Location autres outils à 95800 Courdimanche

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. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE filtre_dpt='95'

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='95800' AND ville_nom like '%courdimanche%' 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. 0.0022

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%autres%outils%' OR ssrubr_title like '%autres%outils%' OR ssrubr_slug like '%autres%outils%') 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='95800'

12. 0.0025

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.7256573344263 AND ville_longitude_deg<2.2743426655737 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='autres outils'

14. 0.0008

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='88'AND MATCH (wish_title,wish_desc) AGAINST ('+autres outils*' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp like '95800%'

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='autres outils' OR ssrubr_slug='autres-outils' OR (ssrubr_title like '%autres outils%')) 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='autres-outils' AND cate_id='88'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='95800'

19. 0.002

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.7256573344263 AND ville_longitude_deg<2.2743426655737 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0149

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.583639197041 AND ville_latitude_deg<49.482960802959 AND ville_longitude_deg>1.3141374218189 AND ville_longitude_deg<2.6858625781811 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0591

    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((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- 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 ('(+autres +outils*)' IN BOOLEAN MODE) AND wish_visu IN (1,6,10) AND wish_cp IN (95800,95800,95000,95180,95650,95490,95280,78740,95450,95450,78740,95650,95000,95000,78510,95650,95650,78480,95450,78570,78780,95520,95450,78250,78130,95450,95650,78570,78540,78250,95610,95300,95450,78250,78250,95300,95310,78130,78260,78700,95450,78670,78670,95830,78250,95830,78955,95450,78410,95450,95300,95450,95810,78250,78920,95450,78440,95450,78820,95640,95640,95810,78300,95450,78630,95300,95450,78410,78440,95480,95640,95430,95220,78630,95640,95640,78440,78410,95810,78440,78440,95810,78600,95420,78580,78600,95370,78440,95250,78580,95640,78240,95640,95810,78240,95540,95530,78410,78410,95750,95420,95450,95690,78126,95630,95430,95750,95240,95150,95550,78440,95740,78100,95510,78440,78680,78500,95760,78970,78230,60240,95690,78580,78360,95640,78580,78110,78440,78112,95420,78121,95810,95690,95840,95130,95420,95420,78124,78750,95690,95130,60240,95810,78440,95620,95840,95320,95420,78440,60119,95510,78420,78810,60240,78560,60119,78810,78620,60240,95420,78124,95870,95290,78160,78800,95560,95390,95110,95510,60240,78400) 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 = 183952 AND W.type_id = 1) OR (W.util_id <> 183952 AND W.type_id = 2)) AND (M.post_util_id = 183952 OR M.dest_util_id = 183952) 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=183952 AND note_visu IN (1,3,4)

24. 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 = 121775 AND W.type_id = 1) OR (W.util_id <> 121775 AND W.type_id = 2)) AND (M.post_util_id = 121775 OR M.dest_util_id = 121775) 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=121775 AND note_visu IN (1,3,4)

26. 0.0005

    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 = 311956 AND W.type_id = 1) OR (W.util_id <> 311956 AND W.type_id = 2)) AND (M.post_util_id = 311956 OR M.dest_util_id = 311956) 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=311956 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 = 516110 AND W.type_id = 1) OR (W.util_id <> 516110 AND W.type_id = 2)) AND (M.post_util_id = 516110 OR M.dest_util_id = 516110) 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=516110 AND note_visu IN (1,3,4)

30. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='95800'

31. 0.0021

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.853435678816 AND ville_latitude_deg<49.213164321184 AND ville_longitude_deg>1.7256573344263 AND ville_longitude_deg<2.2743426655737 HAVING distance <= 20 ORDER BY distance ASC

32. 0.0144

    SELECT ville_cp, ROUND((((acos(sin((49.0333*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((49.0333*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.583639197041 AND ville_latitude_deg<49.482960802959 AND ville_longitude_deg>1.3141374218189 AND ville_longitude_deg<2.6858625781811 HAVING distance <= 50 ORDER BY distance ASC

33. 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 (1175)

34. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (183952,311956,516110,121775)

35. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (183952,311956,516110,121775)

36. 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

37. 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='autres outils' OR ssrubr_slug like '%autres outils%' OR MATCH (ssrubr_slug) AGAINST ('(+autres +outils)')) AND sk.ssrubr_id='1175' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

38. 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 = 88 AND ss.ssrubr_id <> 1175 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

39. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='1175' AND actu_niveau=0 ORDER BY actu_ordre DESC

40. 0

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

41. 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

42. 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

43. 0.0009

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

44. 0.0231

    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'

45. 0.0178

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

45 requetes sql en 0.1452