[Corrigé 3.2.37] Erreur export CSV Statistiques
Pouvez-vous vérifier que l'adresse IP affichée sur cette ligne correspond bien à l'adresse IP affichée dans la section Administration > Système > Client > IP
GestSup: 3.2.47 | Debian: 12 | Apache: 2.4.59 | MariaDB: 11.5.2 | PHP: 8.3.12 | https://doc.gestsup.fr/
Pouvez-vous transmettre l'URL du bouton export csv
GestSup: 3.2.47 | Debian: 12 | Apache: 2.4.59 | MariaDB: 11.5.2 | PHP: 8.3.12 | https://doc.gestsup.fr/
Voici l'URL : https://www.tournus-equipement.com/gest ... 3&userid=1
Pouvez-vous vous activer le mode débug de l'application et indiquer si des erreurs sont affichées sur la page des statistiques.
GestSup: 3.2.47 | Debian: 12 | Apache: 2.4.59 | MariaDB: 11.5.2 | PHP: 8.3.12 | https://doc.gestsup.fr/
Voici ce qu'il y a d'afficher avec le mode debug sur la page statistiques :
DEBUG MODE :
VAR: where_service= | where_agency= | POST_tech=% | POST_service=% | POST_agency=% | POST_state=% | cnt_agency= | cnt_service=
Filtre :
Tous les services
Tous les types
Tous les techniciens
Toutes les catégories
Toutes les criticités
Tous les états
Période :
Août
2023
SELECT COUNT(`tincidents`.`id`) FROM `tincidents`,`tusers` WHERE `tincidents`.`user`=`tusers`.`id` AND `tusers`.`company` LIKE '%' AND `tincidents`.`technician` LIKE '%' AND `tincidents`.`criticality` LIKE '%' AND `tincidents`.`type` LIKE '%' AND `tincidents`.`category` LIKE '%' AND `tincidents`.`u_service` LIKE '%' AND tincidents.state LIKE '%' AND `tincidents`.`date_create` NOT LIKE '0000-00-00 00:00:00' AND `tincidents`.`date_create` LIKE '2023-08-%' AND `tincidents`.`disable`='0'
SELECT day(`tincidents`.`date_create`) AS x,COUNT(`tincidents`.`id`) AS y FROM `tincidents`,`tusers` WHERE `tincidents`.`user`=`tusers`.`id` AND `tusers`.`company` LIKE '%' AND `tincidents`.`technician` LIKE '%' AND `tincidents`.`u_service` LIKE '%' AND tincidents.state LIKE '%' AND `tincidents`.`criticality` LIKE '%' AND `tincidents`.`type` LIKE '%' AND `tincidents`.`category` LIKE '%' AND `tincidents`.`date_create` NOT LIKE '0000-00-00 00:00:00' AND `tincidents`.`date_create` LIKE '2023-08-%' AND `tincidents`.`disable`='0' GROUP BY x ORDER BY x
Array ( [0] => 1 )
[2,1]
Array ( [0] => 3 )
[1,3]
SELECT CONCAT_WS('. ', left(tusers.firstname, 1), tusers.lastname) AS technician, tgroups.name AS group_name, COUNT(*) as tickets FROM tincidents INNER JOIN tusers ON (tincidents.technician=tusers.id) INNER JOIN tgroups ON (tincidents.t_group=tgroups.id) WHERE tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.disable LIKE '0' GROUP BY tusers.id,tgroups.id ORDER by tickets DESC
SELECT ttypes.name as type, COUNT(*) as nb FROM tincidents INNER JOIN ttypes ON (tincidents.type=ttypes.id) WHERE tincidents.disable LIKE '0' AND tincidents.technician LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY ttypes.id ORDER BY nb DESC
SELECT tstates.name as state, COUNT(*) as nb FROM tincidents INNER JOIN tstates ON (tincidents.state=tstates.id) WHERE tincidents.disable LIKE '0' AND tincidents.technician LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tstates.number ORDER BY nb DESC
SELECT tcategory.name as cat, COUNT(*) as nb FROM tincidents INNER JOIN tcategory ON (tincidents.category=tcategory.id) WHERE tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcategory.name ORDER BY nb DESC limit 0,10
SELECT tservices.name as service, COUNT(*) as nb FROM tincidents, tservices WHERE tservices.id=tincidents.u_service AND tincidents.disable='0' AND tincidents.u_service!='0' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tservices.name ORDER BY nb DESC
SELECT tcompany.name AS company, COUNT(*) AS nb FROM tincidents, tcompany, tusers WHERE tcompany.id=tusers.company AND tusers.id=tincidents.user AND tincidents.disable='0' AND tusers.company!='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcompany.name ORDER BY nb DESC
SELECT tcompany.name AS company, COUNT(*) AS nb FROM tincidents, tcompany, tusers WHERE tcompany.id=tusers.company AND tusers.id=tincidents.user AND tincidents.disable='0' AND tusers.company!='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcompany.name ORDER BY nb DESC
SELECT tcategory.name AS technicien, ((SUM(tincidents.time_hope)-SUM(tincidents.time)))/60 AS time FROM `tincidents` INNER JOIN tcategory ON (tincidents.category=tcategory.id ) WHERE tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.disable='0' AND tincidents.time_hope-tincidents.time > 0 AND (tincidents.state='1' OR tincidents.state='2' OR tincidents.state='6' ) GROUP BY tcategory.name ORDER BY time DESC
Délais moyen de résolution
SELECT tusers.firstname, tusers.lastname, ROUND(AVG(TO_DAYS(date_res) - TO_DAYS(date_create))) as jour FROM tincidents INNER JOIN tusers ON (tincidents.technician=tusers.id ) WHERE tincidents.technician NOT LIKE '0' AND tincidents.date_res NOT LIKE '0000-00-00' AND tincidents.date_create NOT LIKE '0000-00-00' AND tincidents.state='3' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.disable='0' GROUP BY tincidents.technician ORDER BY jour ASC
Techniciens jours
Tickets par priorité
SELECT tpriority.name, count(*) AS number FROM tincidents INNER JOIN tpriority ON (tincidents.priority=tpriority.id ) WHERE tincidents.disable='0' AND tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tincidents.priority ORDER BY tpriority.number ASC
Priorité Tickets
Très basse 3
Top 10 des demandeurs
SELECT tusers.firstname AS Util, tusers.lastname, count(*) AS demandes FROM tincidents INNER JOIN tusers ON (tincidents.user=tusers.id ) WHERE tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tincidents.user ORDER BY demandes DESC LIMIT 10
Utilisateurs Tickets
X 1
X 1
X 1
TOP 10 demandeurs de temps
SELECT tusers.firstname AS Util, tusers.lastname, sum(time) AS temps FROM tincidents INNER JOIN tusers ON (tincidents.user=tusers.id) WHERE tincidents.time NOT LIKE '0' AND tincidents.time NOT LIKE '0' AND tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' GROUP BY tincidents.user ORDER BY sum(time) DESC limit 10
Utilisateurs Heures
X 0 h
Xl 0 h
X 0 h
Top jour de la semaine
SELECT DAYOFWEEK(`date_create`) AS day,COUNT(`id`) AS ticket_number FROM `tincidents` WHERE date_create!='0000-00-00 00:00:00' AND disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' GROUP BY DAYOFWEEK(date_create) ORDER BY FIELD(day,'1'), day ;
jour Tickets
Mardi 3
Répartition des temps par statuts
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1041 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.id
ANALYSE TICKET: 1041 THREAD=11455: 2023-06-02 10:16:38 type 1 state 0 [ATTRIBUTION 1]
ANALYSE TICKET: 1041 THREAD=11456: 2023-06-02 10:16:38 type 5 state 1
ANALYSE TICKET: 1041 THREAD=11516: 2023-06-05 11:10:59 type 5 state 2 [WAIT TECH 2_4]
ANALYSE TICKET: 1041 THREAD=12352: 2023-08-02 11:41:05 type 4 state 0 [CURRENT 30_90]
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1116 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1116 THREAD=12338: 2023-08-01 08:59:49 type 5 state 5
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1117 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1117 THREAD=12339: 2023-08-01 11:14:36 type 1 state 0 [ATTRIBUTION 1]
ANALYSE TICKET: 1117 THREAD=12340: 2023-08-01 11:14:36 type 5 state 6
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1118 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1118 THREAD=12344: 2023-08-01 11:25:53 type 5 state 5 [WAIT USER 1]
Ticket analysed: 4
TOTAL
ANALYSE TICKET: 1041 day 62 [CLOSE 30_90]
États Inférieur 1 jour 2 à 4 jours 5 à 10 jours 10 à 30 jours 30 à 90 jours Plus de 90 jours
Temps passé Non attribué 100% (2 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps passé Attente PEC 0% (0 tickets) 100% (1 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps passé En cours 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 100% (1 tickets) 0% (0 tickets)
Temps passé Attente retour 100% (1 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps total de traitement 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 100% (1 tickets) 0% (0 tickets)
DEBUG MODE :
VAR: where_service= | where_agency= | POST_tech=% | POST_service=% | POST_agency=% | POST_state=% | cnt_agency= | cnt_service=
Filtre :
Tous les services
Tous les types
Tous les techniciens
Toutes les catégories
Toutes les criticités
Tous les états
Période :
Août
2023
SELECT COUNT(`tincidents`.`id`) FROM `tincidents`,`tusers` WHERE `tincidents`.`user`=`tusers`.`id` AND `tusers`.`company` LIKE '%' AND `tincidents`.`technician` LIKE '%' AND `tincidents`.`criticality` LIKE '%' AND `tincidents`.`type` LIKE '%' AND `tincidents`.`category` LIKE '%' AND `tincidents`.`u_service` LIKE '%' AND tincidents.state LIKE '%' AND `tincidents`.`date_create` NOT LIKE '0000-00-00 00:00:00' AND `tincidents`.`date_create` LIKE '2023-08-%' AND `tincidents`.`disable`='0'
SELECT day(`tincidents`.`date_create`) AS x,COUNT(`tincidents`.`id`) AS y FROM `tincidents`,`tusers` WHERE `tincidents`.`user`=`tusers`.`id` AND `tusers`.`company` LIKE '%' AND `tincidents`.`technician` LIKE '%' AND `tincidents`.`u_service` LIKE '%' AND tincidents.state LIKE '%' AND `tincidents`.`criticality` LIKE '%' AND `tincidents`.`type` LIKE '%' AND `tincidents`.`category` LIKE '%' AND `tincidents`.`date_create` NOT LIKE '0000-00-00 00:00:00' AND `tincidents`.`date_create` LIKE '2023-08-%' AND `tincidents`.`disable`='0' GROUP BY x ORDER BY x
Array ( [0] => 1 )
[2,1]
Array ( [0] => 3 )
[1,3]
SELECT CONCAT_WS('. ', left(tusers.firstname, 1), tusers.lastname) AS technician, tgroups.name AS group_name, COUNT(*) as tickets FROM tincidents INNER JOIN tusers ON (tincidents.technician=tusers.id) INNER JOIN tgroups ON (tincidents.t_group=tgroups.id) WHERE tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.disable LIKE '0' GROUP BY tusers.id,tgroups.id ORDER by tickets DESC
SELECT ttypes.name as type, COUNT(*) as nb FROM tincidents INNER JOIN ttypes ON (tincidents.type=ttypes.id) WHERE tincidents.disable LIKE '0' AND tincidents.technician LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY ttypes.id ORDER BY nb DESC
SELECT tstates.name as state, COUNT(*) as nb FROM tincidents INNER JOIN tstates ON (tincidents.state=tstates.id) WHERE tincidents.disable LIKE '0' AND tincidents.technician LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tstates.number ORDER BY nb DESC
SELECT tcategory.name as cat, COUNT(*) as nb FROM tincidents INNER JOIN tcategory ON (tincidents.category=tcategory.id) WHERE tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcategory.name ORDER BY nb DESC limit 0,10
SELECT tservices.name as service, COUNT(*) as nb FROM tincidents, tservices WHERE tservices.id=tincidents.u_service AND tincidents.disable='0' AND tincidents.u_service!='0' AND tincidents.type LIKE '%' AND criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tservices.name ORDER BY nb DESC
SELECT tcompany.name AS company, COUNT(*) AS nb FROM tincidents, tcompany, tusers WHERE tcompany.id=tusers.company AND tusers.id=tincidents.user AND tincidents.disable='0' AND tusers.company!='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcompany.name ORDER BY nb DESC
SELECT tcompany.name AS company, COUNT(*) AS nb FROM tincidents, tcompany, tusers WHERE tcompany.id=tusers.company AND tusers.id=tincidents.user AND tincidents.disable='0' AND tusers.company!='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.technician LIKE '%' GROUP BY tcompany.name ORDER BY nb DESC
SELECT tcategory.name AS technicien, ((SUM(tincidents.time_hope)-SUM(tincidents.time)))/60 AS time FROM `tincidents` INNER JOIN tcategory ON (tincidents.category=tcategory.id ) WHERE tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND criticality like '%' AND tincidents.category LIKE '%' AND tincidents.disable='0' AND tincidents.time_hope-tincidents.time > 0 AND (tincidents.state='1' OR tincidents.state='2' OR tincidents.state='6' ) GROUP BY tcategory.name ORDER BY time DESC
Délais moyen de résolution
SELECT tusers.firstname, tusers.lastname, ROUND(AVG(TO_DAYS(date_res) - TO_DAYS(date_create))) as jour FROM tincidents INNER JOIN tusers ON (tincidents.technician=tusers.id ) WHERE tincidents.technician NOT LIKE '0' AND tincidents.date_res NOT LIKE '0000-00-00' AND tincidents.date_create NOT LIKE '0000-00-00' AND tincidents.state='3' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.disable='0' GROUP BY tincidents.technician ORDER BY jour ASC
Techniciens jours
Tickets par priorité
SELECT tpriority.name, count(*) AS number FROM tincidents INNER JOIN tpriority ON (tincidents.priority=tpriority.id ) WHERE tincidents.disable='0' AND tincidents.technician LIKE '%' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tincidents.priority ORDER BY tpriority.number ASC
Priorité Tickets
Très basse 3
Top 10 des demandeurs
SELECT tusers.firstname AS Util, tusers.lastname, count(*) AS demandes FROM tincidents INNER JOIN tusers ON (tincidents.user=tusers.id ) WHERE tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' GROUP BY tincidents.user ORDER BY demandes DESC LIMIT 10
Utilisateurs Tickets
X 1
X 1
X 1
TOP 10 demandeurs de temps
SELECT tusers.firstname AS Util, tusers.lastname, sum(time) AS temps FROM tincidents INNER JOIN tusers ON (tincidents.user=tusers.id) WHERE tincidents.time NOT LIKE '0' AND tincidents.time NOT LIKE '0' AND tincidents.disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' GROUP BY tincidents.user ORDER BY sum(time) DESC limit 10
Utilisateurs Heures
X 0 h
Xl 0 h
X 0 h
Top jour de la semaine
SELECT DAYOFWEEK(`date_create`) AS day,COUNT(`id`) AS ticket_number FROM `tincidents` WHERE date_create!='0000-00-00 00:00:00' AND disable='0' AND tincidents.type LIKE '%' AND tincidents.criticality like '%' AND tincidents.category LIKE '%' AND tincidents.date_create LIKE '%-08-%' AND tincidents.date_create LIKE '2023-%' AND tincidents.u_service LIKE '%' AND tincidents.state LIKE '%' GROUP BY DAYOFWEEK(date_create) ORDER BY FIELD(day,'1'), day ;
jour Tickets
Mardi 3
Répartition des temps par statuts
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1041 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.id
ANALYSE TICKET: 1041 THREAD=11455: 2023-06-02 10:16:38 type 1 state 0 [ATTRIBUTION 1]
ANALYSE TICKET: 1041 THREAD=11456: 2023-06-02 10:16:38 type 5 state 1
ANALYSE TICKET: 1041 THREAD=11516: 2023-06-05 11:10:59 type 5 state 2 [WAIT TECH 2_4]
ANALYSE TICKET: 1041 THREAD=12352: 2023-08-02 11:41:05 type 4 state 0 [CURRENT 30_90]
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1116 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1116 THREAD=12338: 2023-08-01 08:59:49 type 5 state 5
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1117 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1117 THREAD=12339: 2023-08-01 11:14:36 type 1 state 0 [ATTRIBUTION 1]
ANALYSE TICKET: 1117 THREAD=12340: 2023-08-01 11:14:36 type 5 state 6
SELECT tthreads.id, tthreads.date, tthreads.type, tthreads.state FROM tthreads INNER JOIN tincidents ON tincidents.id=tthreads.ticket WHERE tincidents.technician LIKE '%' AND tthreads.ticket=1118 AND tthreads.type!=0 AND tthreads.type!=3 AND tthreads.type!=2 ORDER BY tthreads.idANALYSE TICKET: 1118 THREAD=12344: 2023-08-01 11:25:53 type 5 state 5 [WAIT USER 1]
Ticket analysed: 4
TOTAL
ANALYSE TICKET: 1041 day 62 [CLOSE 30_90]
États Inférieur 1 jour 2 à 4 jours 5 à 10 jours 10 à 30 jours 30 à 90 jours Plus de 90 jours
Temps passé Non attribué 100% (2 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps passé Attente PEC 0% (0 tickets) 100% (1 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps passé En cours 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 100% (1 tickets) 0% (0 tickets)
Temps passé Attente retour 100% (1 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets)
Temps total de traitement 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 0% (0 tickets) 100% (1 tickets) 0% (0 tickets)
Aucune erreur semble s'afficher, lors de l'affichage de la page statistiques, si l'utilisateur à le droit "stat", un jeton est généré dans la table token, il semblerai qu'il ne soit pas généré dans votre cas, car l'impression d'écran du token transmises concerne les tickets.
Pouvez-vous rafraichir la page statistiques sans lancer l'export puis consulter le dernier token en base de données et transmettre une impression écran
Pouvez-vous rafraichir la page statistiques sans lancer l'export puis consulter le dernier token en base de données et transmettre une impression écran
GestSup: 3.2.47 | Debian: 12 | Apache: 2.4.59 | MariaDB: 11.5.2 | PHP: 8.3.12 | https://doc.gestsup.fr/
Je suis connecté en tant qu'administrateur et ce profil à le droit "stat" pour afficher les statistiques
Je viens d'en générer 1, je n'avais juste pas filtrer par date... sorry
Je viens d'en générer 1, je n'avais juste pas filtrer par date... sorry
- Fichiers joints
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- Capture.JPG (24.23 Kio) Vu 1563 fois
A priori l'adresse ip du client n'est pas correctement renseignée en base de données il s'agit pourtant de la variable $_SERVER['REMOTE_ADDR'] qui est utilisé dans la section système > client.
Pouvez-vous indiquer la version affichée dans le fichier /stat.php
Ainsi que le bloc "generate stat token access"
Pouvez-vous indiquer la version affichée dans le fichier /stat.php
Ainsi que le bloc "generate stat token access"
GestSup: 3.2.47 | Debian: 12 | Apache: 2.4.59 | MariaDB: 11.5.2 | PHP: 8.3.12 | https://doc.gestsup.fr/