util_id = 122442 OR M.dest_util_id = 122442) 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=122442 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 = 269803 AND W.type_id = 1) OR (W.util_id <> 269803 AND W.type_id = 2)) AND (M.post_util_id = 269803 OR M.dest_util_id = 269803) 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=269803 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 = 309478 AND W.type_id = 1) OR (W.util_id <> 309478 AND W.type_id = 2)) AND (M.post_util_id = 309478 OR M.dest_util_id = 309478) 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=309478 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 = 343909 AND W.type_id = 1) OR (W.util_id <> 343909 AND W.type_id = 2)) AND (M.post_util_id = 343909 OR M.dest_util_id = 343909) 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=343909 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 = 377769 AND W.type_id = 1) OR (W.util_id <> 377769 AND W.type_id = 2)) AND (M.post_util_id = 377769 OR M.dest_util_id = 377769) 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=377769 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 = 429944 AND W.type_id = 1) OR (W.util_id <> 429944 AND W.type_id = 2)) AND (M.post_util_id = 429944 OR M.dest_util_id = 429944) 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=429944 AND note_visu IN (1,3,4)

37. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='92380'

38. 0.0025

    SELECT ville_cp, ROUND((((acos(sin((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.661835678816 AND ville_latitude_deg<49.021564321184 AND ville_longitude_deg>1.9100383622724 AND ville_longitude_deg<2.4566216377276 HAVING distance <= 20 ORDER BY distance ASC

39. 0.0061

    SELECT ville_cp, ROUND((((acos(sin((48.8417*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8417*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.18333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.392039197041 AND ville_latitude_deg<49.291360802959 AND ville_longitude_deg>1.500095014092 AND ville_longitude_deg<2.866564985908 HAVING distance <= 50 ORDER BY distance ASC

40. 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 (1017)

41. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (122442,429944,377769,269803,68798,343909,309478)

42. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (122442,429944,377769,269803,68798,343909,309478)

43. 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

44. 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 <> 1017 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

45. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='1017' AND actu_niveau=0 ORDER BY actu_ordre DESC

46. 0

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

47. 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

48. 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

49. 0.0009

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

50. 0.0223

    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'

51. 0.0166

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

51 requetes sql en 0.0695