Location marteau piqueur à 62138 Haisnes

1. 0.0005

   SELECT cate_title_slug FROM category WHERE fami_id IN (3,5) AND cate_title_slug<>'' AND cate_title_slug IS NOT NULL

2. 0.0002

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

3. 0.0001

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=87

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='62'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='62138' AND ville_nom like '%haisnes%' 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. 0.0003

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%marteau%piqueur%' OR ssrubr_title like '%marteau%piqueur%' OR ssrubr_slug like '%marteau%piqueur%') AND cate_id='87' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0002

   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='62138'

12. 0.0028

    SELECT ville_cp, ROUND((((acos(sin((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.353435678816 AND ville_latitude_deg<50.713164321184 AND ville_longitude_deg>2.5003592214287 AND ville_longitude_deg<3.0663007785713 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='marteau piqueur'

14. 0.0005

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='87'AND MATCH (wish_title,wish_desc) AGAINST ('+marteau piqueur*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '62138%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=87

16. 0.0005

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='marteau piqueur' OR ssrubr_slug='marteau-piqueur' OR (ssrubr_title like '%marteau piqueur%')) AND cate_id='87' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0002

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='marteau-piqueur' AND cate_id='87'

18. 0.0002

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='62138'

19. 0.003

    SELECT ville_cp, ROUND((((acos(sin((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.353435678816 AND ville_latitude_deg<50.713164321184 AND ville_longitude_deg>2.5003592214287 AND ville_longitude_deg<3.0663007785713 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0225

    SELECT ville_cp, ROUND((((acos(sin((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.083639197041 AND ville_latitude_deg<50.982960802959 AND ville_longitude_deg>2.0758969533211 AND ville_longitude_deg<3.4907630466789 HAVING distance <= 50 ORDER BY distance ASC

21. 0.2802

    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((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- 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='87' AND MATCH (wish_desc) AGAINST ('(+marteau +piqueur*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (62138,62138,59480,62138,62149,62138,62149,59496,62840,62138,62149,62149,59480,62840,59496,62136,62149,59134,62410,62138,59274,62980,62410,62113,59134,62113,62410,62980,62136,59221,62660,62410,62136,59249,59184,62400,59249,59134,62400,62113,62750,62670,62880,59185,59272,62160,62290,59136,62880,62880,62400,59112,62840,62131,62131,62114,62136,59134,62300,62131,62232,59251,62232,62232,62880,59134,59940,62160,62232,62440,59253,62218,62221,62800,62620,62840,59112,62232,59147,62920,62143,62300,59320,62530,62840,62196,59211,59320,59320,62710,62220,59147,62430,62160,59147,62199,59133,62740,59280,62350,62350,62620,62210,59320,62920,59660,62640,62420,62172,59940,62122,62920,59263,59320,62680,62940,62620,62590,62530,59320,59133,62580,62110,62153,59320,62620,62350,59320,59320,62530,62153,59940,59193,59139,62820,59840,62700,62144,59113,62122,62350,62119,59280,62320,59160,62150,59261,59181,59930,62320,62580,59850,62350,59120,59551,62690,62320,62320,62150,62950,59175,59239,62540,62150,62580,59139,62350,59239,59840,62580,62150,59162) AND type_id=1 GROUP BY wish_id

22. 0.0003

    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 = 164009 AND W.type_id = 1) OR (W.util_id <> 164009 AND W.type_id = 2)) AND (M.post_util_id = 164009 OR M.dest_util_id = 164009) 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=164009 AND note_visu IN (1,3,4)

24. 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 = 297720 AND W.type_id = 1) OR (W.util_id <> 297720 AND W.type_id = 2)) AND (M.post_util_id = 297720 OR M.dest_util_id = 297720) 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=297720 AND note_visu IN (1,3,4)

26. 0.0004

    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 = 114058 AND W.type_id = 1) OR (W.util_id <> 114058 AND W.type_id = 2)) AND (M.post_util_id = 114058 OR M.dest_util_id = 114058) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

27. 0.0029

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=114058 AND note_visu IN (1,3,4)

28. 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 = 306416 AND W.type_id = 1) OR (W.util_id <> 306416 AND W.type_id = 2)) AND (M.post_util_id = 306416 OR M.dest_util_id = 306416) 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=306416 AND note_visu IN (1,3,4)

30. 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 = 310643 AND W.type_id = 1) OR (W.util_id <> 310643 AND W.type_id = 2)) AND (M.post_util_id = 310643 OR M.dest_util_id = 310643) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

31. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=310643 AND note_visu IN (1,3,4)

32. 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 = 349390 AND W.type_id = 1) OR (W.util_id <> 349390 AND W.type_id = 2)) AND (M.post_util_id = 349390 OR M.dest_util_id = 349390) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

33. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=349390 AND note_visu IN (1,3,4)

34. 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 = 399542 AND W.type_id = 1) OR (W.util_id <> 399542 AND W.type_id = 2)) AND (M.post_util_id = 399542 OR M.dest_util_id = 399542) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

35. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=399542 AND note_visu IN (1,3,4)

36. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='62138'

37. 0.007

    SELECT ville_cp, ROUND((((acos(sin((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.353435678816 AND ville_latitude_deg<50.713164321184 AND ville_longitude_deg>2.5003592214287 AND ville_longitude_deg<3.0663007785713 HAVING distance <= 20 ORDER BY distance ASC

38. 0.0313

    SELECT ville_cp, ROUND((((acos(sin((50.5333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.5333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.78333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.083639197041 AND ville_latitude_deg<50.982960802959 AND ville_longitude_deg>2.0758969533211 AND ville_longitude_deg<3.4907630466789 HAVING distance <= 50 ORDER BY distance ASC

39. 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 (58)

40. 0.0003

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (114058,399542,310643,164009,349390,297720,306416)

41. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (114058,399542,310643,164009,349390,297720,306416)

42. 0.0005

    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=87 AND ss.fami_id=5 ORDER BY ssrubr_order LIMIT 6,100

43. 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='marteau piqueur' OR ssrubr_slug like '%marteau piqueur%' OR MATCH (ssrubr_slug) AGAINST ('(+marteau +piqueur)')) AND sk.ssrubr_id='58' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

44. 0.0005

    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 = 87 AND ss.ssrubr_id <> 58 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

45. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='58' AND actu_niveau=0 ORDER BY actu_ordre DESC

46. 0.0001

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

47. 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

48. 0.0004

    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 (87) ORDER BY ssrubr_order ASC

49. 0.0018

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

50. 0.0396

    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. 0.0293

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

51 requetes sql en 0.4299