Location valise diagnostic à 59148 Flines-lez-raches

1. 0.0001

   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='outillage-mecanique-automobile'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=227

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('59' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='59148' AND ville_nom like '%flines%lez%raches%' 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. 0.0001

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%valise%diag%auto%' OR ssrubr_title like '%valise%diag%auto%' OR ssrubr_slug like '%valise%diag%auto%') AND cate_id='227' 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. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='59148'

12. 0.0027

    SELECT ville_cp, ROUND((((acos(sin((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.246835678816 AND ville_latitude_deg<50.606564321184 AND ville_longitude_deg>2.9007267116002 AND ville_longitude_deg<3.4653932883998 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='valise diagnostique; valise diag auto; valise diag'

14. 0.0002

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp like '59148%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=227

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug='valise-diagnostique;-valise-diag-auto;-valise-diag' OR (ssrubr_title like '%valise diagnostique; valise diag auto; valise diag%')) AND cate_id='227' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='valise-diag-auto' AND cate_id='227'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='59148'

19. 0.0025

    SELECT ville_cp, ROUND((((acos(sin((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.246835678816 AND ville_latitude_deg<50.606564321184 AND ville_longitude_deg>2.9007267116002 AND ville_longitude_deg<3.4653932883998 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0156

    SELECT ville_cp, ROUND((((acos(sin((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.977039197041 AND ville_latitude_deg<50.876360802959 AND ville_longitude_deg>2.4772206924927 AND ville_longitude_deg<3.8888993075073 HAVING distance <= 50 ORDER BY distance ASC

21. 0.002

    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((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- 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='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp IN (59148,59148,59310,59194,59194,59870,59870,59167,59146,59310,59310,59310,59182,59235,59119,59283,59286,59870,59283,59870,59450,59490,59246,59310,62790,59287,59176,59182,59287,59176,59710,59310,59310,59950,59870,59187,59490,59128,59870,59242,59310,59553,59553,59500,62141,59179,59169,59178,59870,59551,59162,59230,59165,59710,59239,59580,59552,59171,62970,59178,59242,59242,59230,59310,59169,59261,59690,59710,59310,59239,59171,59552,59580,59169,59215,62820,59226,59553,59169,59551,59830,59710,62112,59234,59273,59830,62119,7611,62950,59178,59151,59234,59171,62590,59169,59830,7624,59178,59133,62112,59273,62490,62117,59124,59830,59234,59226,62490,59830,59151,59172,62220,59252,7610,59830,59135,62490,59151,59252,59156,7623,59113,59133,59830,59151,59262,62490,59220,59255,59175,59172,62640,62110,59230,62490,59265,62710,7621,59247,7618,59810,59780,59151,59175,59112,59147,7502,59111,59293,62860,59252,7620,62740,7620,59135,59111,62490,59155,59152,59152,62880,59152,59158,62320,62320,59158,59220,59247,59265,7504,59147,7620,59195,7620,59139,59780,59247) 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 (260044,301081,525013)

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 = 260044 AND W.type_id = 1) OR (W.util_id <> 260044 AND W.type_id = 2)) AND (M.post_util_id = 260044 OR M.dest_util_id = 260044) 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=260044 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 = 301081 AND W.type_id = 1) OR (W.util_id <> 301081 AND W.type_id = 2)) AND (M.post_util_id = 301081 OR M.dest_util_id = 301081) 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=301081 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 = 525013 AND W.type_id = 1) OR (W.util_id <> 525013 AND W.type_id = 2)) AND (M.post_util_id = 525013 OR M.dest_util_id = 525013) 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=525013 AND note_visu IN (1,3,4)

29. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='59148'

30. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>50.246835678816 AND ville_latitude_deg<50.606564321184 AND ville_longitude_deg>2.9007267116002 AND ville_longitude_deg<3.4653932883998 HAVING distance <= 20 ORDER BY distance ASC

31. 0.0137

    SELECT ville_cp, ROUND((((acos(sin((50.4267*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((50.4267*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((3.18306- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>49.977039197041 AND ville_latitude_deg<50.876360802959 AND ville_longitude_deg>2.4772206924927 AND ville_longitude_deg<3.8888993075073 HAVING distance <= 50 ORDER BY distance ASC

32. 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 (874)

33. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (525013,301081,260044)

34. 0

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (525013,301081,260044)

35. 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='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug like '%valise diagnostique; valise diag auto; valise diag%' OR MATCH (ssrubr_slug) AGAINST ('(+valise +diagnostique; +valise +diag +auto; +valise +diag)')) AND sk.ssrubr_id='874' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

36. 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 = 227 AND ss.ssrubr_id <> 874 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

37. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='874' AND actu_niveau=0 ORDER BY actu_ordre DESC

38. 0

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

39. 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

40. 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 (227) ORDER BY ssrubr_order ASC

41. 0.001

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

42. 0.0226

    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'

43. 0.0166

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

43 requetes sql en 0.0833