Location taille haie à 74380 Nangy

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-jardinage'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=88

4. 0

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='74'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='74380' AND ville_nom like '%nangy%' 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 '%taille%haie%' OR ssrubr_title like '%taille%haie%' OR ssrubr_slug like '%taille%haie%') AND cate_id='88' 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='74380'

12. 0.0026

    SELECT ville_cp, ROUND((((acos(sin((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>46.003435678816 AND ville_latitude_deg<46.363164321184 AND ville_longitude_deg>6.0402127490206 AND ville_longitude_deg<6.5597872509794 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='taille haie'

14. 0.0004

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='88'AND MATCH (wish_title,wish_desc) AGAINST ('+taille haie*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '74380%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=88

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='taille haie' OR ssrubr_slug='taille-haie' OR (ssrubr_title like '%taille haie%')) AND cate_id='88' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='taille-haie' AND cate_id='88'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='74380'

19. 0.0025

    SELECT ville_cp, ROUND((((acos(sin((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>46.003435678816 AND ville_latitude_deg<46.363164321184 AND ville_longitude_deg>6.0402127490206 AND ville_longitude_deg<6.5597872509794 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0074

    SELECT ville_cp, ROUND((((acos(sin((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.733639197041 AND ville_latitude_deg<46.632960802959 AND ville_longitude_deg>5.6505262720886 AND ville_longitude_deg<6.9494737279114 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0542

    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((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- 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='88' AND MATCH (wish_desc) AGAINST ('(+taille +haie*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (74380,74380,74380,74380,74100,74250,74380,74380,74100,74100,74100,1243,74100,74250,74140,74100,1241,74130,74930,1254,74240,1226,74930,1244,74930,74140,74560,74420,1251,1225,1252,1253,74250,1224,74130,74800,1231,74800,1255,74250,74250,74420,74140,1223,1222,1208,74250,74890,74560,74420,74250,1207,1234,74160,74420,1206,1246,74930,74420,1245,74250,1256,1200,1240,1204,1201,1227,1205,1247,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1211,1202,74160,74890,1292,74800,1227,74140,74800,74800,74140,74490,74890,74800,1211,1212,1248,1294,1203,74420,74160,74490,1228,1212,1213,1211,1213,1209,1293,74890,74130,1257,1218,74140,74800,74800,74140,1211,1215,1219,74550,74350,74130,1220,1213,74490,1216,1219,74800,1219,74420,01210,1215,1290,1295,1232,1258,1295,1296,74140,74160,74160,1214,74350,74550,74550,74350,1239,74570,74160,1233,1217,1211,74140,01280,1217,74160,74440,1297,74140,74130,1291,74140,01210,74160,74970,1290,74200,74470,74350,1298,1286,1288) AND type_id=1 GROUP BY wish_id

22. 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 = 16947 AND W.type_id = 1) OR (W.util_id <> 16947 AND W.type_id = 2)) AND (M.post_util_id = 16947 OR M.dest_util_id = 16947) 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=16947 AND note_visu IN (1,3,4)

24. 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 = 153322 AND W.type_id = 1) OR (W.util_id <> 153322 AND W.type_id = 2)) AND (M.post_util_id = 153322 OR M.dest_util_id = 153322) 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=153322 AND note_visu IN (1,3,4)

26. 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 = 198957 AND W.type_id = 1) OR (W.util_id <> 198957 AND W.type_id = 2)) AND (M.post_util_id = 198957 OR M.dest_util_id = 198957) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

27. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=198957 AND note_visu IN (1,3,4)

28. 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 = 194275 AND W.type_id = 1) OR (W.util_id <> 194275 AND W.type_id = 2)) AND (M.post_util_id = 194275 OR M.dest_util_id = 194275) 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=194275 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 = 152931 AND W.type_id = 1) OR (W.util_id <> 152931 AND W.type_id = 2)) AND (M.post_util_id = 152931 OR M.dest_util_id = 152931) 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=152931 AND note_visu IN (1,3,4)

32. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='74380'

33. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>46.003435678816 AND ville_latitude_deg<46.363164321184 AND ville_longitude_deg>6.0402127490206 AND ville_longitude_deg<6.5597872509794 HAVING distance <= 20 ORDER BY distance ASC

34. 0.0065

    SELECT ville_cp, ROUND((((acos(sin((46.1833*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((46.1833*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((6.3- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>45.733639197041 AND ville_latitude_deg<46.632960802959 AND ville_longitude_deg>5.6505262720886 AND ville_longitude_deg<6.9494737279114 HAVING distance <= 50 ORDER BY distance ASC

35. 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 (14)

36. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (198957,153322,16947,152931,194275)

37. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (198957,153322,16947,152931,194275)

38. 0.0003

    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=88 AND ss.fami_id=5 ORDER BY ssrubr_order LIMIT 6,100

39. 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='taille haie' OR ssrubr_slug like '%taille haie%' OR MATCH (ssrubr_slug) AGAINST ('(+taille +haie)')) AND sk.ssrubr_id='14' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

40. 0.0003

    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 = 88 AND ss.ssrubr_id <> 14 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

41. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='14' 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 (88) ORDER BY ssrubr_order ASC

45. 0.0011

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

46. 0.0248

    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. 0.0169

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

47 requetes sql en 0.1237