Enjoy !
Philippe Pittoli
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README
244
README
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@ -3,247 +3,3 @@ Hello everyone
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You can watch all my little scripts in C and Perl.
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Enjoy !
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MANGEZ
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SELECT date, SUM(dollars) AS total_dollars,
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SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_dollars,
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SUM(quantity) AS total_qty,
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SUM(SUM(quantity)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS run_qty
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FROM aroma.period a, aroma.sales b, aroma.product c
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WHERE a.perkey = b.perkey
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AND c.prodkey = b.prodkey
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AND c.classkey = b.classkey
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AND year = 2006
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AND month = 'JAN'
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AND prod_name = 'Aroma Roma'
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GROUP BY date
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ORDER BY date;
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SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING)
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OVER = OLAP aggregation function
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MOVING Average = moyenne sur quelques jours pour faire une courbe de la moyenne (moins en dents de scie)
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SELECT date, SUM(dollars) AS total_dollars,
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SUM(SUM(dollars)) OVER(PARTITION BY week ORDER BY date
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ROWS UNBOUNDED PRECEDING) AS run_dollars,
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SUM(quantity) AS total_qty,
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SUM(SUM(quantity)) OVER(PARTITION BY week ORDER BY date
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ROWS UNBOUNDED PRECEDING) AS run_qty
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FROM aroma.period a, aroma.sales b, aroma.product c
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WHERE a.perkey = b.perkey
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AND c.prodkey = b.prodkey
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AND c.classkey = b.classkey
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AND year = 2006
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AND month = 'JAN'
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AND prod_name = 'Aroma Roma'
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GROUP BY week, date
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ORDER BY week, date;
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PARTITION BY week = Faire la somme mais par semaine
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SELECT date, SUM(dollars) AS total_dollars,
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SUM(SUM(dollars)) OVER (PARTITION BY week ORDER BY date
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ROWS UNBOUNDED PRECEDING) AS run_dollars,
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SUM(quantity) AS total_qty,
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SUM(SUM(quantity)) OVER(PARTITION BY week ORDER BY date
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ROWS UNBOUNDED PRECEDING) AS run_qty, week
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FROM aroma.period a, aroma.sales b, aroma.product c
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WHERE a.perkey = b.perkey
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AND c.prodkey = b.prodkey
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AND c.classkey = b.classkey
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AND year = 2006
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AND month = 'JAN'
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AND prod_name = 'Aroma Roma'
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GROUP BY week, date
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ORDER BY week, date;
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SELECT prod_name, SUM(dollars) AS total_sales, SUM(quantity) AS total_qty,
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DEC(sum(dollars)/sum(quantity), 7, 2) AS price
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FROM aroma.product a, aroma.sales b, aroma.period c
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WHERE a.prodkey = b.prodkey
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AND a.classkey = b.classkey
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AND c.perkey = b.perkey
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AND year = 2004
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GROUP BY prod_name
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ORDER BY price;
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dec(sum(dollars)/sum(quantity), 7, 2) AS price
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SELECT t1.date, sales_cume_west, sales_cume_south,
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sales_cume_west - sales_cume_south AS west_vs_south
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FROM
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(SELECT date, SUM(dollars) AS total_sales,
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SUM(SUM(dollars)) OVER(ORDER BY date
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ROWS UNBOUNDED PRECEDING) AS sales_cume_west
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FROM aroma.market a,
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aroma.store b,
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aroma.sales c,
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aroma.period d
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WHERE a.mktkey = b.mktkey
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AND b.storekey = c.storekey
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AND d.perkey = c.perkey
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AND year = 2006
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AND month = 'MAR'
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AND region = 'West'
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GROUP BY date) AS t1
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JOIN
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(SELECT date, SUM(dollars) AS total_sales,
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SUM(SUM(dollars)) OVER(ORDER BY date ROWS UNBOUNDED PRECEDING) AS sales_cume_south
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FROM aroma.market a,
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aroma.store b,
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aroma.sales c,
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aroma.period d
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WHERE a.mktkey = b.mktkey
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AND b.storekey = c.storekey
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AND d.perkey = c.perkey
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AND year = 2006
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AND month = 'MAR'
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AND region = 'South'
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GROUP BY date) AS t2
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ON t1.date = t2.date
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ORDER BY date;
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SELECT city, week, SUM(dollars) AS sales,
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DEC(AVG(SUM(dollars)) OVER(partition by city
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ORDER BY city, week ROWS 2 PRECEDING),7,2) AS mov_avg,
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SUM(SUM(dollars)) OVER(PARTITION BY city
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ORDER BY week ROWS unbounded PRECEDING) AS run_sales
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FROM aroma.store a,
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aroma.sales b,
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aroma.period c
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WHERE a.storekey = b.storekey
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AND c.perkey = b.perkey
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AND qtr = 'Q3_05'
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AND city IN ('San Jose', 'Miami')
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GROUP BY city, week;
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ROWS n PRECEDING (ou on peut aussi dire : FOLLOWING )
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SELECT date, SUM(quantity) AS day_qty,
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DEC(SUM(SUM(quantity)) OVER(ORDER BY date
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ROWS 6 PRECEDING),7,2) AS mov_sum
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FROM aroma.sales a, aroma.period b, aroma.product c
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WHERE b.perkey = a.perkey
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AND c.classkey = a.classkey
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AND c.prodkey = a.prodkey
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AND year = 2006
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AND month = 'MAR'
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AND prod_name = 'Demitasse Ms'
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GROUP BY date
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ORDER BY date;
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REPONSES :
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# Total du montant des ventes par catégorie
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select c.class_type, sum(s.dollars) as total
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from aroma.class c, aroma.sales s, aroma.product p
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where c.classkey = p.classkey
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and p.prodkey = s.prodkey
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and p.classkey = s.classkey
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group by c.class_type
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order by total desc
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# Pourcentage du montant des ventes de chaque catégorie
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select c.class_type, dec(100*sum(s.dollars)/(select sum(dollars) from aroma.sales),7,0) as part
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from aroma.class c, aroma.sales s, aroma.product p
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where c.classkey = p.classkey
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and p.prodkey = s.prodkey
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and p.classkey = s.classkey
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group by c.class_type
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order by part desc
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# Classement des ventes par classes de produit
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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
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from aroma.class c, aroma.sales s, aroma.product p
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where c.classkey = p.classkey
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and p.prodkey = s.prodkey
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and p.classkey = s.classkey
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group by c.class_type
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order by part desc
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# Produit le plus vendu, pourcentage correspondant
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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
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from aroma.sales s, aroma.product p
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where p.prodkey = s.prodkey
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and p.classkey = s.classkey
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group by p.prodkey, p.classkey, p.prod_name, p.pkg_type
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order by part desc²
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# Montant des ventes des produits par semaine
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select p.prodkey, p.classkey, p.prod_name, p.pkg_type, t.week, sum(s.dollars) as montant
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from aroma.sales s, aroma.product p, aroma.period t
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where p.prodkey = s.prodkey
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and p.classkey = s.classkey
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and s.perkey = t.perkey
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group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week
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order by t.week
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# Classement des produits par montant des ventes décroissant pour chaque semaine
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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
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from aroma.sales s, aroma.product p, aroma.period t
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where p.prodkey = s.prodkey
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and p.classkey = s.classkey
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and s.perkey = t.perkey
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group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week
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order by t.week, rang
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# Classement moyen des produits en vente hebdomadaire
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select t.prodkey, t.classkey, t.prod_name, t.pkg_type, avg(rang) as rang_moyen
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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
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from aroma.sales s, aroma.product p, aroma.period t
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where p.prodkey = s.prodkey
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and p.classkey = s.classkey
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and s.perkey = t.perkey
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group by p.prodkey, p.classkey, p.prod_name, p.pkg_type,t.week
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order by t.week, rang) as t(prodkey,classkey,prod_name,pkg_type,week,montant,rang)
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group by t.prodkey,t.classkey, t.prod_name, t.pkg_type
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# Montant moyen des ventes par jour de la semaine
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select ti.day, avg(ti.montant) as moyenne
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from (select t.day,sum(dollars)
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from aroma.sales s, aroma.period t
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where s.perkey = t.perkey
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group by t.perkey,t.day) as ti(day,montant)
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group by ti.day
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order by moyenne desc
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MES REPONSES
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select c.class_type, SUM(s.dollars) as total
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from aroma.class c, aroma.sales s, aroma.product p
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where c.classkey = p.classkey
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and p.classkey = s.classkey
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and p.prodkey = s.prodkey
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group by c.class_type
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order by total desc
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select c.class_type, dec(100*sum(s.dollars)/(select sum(dollars) from aroma.sales), 7,0)
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from aroma.class c, aroma.product p, aroma.sales s
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where c.classkey = p.classkey
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and p.classkey = s.classkey
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and p.prodkey = s.prodkey
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group by c.class_type;
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