Some usable scripts, nothing fancy nor really relevant.
apres.c | ||
chrono.pl | ||
daemon.pl | ||
eko2.c | ||
eko.c | ||
enMajuscule.pl | ||
exoPointeurs.c | ||
function.c | ||
getpwent2.pl | ||
getpwent.pl | ||
humanornot2.pl | ||
humanornot.pl | ||
lePlusGros.pl | ||
matrice1.c | ||
matrice2.c | ||
max.pl | ||
maxcourt.pl | ||
mini_shell.c | ||
minmax.c | ||
monswap.c | ||
morceau_miroir.c | ||
multi_chrono.pl | ||
nbmots.pl | ||
README | ||
silent_cmp.pl | ||
squeeze.c | ||
strdup2.c | ||
supprime.c | ||
swapp.c | ||
testargs.c | ||
tout.c | ||
tube.pl | ||
wc.pl | ||
wordcount.c |
Hello everyone You can watch all my little scripts in C and Perl. Enjoy ! MANGEZ SELECT date, SUM(dollars) AS total_dollars, SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_dollars, SUM(quantity) AS total_qty, SUM(SUM(quantity)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_qty FROM aroma.period a, aroma.sales b, aroma.product c WHERE a.perkey = b.perkey AND c.prodkey = b.prodkey AND c.classkey = b.classkey AND year = 2006 AND month = 'JAN' AND prod_name = 'Aroma Roma' GROUP BY date ORDER BY date; SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) OVER = OLAP aggregation function MOVING Average = moyenne sur quelques jours pour faire une courbe de la moyenne (moins en dents de scie) SELECT date, SUM(dollars) AS total_dollars, SUM(SUM(dollars)) OVER(PARTITION BY week ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_dollars, SUM(quantity) AS total_qty, SUM(SUM(quantity)) OVER(PARTITION BY week ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_qty FROM aroma.period a, aroma.sales b, aroma.product c WHERE a.perkey = b.perkey AND c.prodkey = b.prodkey AND c.classkey = b.classkey AND year = 2006 AND month = 'JAN' AND prod_name = 'Aroma Roma' GROUP BY week, date ORDER BY week, date; PARTITION BY week = Faire la somme mais par semaine SELECT date, SUM(dollars) AS total_dollars, SUM(SUM(dollars)) OVER (PARTITION BY week ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_dollars, SUM(quantity) AS total_qty, SUM(SUM(quantity)) OVER(PARTITION BY week ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_qty, week FROM aroma.period a, aroma.sales b, aroma.product c WHERE a.perkey = b.perkey AND c.prodkey = b.prodkey AND c.classkey = b.classkey AND year = 2006 AND month = 'JAN' AND prod_name = 'Aroma Roma' GROUP BY week, date ORDER BY week, date; SELECT prod_name, SUM(dollars) AS total_sales, SUM(quantity) AS total_qty, DEC(sum(dollars)/sum(quantity), 7, 2) AS price FROM aroma.product a, aroma.sales b, aroma.period c WHERE a.prodkey = b.prodkey AND a.classkey = b.classkey AND c.perkey = b.perkey AND year = 2004 GROUP BY prod_name ORDER BY price; dec(sum(dollars)/sum(quantity), 7, 2) AS price SELECT t1.date, sales_cume_west, sales_cume_south, sales_cume_west - sales_cume_south AS west_vs_south FROM (SELECT date, SUM(dollars) AS total_sales, SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS sales_cume_west FROM aroma.market a, aroma.store b, aroma.sales c, aroma.period d WHERE a.mktkey = b.mktkey AND b.storekey = c.storekey AND d.perkey = c.perkey AND year = 2006 AND month = 'MAR' AND region = 'West' GROUP BY date) AS t1 JOIN (SELECT date, SUM(dollars) AS total_sales, SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS sales_cume_south FROM aroma.market a, aroma.store b, aroma.sales c, aroma.period d WHERE a.mktkey = b.mktkey AND b.storekey = c.storekey AND d.perkey = c.perkey AND year = 2006 AND month = 'MAR' AND region = 'South' GROUP BY date) AS t2 ON t1.date = t2.date ORDER BY date; SELECT city, week, SUM(dollars) AS sales, DEC(AVG(SUM(dollars)) OVER(partition by city ORDER BY city, week ROWS 2 PRECEDING),7,2) AS mov_avg, SUM(SUM(dollars)) OVER(PARTITION BY city ORDER BY week ROWS unbounded PRECEDING) AS run_sales FROM aroma.store a, aroma.sales b, aroma.period c WHERE a.storekey = b.storekey AND c.perkey = b.perkey AND qtr = 'Q3_05' AND city IN ('San Jose', 'Miami') GROUP BY city, week; ROWS n PRECEDING (ou on peut aussi dire : FOLLOWING ) SELECT date, SUM(quantity) AS day_qty, DEC(SUM(SUM(quantity)) OVER(ORDER BY date ROWS 6 PRECEDING),7,2) AS mov_sum FROM aroma.sales a, aroma.period b, aroma.product c WHERE b.perkey = a.perkey AND c.classkey = a.classkey AND c.prodkey = a.prodkey AND year = 2006 AND month = 'MAR' AND prod_name = 'Demitasse Ms' GROUP BY date ORDER BY date; REPONSES : # Total du montant des ventes par catégorie select c.class_type, sum(s.dollars) as total from aroma.class c, aroma.sales s, aroma.product p where c.classkey = p.classkey and p.prodkey = s.prodkey and p.classkey = s.classkey group by c.class_type order by total desc # Pourcentage du montant des ventes de chaque catégorie select c.class_type, dec(100*sum(s.dollars)/(select sum(dollars) from aroma.sales),7,0) as part from aroma.class c, aroma.sales s, aroma.product p where c.classkey = p.classkey and p.prodkey = s.prodkey and p.classkey = s.classkey group by c.class_type order by part desc # Classement des ventes par classes de produit select c.class_type, dec(100*sum(s.dollars)/(select sum(dollars) from aroma.sales),7,0) as part, rank() over(order by sum(s.dollars) desc) as rang from aroma.class c, aroma.sales s, aroma.product p where c.classkey = p.classkey and p.prodkey = s.prodkey and p.classkey = s.classkey group by c.class_type order by part desc # Produit le plus vendu, pourcentage correspondant select p.prodkey, p.classkey, p.prod_name, p.pkg_type, dec(100*sum(s.dollars)/(select sum(dollars) from aroma.sales),7,0) as part from aroma.sales s, aroma.product p where p.prodkey = s.prodkey and p.classkey = s.classkey group by p.prodkey, p.classkey, p.prod_name, p.pkg_type order by part desc # Montant des ventes des produits par semaine select p.prodkey, p.classkey, p.prod_name, p.pkg_type, t.week, sum(s.dollars) as montant from aroma.sales s, aroma.product p, aroma.period t where p.prodkey = s.prodkey and p.classkey = s.classkey and s.perkey = t.perkey group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week order by t.week # Classement des produits par montant des ventes décroissant pour chaque semaine select p.prodkey, p.classkey, p.prod_name, p.pkg_type, t.week, sum(s.dollars) as montant, rank() over(partition by week order by week, sum(s.dollars) desc) as rang from aroma.sales s, aroma.product p, aroma.period t where p.prodkey = s.prodkey and p.classkey = s.classkey and s.perkey = t.perkey group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week order by t.week, rang # Classement moyen des produits en vente hebdomadaire select t.prodkey, t.classkey, t.prod_name, t.pkg_type, avg(rang) as rang_moyen from (select p.prodkey, p.classkey, p.prod_name, p.pkg_type, t.week, sum(s.dollars) as montant, rank() over(partition by week order by week, sum(s.dollars) desc) as rang from aroma.sales s, aroma.product p, aroma.period t where p.prodkey = s.prodkey and p.classkey = s.classkey and s.perkey = t.perkey group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week order by t.week, rang) as t(prodkey,classkey,prod_name,pkg_type,week,montant,rang) group by t.prodkey,t.classkey, t.prod_name, t.pkg_type # Montant moyen des ventes par jour de la semaine select ti.day, avg(ti.montant) as moyenne from (select t.day,sum(dollars) from aroma.sales s, aroma.period t where s.perkey = t.perkey group by t.perkey,t.day) as ti(day,montant) group by ti.day order by moyenne desc