【TPCDS】99条查询SQL

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-- start query 1 in stream 0 using template query1.tpl
with customer_total_return as
(select sr_customer_sk as ctr_customer_sk
,sr_store_sk as ctr_store_sk
,sum(SR_FEE) as ctr_total_return
from store_returns
,date_dim
where sr_returned_date_sk = d_date_sk
and d_year =2000
group by sr_customer_sk
,sr_store_sk)
select top 100 c_customer_id
from customer_total_return ctr1
,store
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_store_sk = ctr2.ctr_store_sk)
and s_store_sk = ctr1.ctr_store_sk
and s_state = 'TN'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id
;

-- start query 2 in stream 0 using template query2.tpl
with wscs as
(select sold_date_sk
,sales_price
from (select ws_sold_date_sk sold_date_sk
,ws_ext_sales_price sales_price
from web_sales
union all
select cs_sold_date_sk sold_date_sk
,cs_ext_sales_price sales_price
from catalog_sales)),
wswscs as
(select d_week_seq,
sum(case when (d_day_name='Sunday') then sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then sales_price else null end) sat_sales
from wscs
,date_dim
where d_date_sk = sold_date_sk
group by d_week_seq)
select d_week_seq1
,round(sun_sales1/sun_sales2,2)
,round(mon_sales1/mon_sales2,2)
,round(tue_sales1/tue_sales2,2)
,round(wed_sales1/wed_sales2,2)
,round(thu_sales1/thu_sales2,2)
,round(fri_sales1/fri_sales2,2)
,round(sat_sales1/sat_sales2,2)
from
(select wswscs.d_week_seq d_week_seq1
,sun_sales sun_sales1
,mon_sales mon_sales1
,tue_sales tue_sales1
,wed_sales wed_sales1
,thu_sales thu_sales1
,fri_sales fri_sales1
,sat_sales sat_sales1
from wswscs,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 1998) y,
(select wswscs.d_week_seq d_week_seq2
,sun_sales sun_sales2
,mon_sales mon_sales2
,tue_sales tue_sales2
,wed_sales wed_sales2
,thu_sales thu_sales2
,fri_sales fri_sales2
,sat_sales sat_sales2
from wswscs
,date_dim
where date_dim.d_week_seq = wswscs.d_week_seq and
d_year = 1998+1) z
where d_week_seq1=d_week_seq2-53
order by d_week_seq1;

-- start query 3 in stream 0 using template query3.tpl
select top 100 dt.d_year
,item.i_brand_id brand_id
,item.i_brand brand
,sum(ss_sales_price) sum_agg
from date_dim dt
,store_sales
,item
where dt.d_date_sk = store_sales.ss_sold_date_sk
and store_sales.ss_item_sk = item.i_item_sk
and item.i_manufact_id = 816
and dt.d_moy=11
group by dt.d_year
,item.i_brand
,item.i_brand_id
order by dt.d_year
,sum_agg desc
,brand_id
;

-- start query 4 in stream 0 using template query4.tpl
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(((ss_ext_list_price-ss_ext_wholesale_cost-ss_ext_discount_amt)+ss_ext_sales_price)/2) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum((((cs_ext_list_price-cs_ext_wholesale_cost-cs_ext_discount_amt)+cs_ext_sales_price)/2) ) year_total
,'c' sale_type
from customer
,catalog_sales
,date_dim
where c_customer_sk = cs_bill_customer_sk
and cs_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum((((ws_ext_list_price-ws_ext_wholesale_cost-ws_ext_discount_amt)+ws_ext_sales_price)/2) ) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
)
select top 100
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_birth_country
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_c_firstyear
,year_total t_c_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_c_secyear.customer_id
and t_s_firstyear.customer_id = t_c_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_c_firstyear.sale_type = 'c'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_c_secyear.sale_type = 'c'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.dyear = 1999
and t_s_secyear.dyear = 1999+1
and t_c_firstyear.dyear = 1999
and t_c_secyear.dyear = 1999+1
and t_w_firstyear.dyear = 1999
and t_w_secyear.dyear = 1999+1
and t_s_firstyear.year_total > 0
and t_c_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
and case when t_c_firstyear.year_total > 0 then t_c_secyear.year_total / t_c_firstyear.year_total else null end
> case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
order by t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_birth_country
;

-- start query 5 in stream 0 using template query5.tpl
with ssr as
(select s_store_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select ss_store_sk as store_sk,
ss_sold_date_sk as date_sk,
ss_ext_sales_price as sales_price,
ss_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from store_sales
union all
select sr_store_sk as store_sk,
sr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
sr_return_amt as return_amt,
sr_net_loss as net_loss
from store_returns
) salesreturns,
date_dim,
store
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
and (date_add(cast('2000-08-19' as date),interval 14 day))
and store_sk = s_store_sk
group by s_store_id)
,
csr as
(select cp_catalog_page_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select cs_catalog_page_sk as page_sk,
cs_sold_date_sk as date_sk,
cs_ext_sales_price as sales_price,
cs_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from catalog_sales
union all
select cr_catalog_page_sk as page_sk,
cr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
cr_return_amount as return_amt,
cr_net_loss as net_loss
from catalog_returns
) salesreturns,
date_dim,
catalog_page
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
and (date_add(cast('2000-08-19' as date),interval 14 day))
and page_sk = cp_catalog_page_sk
group by cp_catalog_page_id)
,
wsr as
(select web_site_id,
sum(sales_price) as sales,
sum(profit) as profit,
sum(return_amt) as returns,
sum(net_loss) as profit_loss
from
( select ws_web_site_sk as wsr_web_site_sk,
ws_sold_date_sk as date_sk,
ws_ext_sales_price as sales_price,
ws_net_profit as profit,
cast(0 as decimal(7,2)) as return_amt,
cast(0 as decimal(7,2)) as net_loss
from web_sales
union all
select ws_web_site_sk as wsr_web_site_sk,
wr_returned_date_sk as date_sk,
cast(0 as decimal(7,2)) as sales_price,
cast(0 as decimal(7,2)) as profit,
wr_return_amt as return_amt,
wr_net_loss as net_loss
from web_returns left outer join web_sales on
( wr_item_sk = ws_item_sk
and wr_order_number = ws_order_number)
) salesreturns,
date_dim,
web_site
where date_sk = d_date_sk
and d_date between cast('2000-08-19' as date)
and (date_add(cast('2000-08-19' as date),interval 14 day))
and wsr_web_site_sk = web_site_sk
group by web_site_id)
select top 100 channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, 'store' || s_store_id as id
, sales
, returns
, (profit - profit_loss) as profit
from ssr
union all
select 'catalog channel' as channel
, 'catalog_page' || cp_catalog_page_id as id
, sales
, returns
, (profit - profit_loss) as profit
from csr
union all
select 'web channel' as channel
, 'web_site' || web_site_id as id
, sales
, returns
, (profit - profit_loss) as profit
from wsr
) x
group by rollup (channel, id)
order by channel
,id
;

-- start query 6 in stream 0 using template query6.tpl
select top 100 a.ca_state state, count(*) cnt
from customer_address a
,customer c
,store_sales s
,date_dim d
,item i
where a.ca_address_sk = c.c_current_addr_sk
and c.c_customer_sk = s.ss_customer_sk
and s.ss_sold_date_sk = d.d_date_sk
and s.ss_item_sk = i.i_item_sk
and d.d_month_seq =
(select distinct (d_month_seq)
from date_dim
where d_year = 2002
and d_moy = 3 )
and i.i_current_price > 1.2 *
(select avg(j.i_current_price)
from item j
where j.i_category = i.i_category)
group by a.ca_state
having count(*) >= 10
order by cnt, a.ca_state
;

-- start query 7 in stream 0 using template query7.tpl
select top 100 i_item_id,
avg(ss_quantity) agg1,
avg(ss_list_price) agg2,
avg(ss_coupon_amt) agg3,
avg(ss_sales_price) agg4
from store_sales, customer_demographics, date_dim, item, promotion
where ss_sold_date_sk = d_date_sk and
ss_item_sk = i_item_sk and
ss_cdemo_sk = cd_demo_sk and
ss_promo_sk = p_promo_sk and
cd_gender = 'F' and
cd_marital_status = 'W' and
cd_education_status = 'College' and
(p_channel_email = 'N' or p_channel_event = 'N') and
d_year = 2001
group by i_item_id
order by i_item_id
;

-- start query 8 in stream 0 using template query8.tpl
select top 100 s_store_name
,sum(ss_net_profit)
from store_sales
,date_dim
,store,
(select ca_zip
from (
SELECT substr(ca_zip,1,5) ca_zip
FROM customer_address
WHERE substr(ca_zip,1,5) IN (
'47602','16704','35863','28577','83910','36201',
'58412','48162','28055','41419','80332',
'38607','77817','24891','16226','18410',
'21231','59345','13918','51089','20317',
'17167','54585','67881','78366','47770',
'18360','51717','73108','14440','21800',
'89338','45859','65501','34948','25973',
'73219','25333','17291','10374','18829',
'60736','82620','41351','52094','19326',
'25214','54207','40936','21814','79077',
'25178','75742','77454','30621','89193',
'27369','41232','48567','83041','71948',
'37119','68341','14073','16891','62878',
'49130','19833','24286','27700','40979',
'50412','81504','94835','84844','71954',
'39503','57649','18434','24987','12350',
'86379','27413','44529','98569','16515',
'27287','24255','21094','16005','56436',
'91110','68293','56455','54558','10298',
'83647','32754','27052','51766','19444',
'13869','45645','94791','57631','20712',
'37788','41807','46507','21727','71836',
'81070','50632','88086','63991','20244',
'31655','51782','29818','63792','68605',
'94898','36430','57025','20601','82080',
'33869','22728','35834','29086','92645',
'98584','98072','11652','78093','57553',
'43830','71144','53565','18700','90209',
'71256','38353','54364','28571','96560',
'57839','56355','50679','45266','84680',
'34306','34972','48530','30106','15371',
'92380','84247','92292','68852','13338',
'34594','82602','70073','98069','85066',
'47289','11686','98862','26217','47529',
'63294','51793','35926','24227','14196',
'24594','32489','99060','49472','43432',
'49211','14312','88137','47369','56877',
'20534','81755','15794','12318','21060',
'73134','41255','63073','81003','73873',
'66057','51184','51195','45676','92696',
'70450','90669','98338','25264','38919',
'59226','58581','60298','17895','19489',
'52301','80846','95464','68770','51634',
'19988','18367','18421','11618','67975',
'25494','41352','95430','15734','62585',
'97173','33773','10425','75675','53535',
'17879','41967','12197','67998','79658',
'59130','72592','14851','43933','68101',
'50636','25717','71286','24660','58058',
'72991','95042','15543','33122','69280',
'11912','59386','27642','65177','17672',
'33467','64592','36335','54010','18767',
'63193','42361','49254','33113','33159',
'36479','59080','11855','81963','31016',
'49140','29392','41836','32958','53163',
'13844','73146','23952','65148','93498',
'14530','46131','58454','13376','13378',
'83986','12320','17193','59852','46081',
'98533','52389','13086','68843','31013',
'13261','60560','13443','45533','83583',
'11489','58218','19753','22911','25115',
'86709','27156','32669','13123','51933',
'39214','41331','66943','14155','69998',
'49101','70070','35076','14242','73021',
'59494','15782','29752','37914','74686',
'83086','34473','15751','81084','49230',
'91894','60624','17819','28810','63180',
'56224','39459','55233','75752','43639',
'55349','86057','62361','50788','31830',
'58062','18218','85761','60083','45484',
'21204','90229','70041','41162','35390',
'16364','39500','68908','26689','52868',
'81335','40146','11340','61527','61794',
'71997','30415','59004','29450','58117',
'69952','33562','83833','27385','61860',
'96435','48333','23065','32961','84919',
'61997','99132','22815','56600','68730',
'48017','95694','32919','88217','27116',
'28239','58032','18884','16791','21343',
'97462','18569','75660','15475')
intersect
select ca_zip
from (SELECT substr(ca_zip,1,5) ca_zip,count(*) cnt
FROM customer_address, customer
WHERE ca_address_sk = c_current_addr_sk and
c_preferred_cust_flag='Y'
group by ca_zip
having count(*) > 10)A1)A2) V1
where ss_store_sk = s_store_sk
and ss_sold_date_sk = d_date_sk
and d_qoy = 2 and d_year = 1998
and (substr(s_zip,1,2) = substr(V1.ca_zip,1,2))
group by s_store_name
order by s_store_name
;

-- start query 9 in stream 0 using template query9.tpl
select case when (select count(*)
from store_sales
where ss_quantity between 1 and 20) > 1071
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 1 and 20)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 1 and 20) end bucket1 ,
case when (select count(*)
from store_sales
where ss_quantity between 21 and 40) > 39161
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 21 and 40)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 21 and 40) end bucket2,
case when (select count(*)
from store_sales
where ss_quantity between 41 and 60) > 29434
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 41 and 60)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 41 and 60) end bucket3,
case when (select count(*)
from store_sales
where ss_quantity between 61 and 80) > 6568
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 61 and 80)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 61 and 80) end bucket4,
case when (select count(*)
from store_sales
where ss_quantity between 81 and 100) > 21216
then (select avg(ss_ext_tax)
from store_sales
where ss_quantity between 81 and 100)
else (select avg(ss_net_paid_inc_tax)
from store_sales
where ss_quantity between 81 and 100) end bucket5
from reason
where r_reason_sk = 1
;

-- start query 10 in stream 0 using template query10.tpl
select top 100
cd_gender,
cd_marital_status,
cd_education_status,
count(*) cnt1,
cd_purchase_estimate,
count(*) cnt2,
cd_credit_rating,
count(*) cnt3,
cd_dep_count,
count(*) cnt4,
cd_dep_employed_count,
count(*) cnt5,
cd_dep_college_count,
count(*) cnt6
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_county in ('Fairfield County','Campbell County','Washtenaw County','Escambia County','Cleburne County') and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 2001 and
d_moy between 3 and 3+3) and
(exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 2001 and
d_moy between 3 ANd 3+3) or
exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 2001 and
d_moy between 3 and 3+3))
group by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
order by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
;

-- start query 11 in stream 0 using template query11.tpl
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(ss_ext_list_price-ss_ext_discount_amt) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,c_preferred_cust_flag customer_preferred_cust_flag
,c_birth_country customer_birth_country
,c_login customer_login
,c_email_address customer_email_address
,d_year dyear
,sum(ws_ext_list_price-ws_ext_discount_amt) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
group by c_customer_id
,c_first_name
,c_last_name
,c_preferred_cust_flag
,c_birth_country
,c_login
,c_email_address
,d_year
)
select top 100
t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.dyear = 1998
and t_s_secyear.dyear = 1998+1
and t_w_firstyear.dyear = 1998
and t_w_secyear.dyear = 1998+1
and t_s_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else 0.0 end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else 0.0 end
order by t_s_secyear.customer_id
,t_s_secyear.customer_first_name
,t_s_secyear.customer_last_name
,t_s_secyear.customer_email_address
;

-- start query 12 in stream 0 using template query12.tpl
select top 100 i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(ws_ext_sales_price) as itemrevenue
,sum(ws_ext_sales_price)*100/sum(sum(ws_ext_sales_price)) over
(partition by i_class) as revenueratio
from
web_sales
,item
,date_dim
where
ws_item_sk = i_item_sk
and i_category in ('Men', 'Books', 'Electronics')
and ws_sold_date_sk = d_date_sk
and d_date between cast('2001-06-15' as date)
and (date_add(cast('2001-06-15' as date),interval 30 day))
group by
i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by
i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio
;

-- start query 13 in stream 0 using template query13.tpl
select avg(ss_quantity)
,avg(ss_ext_sales_price)
,avg(ss_ext_wholesale_cost)
,sum(ss_ext_wholesale_cost)
from store_sales
,store
,customer_demographics
,household_demographics
,customer_address
,date_dim
where s_store_sk = ss_store_sk
and ss_sold_date_sk = d_date_sk and d_year = 2001
and((ss_hdemo_sk=hd_demo_sk
and cd_demo_sk = ss_cdemo_sk
and cd_marital_status = 'M'
and cd_education_status = 'College'
and ss_sales_price between 100.00 and 150.00
and hd_dep_count = 3
)or
(ss_hdemo_sk=hd_demo_sk
and cd_demo_sk = ss_cdemo_sk
and cd_marital_status = 'D'
and cd_education_status = 'Primary'
and ss_sales_price between 50.00 and 100.00
and hd_dep_count = 1
) or
(ss_hdemo_sk=hd_demo_sk
and cd_demo_sk = ss_cdemo_sk
and cd_marital_status = 'W'
and cd_education_status = '2 yr Degree'
and ss_sales_price between 150.00 and 200.00
and hd_dep_count = 1
))
and((ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('IL', 'TN', 'TX')
and ss_net_profit between 100 and 200
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('WY', 'OH', 'ID')
and ss_net_profit between 150 and 300
) or
(ss_addr_sk = ca_address_sk
and ca_country = 'United States'
and ca_state in ('MS', 'SC', 'IA')
and ss_net_profit between 50 and 250
))
;

-- start query 14 in stream 0 using template query14.tpl
with cross_items as
(select i_item_sk ss_item_sk
from item,
(select iss.i_brand_id brand_id
,iss.i_class_id class_id
,iss.i_category_id category_id
from store_sales
,item iss
,date_dim d1
where ss_item_sk = iss.i_item_sk
and ss_sold_date_sk = d1.d_date_sk
and d1.d_year between 1999 AND 1999 + 2
intersect
select ics.i_brand_id
,ics.i_class_id
,ics.i_category_id
from catalog_sales
,item ics
,date_dim d2
where cs_item_sk = ics.i_item_sk
and cs_sold_date_sk = d2.d_date_sk
and d2.d_year between 1999 AND 1999 + 2
intersect
select iws.i_brand_id
,iws.i_class_id
,iws.i_category_id
from web_sales
,item iws
,date_dim d3
where ws_item_sk = iws.i_item_sk
and ws_sold_date_sk = d3.d_date_sk
and d3.d_year between 1999 AND 1999 + 2)
where i_brand_id = brand_id
and i_class_id = class_id
and i_category_id = category_id
),
avg_sales as
(select avg(quantity*list_price) average_sales
from (select ss_quantity quantity
,ss_list_price list_price
from store_sales
,date_dim
where ss_sold_date_sk = d_date_sk
and d_year between 1999 and 1999 + 2
union all
select cs_quantity quantity
,cs_list_price list_price
from catalog_sales
,date_dim
where cs_sold_date_sk = d_date_sk
and d_year between 1999 and 1999 + 2
union all
select ws_quantity quantity
,ws_list_price list_price
from web_sales
,date_dim
where ws_sold_date_sk = d_date_sk
and d_year between 1999 and 1999 + 2) x)
select top 100 channel, i_brand_id,i_class_id,i_category_id,sum(sales), sum(number_sales)
from(
select 'store' channel, i_brand_id,i_class_id
,i_category_id,sum(ss_quantity*ss_list_price) sales
, count(*) number_sales
from store_sales
,item
,date_dim
where ss_item_sk in (select ss_item_sk from cross_items)
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 1999+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(ss_quantity*ss_list_price) > (select average_sales from avg_sales)
union all
select 'catalog' channel, i_brand_id,i_class_id,i_category_id, sum(cs_quantity*cs_list_price) sales, count(*) number_sales
from catalog_sales
,item
,date_dim
where cs_item_sk in (select ss_item_sk from cross_items)
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 1999+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(cs_quantity*cs_list_price) > (select average_sales from avg_sales)
union all
select 'web' channel, i_brand_id,i_class_id,i_category_id, sum(ws_quantity*ws_list_price) sales , count(*) number_sales
from web_sales
,item
,date_dim
where ws_item_sk in (select ss_item_sk from cross_items)
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 1999+2
and d_moy = 11
group by i_brand_id,i_class_id,i_category_id
having sum(ws_quantity*ws_list_price) > (select average_sales from avg_sales)
) y
group by rollup (channel, i_brand_id,i_class_id,i_category_id)
order by channel,i_brand_id,i_class_id,i_category_id
;

-- start query 15 in stream 0 using template query15.tpl
select top 100 ca_zip
,sum(cs_sales_price)
from catalog_sales
,customer
,customer_address
,date_dim
where cs_bill_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475',
'85392', '85460', '80348', '81792')
or ca_state in ('CA','WA','GA')
or cs_sales_price > 500)
and cs_sold_date_sk = d_date_sk
and d_qoy = 2 and d_year = 2001
group by ca_zip
order by ca_zip
;

-- start query 16 in stream 0 using template query16.tpl
select top 100
count(distinct cs_order_number) as "order count"
,sum(cs_ext_ship_cost) as "total shipping cost"
,sum(cs_net_profit) as "total net profit"
from
catalog_sales cs1
,date_dim
,customer_address
,call_center
where
d_date between '2002-4-01' and
(date_add(cast('2002-4-01' as date),interval 60 day))
and cs1.cs_ship_date_sk = d_date_sk
and cs1.cs_ship_addr_sk = ca_address_sk
and ca_state = 'PA'
and cs1.cs_call_center_sk = cc_call_center_sk
and cc_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
'Williamson County'
)
and exists (select *
from catalog_sales cs2
where cs1.cs_order_number = cs2.cs_order_number
and cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk)
and not exists(select *
from catalog_returns cr1
where cs1.cs_order_number = cr1.cr_order_number)
order by count(distinct cs_order_number)
;

-- start query 17 in stream 0 using template query17.tpl
select top 100 i_item_id
,i_item_desc
,s_state
,count(ss_quantity) as store_sales_quantitycount
,avg(ss_quantity) as store_sales_quantityave
,stddev_samp(ss_quantity) as store_sales_quantitystdev
,stddev_samp(ss_quantity)/avg(ss_quantity) as store_sales_quantitycov
,count(sr_return_quantity) as store_returns_quantitycount
,avg(sr_return_quantity) as store_returns_quantityave
,stddev_samp(sr_return_quantity) as store_returns_quantitystdev
,stddev_samp(sr_return_quantity)/avg(sr_return_quantity) as store_returns_quantitycov
,count(cs_quantity) as catalog_sales_quantitycount ,avg(cs_quantity) as catalog_sales_quantityave
,stddev_samp(cs_quantity) as catalog_sales_quantitystdev
,stddev_samp(cs_quantity)/avg(cs_quantity) as catalog_sales_quantitycov
from store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where d1.d_quarter_name = '2001Q1'
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_quarter_name in ('2001Q1','2001Q2','2001Q3')
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_quarter_name in ('2001Q1','2001Q2','2001Q3')
group by i_item_id
,i_item_desc
,s_state
order by i_item_id
,i_item_desc
,s_state
;

-- start query 18 in stream 0 using template query18.tpl
select top 100 i_item_id,
ca_country,
ca_state,
ca_county,
avg( cast(cs_quantity as decimal(12,2))) agg1,
avg( cast(cs_list_price as decimal(12,2))) agg2,
avg( cast(cs_coupon_amt as decimal(12,2))) agg3,
avg( cast(cs_sales_price as decimal(12,2))) agg4,
avg( cast(cs_net_profit as decimal(12,2))) agg5,
avg( cast(c_birth_year as decimal(12,2))) agg6,
avg( cast(cd1.cd_dep_count as decimal(12,2))) agg7
from catalog_sales, customer_demographics cd1,
customer_demographics cd2, customer, customer_address, date_dim, item
where cs_sold_date_sk = d_date_sk and
cs_item_sk = i_item_sk and
cs_bill_cdemo_sk = cd1.cd_demo_sk and
cs_bill_customer_sk = c_customer_sk and
cd1.cd_gender = 'F' and
cd1.cd_education_status = 'Primary' and
c_current_cdemo_sk = cd2.cd_demo_sk and
c_current_addr_sk = ca_address_sk and
c_birth_month in (1,3,7,11,10,4) and
d_year = 2001 and
ca_state in ('AL','MO','TN'
,'GA','MT','IN','CA')
group by rollup (i_item_id, ca_country, ca_state, ca_county)
order by ca_country,
ca_state,
ca_county,
i_item_id
;

-- start query 19 in stream 0 using template query19.tpl
select top 100 i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
sum(ss_ext_sales_price) ext_price
from date_dim, store_sales, item,customer,customer_address,store
where d_date_sk = ss_sold_date_sk
and ss_item_sk = i_item_sk
and i_manager_id=14
and d_moy=11
and d_year=2002
and ss_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and substr(ca_zip,1,5) <> substr(s_zip,1,5)
and ss_store_sk = s_store_sk
group by i_brand
,i_brand_id
,i_manufact_id
,i_manufact
order by ext_price desc
,i_brand
,i_brand_id
,i_manufact_id
,i_manufact
;

-- start query 20 in stream 0 using template query20.tpl
select top 100 i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(cs_ext_sales_price) as itemrevenue
,sum(cs_ext_sales_price)*100/sum(sum(cs_ext_sales_price)) over
(partition by i_class) as revenueratio
from catalog_sales
,item
,date_dim
where cs_item_sk = i_item_sk
and i_category in ('Books', 'Music', 'Sports')
and cs_sold_date_sk = d_date_sk
and d_date between cast('2002-06-18' as date)
and (date_add(cast('2002-06-18' as date),interval 30 day))
group by i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio
;

-- start query 21 in stream 0 using template query21.tpl
select top 100 *
from(select w_warehouse_name
,i_item_id
,sum(case when (cast(d_date as date) < cast ('1999-06-22' as date))
then inv_quantity_on_hand
else 0 end) as inv_before
,sum(case when (cast(d_date as date) >= cast ('1999-06-22' as date))
then inv_quantity_on_hand
else 0 end) as inv_after
from inventory
,warehouse
,item
,date_dim
where i_current_price between 0.99 and 1.49
and i_item_sk = inv_item_sk
and inv_warehouse_sk = w_warehouse_sk
and inv_date_sk = d_date_sk
and d_date between (date_sub(cast ('1999-06-22' as date),interval 30 day))
and (date_add(cast('1999-06-22' as date),interval 30 day))
group by w_warehouse_name, i_item_id) x
where (case when inv_before > 0
then inv_after / inv_before
else null
end) between 2.0/3.0 and 3.0/2.0
order by w_warehouse_name
,i_item_id
;

-- start query 22 in stream 0 using template query22.tpl
select top 100 i_product_name
,i_brand
,i_class
,i_category
,avg(inv_quantity_on_hand) qoh
from inventory
,date_dim
,item
where inv_date_sk=d_date_sk
and inv_item_sk=i_item_sk
and d_month_seq between 1200 and 1200 + 11
group by rollup(i_product_name
,i_brand
,i_class
,i_category)
order by qoh, i_product_name, i_brand, i_class, i_category
;

-- start query 23 in stream 0 using template query23.tpl
with frequent_ss_items as
(select substr(i_item_desc,1,30) itemdesc,i_item_sk item_sk,d_date solddate,count(*) cnt
from store_sales
,date_dim
,item
where ss_sold_date_sk = d_date_sk
and ss_item_sk = i_item_sk
and d_year in (2000,2000+1,2000+2,2000+3)
group by substr(i_item_desc,1,30),i_item_sk,d_date
having count(*) >4),
max_store_sales as
(select max(csales) tpcds_cmax
from (select c_customer_sk,sum(ss_quantity*ss_sales_price) csales
from store_sales
,customer
,date_dim
where ss_customer_sk = c_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (2000,2000+1,2000+2,2000+3)
group by c_customer_sk)),
best_ss_customer as
(select c_customer_sk,sum(ss_quantity*ss_sales_price) ssales
from store_sales
,customer
where ss_customer_sk = c_customer_sk
group by c_customer_sk
having sum(ss_quantity*ss_sales_price) > (95/100.0) * (select
*
from
max_store_sales))
select top 100 sum(sales)
from (select cs_quantity*cs_list_price sales
from catalog_sales
,date_dim
where d_year = 2000
and d_moy = 7
and cs_sold_date_sk = d_date_sk
and cs_item_sk in (select item_sk from frequent_ss_items)
and cs_bill_customer_sk in (select c_customer_sk from best_ss_customer)
union all
select ws_quantity*ws_list_price sales
from web_sales
,date_dim
where d_year = 2000
and d_moy = 7
and ws_sold_date_sk = d_date_sk
and ws_item_sk in (select item_sk from frequent_ss_items)
and ws_bill_customer_sk in (select c_customer_sk from best_ss_customer))
;

-- start query 24 in stream 0 using template query24.tpl
with ssales as
(select c_last_name
,c_first_name
,s_store_name
,ca_state
,s_state
,i_color
,i_current_price
,i_manager_id
,i_units
,i_size
,sum(ss_net_paid) netpaid
from store_sales
,store_returns
,store
,item
,customer
,customer_address
where ss_ticket_number = sr_ticket_number
and ss_item_sk = sr_item_sk
and ss_customer_sk = c_customer_sk
and ss_item_sk = i_item_sk
and ss_store_sk = s_store_sk
and c_current_addr_sk = ca_address_sk
and c_birth_country <> upper(ca_country)
and s_zip = ca_zip
and s_market_id=5
group by c_last_name
,c_first_name
,s_store_name
,ca_state
,s_state
,i_color
,i_current_price
,i_manager_id
,i_units
,i_size)
select c_last_name
,c_first_name
,s_store_name
,sum(netpaid) paid
from ssales
where i_color = 'aquamarine'
group by c_last_name
,c_first_name
,s_store_name
having sum(netpaid) > (select 0.05*avg(netpaid)
from ssales)
order by c_last_name
,c_first_name
,s_store_name
;

-- start query 25 in stream 0 using template query25.tpl
select top 100
i_item_id
,i_item_desc
,s_store_id
,s_store_name
,max(ss_net_profit) as store_sales_profit
,max(sr_net_loss) as store_returns_loss
,max(cs_net_profit) as catalog_sales_profit
from
store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where
d1.d_moy = 4
and d1.d_year = 1999
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_moy between 4 and 10
and d2.d_year = 1999
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_moy between 4 and 10
and d3.d_year = 1999
group by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
order by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
;

-- start query 26 in stream 0 using template query26.tpl
select top 100 i_item_id,
avg(cs_quantity) agg1,
avg(cs_list_price) agg2,
avg(cs_coupon_amt) agg3,
avg(cs_sales_price) agg4
from catalog_sales, customer_demographics, date_dim, item, promotion
where cs_sold_date_sk = d_date_sk and
cs_item_sk = i_item_sk and
cs_bill_cdemo_sk = cd_demo_sk and
cs_promo_sk = p_promo_sk and
cd_gender = 'M' and
cd_marital_status = 'W' and
cd_education_status = 'Unknown' and
(p_channel_email = 'N' or p_channel_event = 'N') and
d_year = 2002
group by i_item_id
order by i_item_id
;

-- start query 27 in stream 0 using template query27.tpl
select top 100 i_item_id,
s_state, grouping(s_state) g_state,
avg(ss_quantity) agg1,
avg(ss_list_price) agg2,
avg(ss_coupon_amt) agg3,
avg(ss_sales_price) agg4
from store_sales, customer_demographics, date_dim, store, item
where ss_sold_date_sk = d_date_sk and
ss_item_sk = i_item_sk and
ss_store_sk = s_store_sk and
ss_cdemo_sk = cd_demo_sk and
cd_gender = 'M' and
cd_marital_status = 'W' and
cd_education_status = 'Secondary' and
d_year = 1999 and
s_state in ('TN','TN', 'TN', 'TN', 'TN', 'TN')
group by rollup (i_item_id, s_state)
order by i_item_id
,s_state
;

-- start query 28 in stream 0 using template query28.tpl
select top 100 *
from (select avg(ss_list_price) B1_LP
,count(ss_list_price) B1_CNT
,count(distinct ss_list_price) B1_CNTD
from store_sales
where ss_quantity between 0 and 5
and (ss_list_price between 107 and 107+10
or ss_coupon_amt between 1319 and 1319+1000
or ss_wholesale_cost between 60 and 60+20)) B1,
(select avg(ss_list_price) B2_LP
,count(ss_list_price) B2_CNT
,count(distinct ss_list_price) B2_CNTD
from store_sales
where ss_quantity between 6 and 10
and (ss_list_price between 23 and 23+10
or ss_coupon_amt between 825 and 825+1000
or ss_wholesale_cost between 43 and 43+20)) B2,
(select avg(ss_list_price) B3_LP
,count(ss_list_price) B3_CNT
,count(distinct ss_list_price) B3_CNTD
from store_sales
where ss_quantity between 11 and 15
and (ss_list_price between 74 and 74+10
or ss_coupon_amt between 4381 and 4381+1000
or ss_wholesale_cost between 57 and 57+20)) B3,
(select avg(ss_list_price) B4_LP
,count(ss_list_price) B4_CNT
,count(distinct ss_list_price) B4_CNTD
from store_sales
where ss_quantity between 16 and 20
and (ss_list_price between 89 and 89+10
or ss_coupon_amt between 3117 and 3117+1000
or ss_wholesale_cost between 68 and 68+20)) B4,
(select avg(ss_list_price) B5_LP
,count(ss_list_price) B5_CNT
,count(distinct ss_list_price) B5_CNTD
from store_sales
where ss_quantity between 21 and 25
and (ss_list_price between 58 and 58+10
or ss_coupon_amt between 9402 and 9402+1000
or ss_wholesale_cost between 38 and 38+20)) B5,
(select avg(ss_list_price) B6_LP
,count(ss_list_price) B6_CNT
,count(distinct ss_list_price) B6_CNTD
from store_sales
where ss_quantity between 26 and 30
and (ss_list_price between 64 and 64+10
or ss_coupon_amt between 5792 and 5792+1000
or ss_wholesale_cost between 73 and 73+20)) B6
;

-- start query 29 in stream 0 using template query29.tpl
select top 100
i_item_id
,i_item_desc
,s_store_id
,s_store_name
,max(ss_quantity) as store_sales_quantity
,max(sr_return_quantity) as store_returns_quantity
,max(cs_quantity) as catalog_sales_quantity
from
store_sales
,store_returns
,catalog_sales
,date_dim d1
,date_dim d2
,date_dim d3
,store
,item
where
d1.d_moy = 4
and d1.d_year = 1998
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and ss_customer_sk = sr_customer_sk
and ss_item_sk = sr_item_sk
and ss_ticket_number = sr_ticket_number
and sr_returned_date_sk = d2.d_date_sk
and d2.d_moy between 4 and 4 + 3
and d2.d_year = 1998
and sr_customer_sk = cs_bill_customer_sk
and sr_item_sk = cs_item_sk
and cs_sold_date_sk = d3.d_date_sk
and d3.d_year in (1998,1998+1,1998+2)
group by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
order by
i_item_id
,i_item_desc
,s_store_id
,s_store_name
;

-- start query 30 in stream 0 using template query30.tpl
with customer_total_return as
(select wr_returning_customer_sk as ctr_customer_sk
,ca_state as ctr_state,
sum(wr_return_amt) as ctr_total_return
from web_returns
,date_dim
,customer_address
where wr_returned_date_sk = d_date_sk
and d_year =2000
and wr_returning_addr_sk = ca_address_sk
group by wr_returning_customer_sk
,ca_state)
select top 100 c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
,c_last_review_date_sk,ctr_total_return
from customer_total_return ctr1
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'AR'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id,c_salutation,c_first_name,c_last_name,c_preferred_cust_flag
,c_birth_day,c_birth_month,c_birth_year,c_birth_country,c_login,c_email_address
,c_last_review_date_sk,ctr_total_return
;

-- start query 31 in stream 0 using template query31.tpl
with ss as
(select ca_county,d_qoy, d_year,sum(ss_ext_sales_price) as store_sales
from store_sales,date_dim,customer_address
where ss_sold_date_sk = d_date_sk
and ss_addr_sk=ca_address_sk
group by ca_county,d_qoy, d_year),
ws as
(select ca_county,d_qoy, d_year,sum(ws_ext_sales_price) as web_sales
from web_sales,date_dim,customer_address
where ws_sold_date_sk = d_date_sk
and ws_bill_addr_sk=ca_address_sk
group by ca_county,d_qoy, d_year)
select
ss1.ca_county
,ss1.d_year
,ws2.web_sales/ws1.web_sales web_q1_q2_increase
,ss2.store_sales/ss1.store_sales store_q1_q2_increase
,ws3.web_sales/ws2.web_sales web_q2_q3_increase
,ss3.store_sales/ss2.store_sales store_q2_q3_increase
from
ss ss1
,ss ss2
,ss ss3
,ws ws1
,ws ws2
,ws ws3
where
ss1.d_qoy = 1
and ss1.d_year = 1999
and ss1.ca_county = ss2.ca_county
and ss2.d_qoy = 2
and ss2.d_year = 1999
and ss2.ca_county = ss3.ca_county
and ss3.d_qoy = 3
and ss3.d_year = 1999
and ss1.ca_county = ws1.ca_county
and ws1.d_qoy = 1
and ws1.d_year = 1999
and ws1.ca_county = ws2.ca_county
and ws2.d_qoy = 2
and ws2.d_year = 1999
and ws1.ca_county = ws3.ca_county
and ws3.d_qoy = 3
and ws3.d_year =1999
and case when ws1.web_sales > 0 then ws2.web_sales/ws1.web_sales else null end
> case when ss1.store_sales > 0 then ss2.store_sales/ss1.store_sales else null end
and case when ws2.web_sales > 0 then ws3.web_sales/ws2.web_sales else null end
> case when ss2.store_sales > 0 then ss3.store_sales/ss2.store_sales else null end
order by store_q2_q3_increase;

-- start query 32 in stream 0 using template query32.tpl
select top 100 sum(cs_ext_discount_amt) as "excess discount amount"
from
catalog_sales
,item
,date_dim
where
i_manufact_id = 722
and i_item_sk = cs_item_sk
and d_date between '2001-03-09' and
(date_add(cast('2001-03-09' as date),interval 90 day))
and d_date_sk = cs_sold_date_sk
and cs_ext_discount_amt
> (
select
1.3 * avg(cs_ext_discount_amt)
from
catalog_sales
,date_dim
where
cs_item_sk = i_item_sk
and d_date between '2001-03-09' and
(date_add(cast('2001-03-09' as date),interval 90 day))
and d_date_sk = cs_sold_date_sk
)
;

-- start query 33 in stream 0 using template query33.tpl
with ss as (
select
i_manufact_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 2001
and d_moy = 3
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_manufact_id),
cs as (
select
i_manufact_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 2001
and d_moy = 3
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_manufact_id),
ws as (
select
i_manufact_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_manufact_id in (select
i_manufact_id
from
item
where i_category in ('Books'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 2001
and d_moy = 3
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_manufact_id)
select top 100 i_manufact_id ,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_manufact_id
order by total_sales
;

-- start query 34 in stream 0 using template query34.tpl
select c_last_name
,c_first_name
,c_salutation
,c_preferred_cust_flag
,ss_ticket_number
,cnt from
(select ss_ticket_number
,ss_customer_sk
,count(*) cnt
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and (date_dim.d_dom between 1 and 3 or date_dim.d_dom between 25 and 28)
and (household_demographics.hd_buy_potential = '1001-5000' or
household_demographics.hd_buy_potential = '0-500')
and household_demographics.hd_vehicle_count > 0
and (case when household_demographics.hd_vehicle_count > 0
then household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count
else null
end) > 1.2
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County',
'Williamson County','Williamson County','Williamson County','Williamson County')
group by ss_ticket_number,ss_customer_sk) dn,customer
where ss_customer_sk = c_customer_sk
and cnt between 15 and 20
order by c_last_name,c_first_name,c_salutation,c_preferred_cust_flag desc, ss_ticket_number
;

-- start query 35 in stream 0 using template query35.tpl
select top 100
ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
count(*) cnt1,
avg(cd_dep_count),
stddev_samp(cd_dep_count),
sum(cd_dep_count),
cd_dep_employed_count,
count(*) cnt2,
avg(cd_dep_employed_count),
stddev_samp(cd_dep_employed_count),
sum(cd_dep_employed_count),
cd_dep_college_count,
count(*) cnt3,
avg(cd_dep_college_count),
stddev_samp(cd_dep_college_count),
sum(cd_dep_college_count)
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4) and
(exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4) or
exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 1999 and
d_qoy < 4))
group by ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
order by ca_state,
cd_gender,
cd_marital_status,
cd_dep_count,
cd_dep_employed_count,
cd_dep_college_count
;

-- start query 36 in stream 0 using template query36.tpl
select top 100
sum(ss_net_profit)/sum(ss_ext_sales_price) as gross_margin
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
case when grouping(i_class) = 0 then i_category end
order by sum(ss_net_profit)/sum(ss_ext_sales_price) asc) as rank_within_parent
from
store_sales
,date_dim d1
,item
,store
where
d1.d_year = 2000
and d1.d_date_sk = ss_sold_date_sk
and i_item_sk = ss_item_sk
and s_store_sk = ss_store_sk
and s_state in ('TN','TN','TN','TN',
'TN','TN','TN','TN')
group by rollup(i_category,i_class)
order by
lochierarchy desc
,case when lochierarchy = 0 then i_category end
,rank_within_parent
;

-- start query 37 in stream 0 using template query37.tpl
select top 100 i_item_id
,i_item_desc
,i_current_price
from item, inventory, date_dim, catalog_sales
where i_current_price between 29 and 29 + 30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
and d_date between cast('2002-03-29' as date) and (date_add(cast('2002-03-29' as date),interval 60 day))
and i_manufact_id in (705,742,777,944)
and inv_quantity_on_hand between 100 and 500
and cs_item_sk = i_item_sk
group by i_item_id,i_item_desc,i_current_price
order by i_item_id
;

-- start query 38 in stream 0 using template query38.tpl
select top 100 count(*) from (
select distinct c_last_name, c_first_name, d_date
from store_sales, date_dim, customer
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_customer_sk = customer.c_customer_sk
and d_month_seq between 1189 and 1189 + 11
intersect
select distinct c_last_name, c_first_name, d_date
from catalog_sales, date_dim, customer
where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1189 and 1189 + 11
intersect
select distinct c_last_name, c_first_name, d_date
from web_sales, date_dim, customer
where web_sales.ws_sold_date_sk = date_dim.d_date_sk
and web_sales.ws_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1189 and 1189 + 11
) hot_cust
;

-- start query 39 in stream 0 using template query39.tpl
with inv as
(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
,stdev,mean, case mean when 0 then null else stdev/mean end cov
from(select w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy
,stddev_samp(inv_quantity_on_hand) stdev,avg(inv_quantity_on_hand) mean
from inventory
,item
,warehouse
,date_dim
where inv_item_sk = i_item_sk
and inv_warehouse_sk = w_warehouse_sk
and inv_date_sk = d_date_sk
and d_year =2000
group by w_warehouse_name,w_warehouse_sk,i_item_sk,d_moy) foo
where case mean when 0 then 0 else stdev/mean end > 1)
select inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean, inv1.cov
,inv2.w_warehouse_sk,inv2.i_item_sk,inv2.d_moy,inv2.mean, inv2.cov
from inv inv1,inv inv2
where inv1.i_item_sk = inv2.i_item_sk
and inv1.w_warehouse_sk = inv2.w_warehouse_sk
and inv1.d_moy=1
and inv2.d_moy=1+1
order by inv1.w_warehouse_sk,inv1.i_item_sk,inv1.d_moy,inv1.mean,inv1.cov
,inv2.d_moy,inv2.mean, inv2.cov
;

-- start query 40 in stream 0 using template query40.tpl
select top 100
w_state
,i_item_id
,sum(case when (cast(d_date as date) < cast ('2001-05-02' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_before
,sum(case when (cast(d_date as date) >= cast ('2001-05-02' as date))
then cs_sales_price - coalesce(cr_refunded_cash,0) else 0 end) as sales_after
from
catalog_sales left outer join catalog_returns on
(cs_order_number = cr_order_number
and cs_item_sk = cr_item_sk)
,warehouse
,item
,date_dim
where
i_current_price between 0.99 and 1.49
and i_item_sk = cs_item_sk
and cs_warehouse_sk = w_warehouse_sk
and cs_sold_date_sk = d_date_sk
and d_date between (date_sub(cast ('2001-05-02' as date),interval 30 day))
and (date_add(cast('2001-05-02' as date),interval 30 day))
group by
w_state,i_item_id
order by w_state,i_item_id
;

-- start query 41 in stream 0 using template query41.tpl
select top 100 i_product_name
from item i1
where i_manufact_id between 704 and 744
and (select count(*) as item_cnt
from item
where (i_manufact = i1.i_manufact and
((i_category = 'Women' and
(i_color = 'forest' or i_color = 'lime') and
(i_units = 'Pallet' or i_units = 'Pound') and
(i_size = 'economy' or i_size = 'small')
) or
(i_category = 'Women' and
(i_color = 'navy' or i_color = 'slate') and
(i_units = 'Gross' or i_units = 'Bunch') and
(i_size = 'extra large' or i_size = 'petite')
) or
(i_category = 'Men' and
(i_color = 'powder' or i_color = 'sky') and
(i_units = 'Dozen' or i_units = 'Lb') and
(i_size = 'N/A' or i_size = 'large')
) or
(i_category = 'Men' and
(i_color = 'maroon' or i_color = 'smoke') and
(i_units = 'Ounce' or i_units = 'Case') and
(i_size = 'economy' or i_size = 'small')
))) or
(i_manufact = i1.i_manufact and
((i_category = 'Women' and
(i_color = 'dark' or i_color = 'aquamarine') and
(i_units = 'Ton' or i_units = 'Tbl') and
(i_size = 'economy' or i_size = 'small')
) or
(i_category = 'Women' and
(i_color = 'frosted' or i_color = 'plum') and
(i_units = 'Dram' or i_units = 'Box') and
(i_size = 'extra large' or i_size = 'petite')
) or
(i_category = 'Men' and
(i_color = 'papaya' or i_color = 'peach') and
(i_units = 'Bundle' or i_units = 'Carton') and
(i_size = 'N/A' or i_size = 'large')
) or
(i_category = 'Men' and
(i_color = 'firebrick' or i_color = 'sienna') and
(i_units = 'Cup' or i_units = 'Each') and
(i_size = 'economy' or i_size = 'small')
)))) > 0
group by i1.i_product_name
order by i1.i_product_name
;

-- start query 42 in stream 0 using template query42.tpl
select top 100 dt.d_year
,item.i_category_id
,item.i_category
,sum(ss_ext_sales_price)
from date_dim dt
,store_sales
,item
where dt.d_date_sk = store_sales.ss_sold_date_sk
and store_sales.ss_item_sk = item.i_item_sk
and item.i_manager_id = 1
and dt.d_moy=11
and dt.d_year=1998
group by dt.d_year
,item.i_category_id
,item.i_category
order by sum(ss_ext_sales_price) desc,dt.d_year
,item.i_category_id
,item.i_category
;

-- start query 43 in stream 0 using template query43.tpl
select top 100 s_store_name, s_store_id,
sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
from date_dim, store_sales, store
where d_date_sk = ss_sold_date_sk and
s_store_sk = ss_store_sk and
s_gmt_offset = -5 and
d_year = 2000
group by s_store_name, s_store_id
order by s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
;

-- start query 44 in stream 0 using template query44.tpl
select top 100 asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing
from(select *
from (select item_sk,rank() over (order by rank_col asc) rnk
from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
from store_sales ss1
where ss_store_sk = 4
group by ss_item_sk
having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
from store_sales
where ss_store_sk = 4
and ss_hdemo_sk is null
group by ss_store_sk))V1)V11
where rnk < 11) asceding,
(select *
from (select item_sk,rank() over (order by rank_col desc) rnk
from (select ss_item_sk item_sk,avg(ss_net_profit) rank_col
from store_sales ss1
where ss_store_sk = 4
group by ss_item_sk
having avg(ss_net_profit) > 0.9*(select avg(ss_net_profit) rank_col
from store_sales
where ss_store_sk = 4
and ss_hdemo_sk is null
group by ss_store_sk))V2)V21
where rnk < 11) descending,
item i1,
item i2
where asceding.rnk = descending.rnk
and i1.i_item_sk=asceding.item_sk
and i2.i_item_sk=descending.item_sk
order by asceding.rnk
;

-- start query 45 in stream 0 using template query45.tpl
select top 100 ca_zip, ca_city, sum(ws_sales_price)
from web_sales, customer, customer_address, date_dim, item
where ws_bill_customer_sk = c_customer_sk
and c_current_addr_sk = ca_address_sk
and ws_item_sk = i_item_sk
and ( substr(ca_zip,1,5) in ('85669', '86197','88274','83405','86475', '85392', '85460', '80348', '81792')
or
i_item_id in (select i_item_id
from item
where i_item_sk in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)
)
)
and ws_sold_date_sk = d_date_sk
and d_qoy = 1 and d_year = 2000
group by ca_zip, ca_city
order by ca_zip, ca_city
;

-- start query 46 in stream 0 using template query46.tpl
select top 100 c_last_name
,c_first_name
,ca_city
,bought_city
,ss_ticket_number
,amt,profit
from
(select ss_ticket_number
,ss_customer_sk
,ca_city bought_city
,sum(ss_coupon_amt) amt
,sum(ss_net_profit) profit
from store_sales,date_dim,store,household_demographics,customer_address
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and store_sales.ss_addr_sk = customer_address.ca_address_sk
and (household_demographics.hd_dep_count = 8 or
household_demographics.hd_vehicle_count= 0)
and date_dim.d_dow in (6,0)
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_city in ('Midway','Fairview','Fairview','Midway','Fairview')
group by ss_ticket_number,ss_customer_sk,ss_addr_sk,ca_city) dn,customer,customer_address current_addr
where ss_customer_sk = c_customer_sk
and customer.c_current_addr_sk = current_addr.ca_address_sk
and current_addr.ca_city <> bought_city
order by c_last_name
,c_first_name
,ca_city
,bought_city
,ss_ticket_number
;

-- start query 47 in stream 0 using template query47.tpl
with v1 as(
select i_category, i_brand,
s_store_name, s_company_name,
d_year, d_moy,
sum(ss_sales_price) sum_sales,
avg(sum(ss_sales_price)) over
(partition by i_category, i_brand,
s_store_name, s_company_name, d_year)
avg_monthly_sales,
rank() over
(partition by i_category, i_brand,
s_store_name, s_company_name
order by d_year, d_moy) rn
from item, store_sales, date_dim, store
where ss_item_sk = i_item_sk and
ss_sold_date_sk = d_date_sk and
ss_store_sk = s_store_sk and
(
d_year = 2000 or
( d_year = 2000-1 and d_moy =12) or
( d_year = 2000+1 and d_moy =1)
)
group by i_category, i_brand,
s_store_name, s_company_name,
d_year, d_moy),
v2 as(
select v1.s_store_name, v1.s_company_name
,v1.d_year
,v1.avg_monthly_sales
,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
from v1, v1 v1_lag, v1 v1_lead
where v1.i_category = v1_lag.i_category and
v1.i_category = v1_lead.i_category and
v1.i_brand = v1_lag.i_brand and
v1.i_brand = v1_lead.i_brand and
v1.s_store_name = v1_lag.s_store_name and
v1.s_store_name = v1_lead.s_store_name and
v1.s_company_name = v1_lag.s_company_name and
v1.s_company_name = v1_lead.s_company_name and
v1.rn = v1_lag.rn + 1 and
v1.rn = v1_lead.rn - 1)
select top 100 *
from v2
where d_year = 2000 and
avg_monthly_sales > 0 and
case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
order by sum_sales - avg_monthly_sales, nsum
;

-- start query 48 in stream 0 using template query48.tpl
select sum (ss_quantity)
from store_sales, store, customer_demographics, customer_address, date_dim
where s_store_sk = ss_store_sk
and ss_sold_date_sk = d_date_sk and d_year = 2001
and
(
(
cd_demo_sk = ss_cdemo_sk
and
cd_marital_status = 'S'
and
cd_education_status = 'Secondary'
and
ss_sales_price between 100.00 and 150.00
)
or
(
cd_demo_sk = ss_cdemo_sk
and
cd_marital_status = 'M'
and
cd_education_status = '2 yr Degree'
and
ss_sales_price between 50.00 and 100.00
)
or
(
cd_demo_sk = ss_cdemo_sk
and
cd_marital_status = 'D'
and
cd_education_status = 'Advanced Degree'
and
ss_sales_price between 150.00 and 200.00
)
)
and
(
(
ss_addr_sk = ca_address_sk
and
ca_country = 'United States'
and
ca_state in ('ND', 'NY', 'SD')
and ss_net_profit between 0 and 2000
)
or
(ss_addr_sk = ca_address_sk
and
ca_country = 'United States'
and
ca_state in ('MD', 'GA', 'KS')
and ss_net_profit between 150 and 3000
)
or
(ss_addr_sk = ca_address_sk
and
ca_country = 'United States'
and
ca_state in ('CO', 'MN', 'NC')
and ss_net_profit between 50 and 25000
)
)
;

-- start query 49 in stream 0 using template query49.tpl
select top 100 channel, item, return_ratio, return_rank, currency_rank from
(select
'web' as channel
,web.item
,web.return_ratio
,web.return_rank
,web.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select ws.ws_item_sk as item
,(cast(sum(coalesce(wr.wr_return_quantity,0)) as decimal(15,4))/
cast(sum(coalesce(ws.ws_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(wr.wr_return_amt,0)) as decimal(15,4))/
cast(sum(coalesce(ws.ws_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
web_sales ws left outer join web_returns wr
on (ws.ws_order_number = wr.wr_order_number and
ws.ws_item_sk = wr.wr_item_sk)
,date_dim
where
wr.wr_return_amt > 10000
and ws.ws_net_profit > 1
and ws.ws_net_paid > 0
and ws.ws_quantity > 0
and ws_sold_date_sk = d_date_sk
and d_year = 1998
and d_moy = 11
group by ws.ws_item_sk
) in_web
) web
where
(
web.return_rank <= 10
or
web.currency_rank <= 10
)
union
select
'catalog' as channel
,catalog.item
,catalog.return_ratio
,catalog.return_rank
,catalog.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select
cs.cs_item_sk as item
,(cast(sum(coalesce(cr.cr_return_quantity,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(cr.cr_return_amount,0)) as decimal(15,4))/
cast(sum(coalesce(cs.cs_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
catalog_sales cs left outer join catalog_returns cr
on (cs.cs_order_number = cr.cr_order_number and
cs.cs_item_sk = cr.cr_item_sk)
,date_dim
where
cr.cr_return_amount > 10000
and cs.cs_net_profit > 1
and cs.cs_net_paid > 0
and cs.cs_quantity > 0
and cs_sold_date_sk = d_date_sk
and d_year = 1998
and d_moy = 11
group by cs.cs_item_sk
) in_cat
) catalog
where
(
catalog.return_rank <= 10
or
catalog.currency_rank <=10
)
union
select
'store' as channel
,store.item
,store.return_ratio
,store.return_rank
,store.currency_rank
from (
select
item
,return_ratio
,currency_ratio
,rank() over (order by return_ratio) as return_rank
,rank() over (order by currency_ratio) as currency_rank
from
( select sts.ss_item_sk as item
,(cast(sum(coalesce(sr.sr_return_quantity,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_quantity,0)) as decimal(15,4) )) as return_ratio
,(cast(sum(coalesce(sr.sr_return_amt,0)) as decimal(15,4))/cast(sum(coalesce(sts.ss_net_paid,0)) as decimal(15,4) )) as currency_ratio
from
store_sales sts left outer join store_returns sr
on (sts.ss_ticket_number = sr.sr_ticket_number and sts.ss_item_sk = sr.sr_item_sk)
,date_dim
where
sr.sr_return_amt > 10000
and sts.ss_net_profit > 1
and sts.ss_net_paid > 0
and sts.ss_quantity > 0
and ss_sold_date_sk = d_date_sk
and d_year = 1998
and d_moy = 11
group by sts.ss_item_sk
) in_store
) store
where (
store.return_rank <= 10
or
store.currency_rank <= 10
)
)
order by 1,4,5,2
;

-- start query 50 in stream 0 using template query50.tpl
select top 100
s_store_name
,s_company_id
,s_street_number
,s_street_name
,s_street_type
,s_suite_number
,s_city
,s_county
,s_state
,s_zip
,sum(case when (sr_returned_date_sk - ss_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 30) and
(sr_returned_date_sk - ss_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 60) and
(sr_returned_date_sk - ss_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 90) and
(sr_returned_date_sk - ss_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
,sum(case when (sr_returned_date_sk - ss_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
store_sales
,store_returns
,store
,date_dim d1
,date_dim d2
where
d2.d_year = 2001
and d2.d_moy = 8
and ss_ticket_number = sr_ticket_number
and ss_item_sk = sr_item_sk
and ss_sold_date_sk = d1.d_date_sk
and sr_returned_date_sk = d2.d_date_sk
and ss_customer_sk = sr_customer_sk
and ss_store_sk = s_store_sk
group by
s_store_name
,s_company_id
,s_street_number
,s_street_name
,s_street_type
,s_suite_number
,s_city
,s_county
,s_state
,s_zip
order by s_store_name
,s_company_id
,s_street_number
,s_street_name
,s_street_type
,s_suite_number
,s_city
,s_county
,s_state
,s_zip
;

-- start query 51 in stream 0 using template query51.tpl
WITH web_v1 as (
select
ws_item_sk item_sk, d_date,
sum(sum(ws_sales_price))
over (partition by ws_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from web_sales
,date_dim
where ws_sold_date_sk=d_date_sk
and d_month_seq between 1212 and 1212+11
and ws_item_sk is not NULL
group by ws_item_sk, d_date),
store_v1 as (
select
ss_item_sk item_sk, d_date,
sum(sum(ss_sales_price))
over (partition by ss_item_sk order by d_date rows between unbounded preceding and current row) cume_sales
from store_sales
,date_dim
where ss_sold_date_sk=d_date_sk
and d_month_seq between 1212 and 1212+11
and ss_item_sk is not NULL
group by ss_item_sk, d_date)
select top 100 *
from (select item_sk
,d_date
,web_sales
,store_sales
,max(web_sales)
over (partition by item_sk order by d_date rows between unbounded preceding and current row) web_cumulative
,max(store_sales)
over (partition by item_sk order by d_date rows between unbounded preceding and current row) store_cumulative
from (select case when web.item_sk is not null then web.item_sk else store.item_sk end item_sk
,case when web.d_date is not null then web.d_date else store.d_date end d_date
,web.cume_sales web_sales
,store.cume_sales store_sales
from web_v1 web full outer join store_v1 store on (web.item_sk = store.item_sk
and web.d_date = store.d_date)
)x )y
where web_cumulative > store_cumulative
order by item_sk
,d_date
;

-- start query 52 in stream 0 using template query52.tpl
select top 100 dt.d_year
,item.i_brand_id brand_id
,item.i_brand brand
,sum(ss_ext_sales_price) ext_price
from date_dim dt
,store_sales
,item
where dt.d_date_sk = store_sales.ss_sold_date_sk
and store_sales.ss_item_sk = item.i_item_sk
and item.i_manager_id = 1
and dt.d_moy=12
and dt.d_year=2000
group by dt.d_year
,item.i_brand
,item.i_brand_id
order by dt.d_year
,ext_price desc
,brand_id
;

-- start query 53 in stream 0 using template query53.tpl
select top 100 * from
(select i_manufact_id,
sum(ss_sales_price) sum_sales,
avg(sum(ss_sales_price)) over (partition by i_manufact_id) avg_quarterly_sales
from item, store_sales, date_dim, store
where ss_item_sk = i_item_sk and
ss_sold_date_sk = d_date_sk and
ss_store_sk = s_store_sk and
d_month_seq in (1186,1186+1,1186+2,1186+3,1186+4,1186+5,1186+6,1186+7,1186+8,1186+9,1186+10,1186+11) and
((i_category in ('Books','Children','Electronics') and
i_class in ('personal','portable','reference','self-help') and
i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
'exportiunivamalg #9','scholaramalgamalg #9'))
or(i_category in ('Women','Music','Men') and
i_class in ('accessories','classical','fragrances','pants') and
i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
'importoamalg #1')))
group by i_manufact_id, d_qoy ) tmp1
where case when avg_quarterly_sales > 0
then abs (sum_sales - avg_quarterly_sales)/ avg_quarterly_sales
else null end > 0.1
order by avg_quarterly_sales,
sum_sales,
i_manufact_id
;

-- start query 54 in stream 0 using template query54.tpl
with my_customers as (
select distinct c_customer_sk
, c_current_addr_sk
from
( select cs_sold_date_sk sold_date_sk,
cs_bill_customer_sk customer_sk,
cs_item_sk item_sk
from catalog_sales
union all
select ws_sold_date_sk sold_date_sk,
ws_bill_customer_sk customer_sk,
ws_item_sk item_sk
from web_sales
) cs_or_ws_sales,
item,
date_dim,
customer
where sold_date_sk = d_date_sk
and item_sk = i_item_sk
and i_category = 'Music'
and i_class = 'country'
and c_customer_sk = cs_or_ws_sales.customer_sk
and d_moy = 1
and d_year = 1999
)
, my_revenue as (
select c_customer_sk,
sum(ss_ext_sales_price) as revenue
from my_customers,
store_sales,
customer_address,
store,
date_dim
where c_current_addr_sk = ca_address_sk
and ca_county = s_county
and ca_state = s_state
and ss_sold_date_sk = d_date_sk
and c_customer_sk = ss_customer_sk
and d_month_seq between (select distinct d_month_seq+1
from date_dim where d_year = 1999 and d_moy = 1)
and (select distinct d_month_seq+3
from date_dim where d_year = 1999 and d_moy = 1)
group by c_customer_sk
)
, segments as
(select cast((revenue/50) as int) as segment
from my_revenue
)
select top 100 segment, count(*) as num_customers, segment*50 as segment_base
from segments
group by segment
order by segment, num_customers
;

-- start query 55 in stream 0 using template query55.tpl
select top 100 i_brand_id brand_id, i_brand brand,
sum(ss_ext_sales_price) ext_price
from date_dim, store_sales, item
where d_date_sk = ss_sold_date_sk
and ss_item_sk = i_item_sk
and i_manager_id=52
and d_moy=11
and d_year=2000
group by i_brand, i_brand_id
order by ext_price desc, i_brand_id
;

-- start query 56 in stream 0 using template query56.tpl
with ss as (
select i_item_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where i_item_id in (select
i_item_id
from item
where i_color in ('powder','orchid','pink'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 3
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id),
cs as (
select i_item_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from item
where i_color in ('powder','orchid','pink'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 3
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id),
ws as (
select i_item_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from item
where i_color in ('powder','orchid','pink'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 3
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -6
group by i_item_id)
select top 100 i_item_id ,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_item_id
order by total_sales,
i_item_id
;

-- start query 57 in stream 0 using template query57.tpl
with v1 as(
select i_category, i_brand,
cc_name,
d_year, d_moy,
sum(cs_sales_price) sum_sales,
avg(sum(cs_sales_price)) over
(partition by i_category, i_brand,
cc_name, d_year)
avg_monthly_sales,
rank() over
(partition by i_category, i_brand,
cc_name
order by d_year, d_moy) rn
from item, catalog_sales, date_dim, call_center
where cs_item_sk = i_item_sk and
cs_sold_date_sk = d_date_sk and
cc_call_center_sk= cs_call_center_sk and
(
d_year = 2001 or
( d_year = 2001-1 and d_moy =12) or
( d_year = 2001+1 and d_moy =1)
)
group by i_category, i_brand,
cc_name , d_year, d_moy),
v2 as(
select v1.i_category, v1.i_brand, v1.cc_name
,v1.d_year
,v1.avg_monthly_sales
,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum
from v1, v1 v1_lag, v1 v1_lead
where v1.i_category = v1_lag.i_category and
v1.i_category = v1_lead.i_category and
v1.i_brand = v1_lag.i_brand and
v1.i_brand = v1_lead.i_brand and
v1. cc_name = v1_lag. cc_name and
v1. cc_name = v1_lead. cc_name and
v1.rn = v1_lag.rn + 1 and
v1.rn = v1_lead.rn - 1)
select top 100 *
from v2
where d_year = 2001 and
avg_monthly_sales > 0 and
case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
order by sum_sales - avg_monthly_sales, avg_monthly_sales
;

-- start query 58 in stream 0 using template query58.tpl
with ss_items as
(select i_item_id item_id
,sum(ss_ext_sales_price) ss_item_rev
from store_sales
,item
,date_dim
where ss_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq = (select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and ss_sold_date_sk = d_date_sk
group by i_item_id),
cs_items as
(select i_item_id item_id
,sum(cs_ext_sales_price) cs_item_rev
from catalog_sales
,item
,date_dim
where cs_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq = (select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and cs_sold_date_sk = d_date_sk
group by i_item_id),
ws_items as
(select i_item_id item_id
,sum(ws_ext_sales_price) ws_item_rev
from web_sales
,item
,date_dim
where ws_item_sk = i_item_sk
and d_date in (select d_date
from date_dim
where d_week_seq =(select d_week_seq
from date_dim
where d_date = '2001-06-16'))
and ws_sold_date_sk = d_date_sk
group by i_item_id)
select top 100 ss_items.item_id
,ss_item_rev
,ss_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ss_dev
,cs_item_rev
,cs_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 cs_dev
,ws_item_rev
,ws_item_rev/((ss_item_rev+cs_item_rev+ws_item_rev)/3) * 100 ws_dev
,(ss_item_rev+cs_item_rev+ws_item_rev)/3 average
from ss_items,cs_items,ws_items
where ss_items.item_id=cs_items.item_id
and ss_items.item_id=ws_items.item_id
and ss_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
and ss_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
and cs_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
and cs_item_rev between 0.9 * ws_item_rev and 1.1 * ws_item_rev
and ws_item_rev between 0.9 * ss_item_rev and 1.1 * ss_item_rev
and ws_item_rev between 0.9 * cs_item_rev and 1.1 * cs_item_rev
order by ss_items.item_id
,ss_item_rev
;

-- start query 59 in stream 0 using template query59.tpl
with wss as
(select d_week_seq,
ss_store_sk,
sum(case when (d_day_name='Sunday') then ss_sales_price else null end) sun_sales,
sum(case when (d_day_name='Monday') then ss_sales_price else null end) mon_sales,
sum(case when (d_day_name='Tuesday') then ss_sales_price else null end) tue_sales,
sum(case when (d_day_name='Wednesday') then ss_sales_price else null end) wed_sales,
sum(case when (d_day_name='Thursday') then ss_sales_price else null end) thu_sales,
sum(case when (d_day_name='Friday') then ss_sales_price else null end) fri_sales,
sum(case when (d_day_name='Saturday') then ss_sales_price else null end) sat_sales
from store_sales,date_dim
where d_date_sk = ss_sold_date_sk
group by d_week_seq,ss_store_sk
)
select top 100 s_store_name1,s_store_id1,d_week_seq1
,sun_sales1/sun_sales2,mon_sales1/mon_sales2
,tue_sales1/tue_sales2,wed_sales1/wed_sales2,thu_sales1/thu_sales2
,fri_sales1/fri_sales2,sat_sales1/sat_sales2
from
(select s_store_name s_store_name1,wss.d_week_seq d_week_seq1
,s_store_id s_store_id1,sun_sales sun_sales1
,mon_sales mon_sales1,tue_sales tue_sales1
,wed_sales wed_sales1,thu_sales thu_sales1
,fri_sales fri_sales1,sat_sales sat_sales1
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
ss_store_sk = s_store_sk and
d_month_seq between 1195 and 1195 + 11) y,
(select s_store_name s_store_name2,wss.d_week_seq d_week_seq2
,s_store_id s_store_id2,sun_sales sun_sales2
,mon_sales mon_sales2,tue_sales tue_sales2
,wed_sales wed_sales2,thu_sales thu_sales2
,fri_sales fri_sales2,sat_sales sat_sales2
from wss,store,date_dim d
where d.d_week_seq = wss.d_week_seq and
ss_store_sk = s_store_sk and
d_month_seq between 1195+ 12 and 1195 + 23) x
where s_store_id1=s_store_id2
and d_week_seq1=d_week_seq2-52
order by s_store_name1,s_store_id1,d_week_seq1
;

-- start query 60 in stream 0 using template query60.tpl
with ss as (
select
i_item_id,sum(ss_ext_sales_price) total_sales
from
store_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Jewelry'))
and ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 10
and ss_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_item_id),
cs as (
select
i_item_id,sum(cs_ext_sales_price) total_sales
from
catalog_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Jewelry'))
and cs_item_sk = i_item_sk
and cs_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 10
and cs_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_item_id),
ws as (
select
i_item_id,sum(ws_ext_sales_price) total_sales
from
web_sales,
date_dim,
customer_address,
item
where
i_item_id in (select
i_item_id
from
item
where i_category in ('Jewelry'))
and ws_item_sk = i_item_sk
and ws_sold_date_sk = d_date_sk
and d_year = 2000
and d_moy = 10
and ws_bill_addr_sk = ca_address_sk
and ca_gmt_offset = -5
group by i_item_id)
select top 100
i_item_id
,sum(total_sales) total_sales
from (select * from ss
union all
select * from cs
union all
select * from ws) tmp1
group by i_item_id
order by i_item_id
,total_sales
;

-- start query 61 in stream 0 using template query61.tpl
select top 100 promotions,total,cast(promotions as decimal(15,4))/cast(total as decimal(15,4))*100
from
(select sum(ss_ext_sales_price) promotions
from store_sales
,store
,promotion
,date_dim
,customer
,customer_address
,item
where ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and ss_promo_sk = p_promo_sk
and ss_customer_sk= c_customer_sk
and ca_address_sk = c_current_addr_sk
and ss_item_sk = i_item_sk
and ca_gmt_offset = -7
and i_category = 'Home'
and (p_channel_dmail = 'Y' or p_channel_email = 'Y' or p_channel_tv = 'Y')
and s_gmt_offset = -7
and d_year = 2000
and d_moy = 12) promotional_sales,
(select sum(ss_ext_sales_price) total
from store_sales
,store
,date_dim
,customer
,customer_address
,item
where ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and ss_customer_sk= c_customer_sk
and ca_address_sk = c_current_addr_sk
and ss_item_sk = i_item_sk
and ca_gmt_offset = -7
and i_category = 'Home'
and s_gmt_offset = -7
and d_year = 2000
and d_moy = 12) all_sales
order by promotions, total
;

-- start query 62 in stream 0 using template query62.tpl
select top 100
substr(w_warehouse_name,1,20)
,sm_type
,web_name
,sum(case when (ws_ship_date_sk - ws_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 30) and
(ws_ship_date_sk - ws_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 60) and
(ws_ship_date_sk - ws_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 90) and
(ws_ship_date_sk - ws_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
,sum(case when (ws_ship_date_sk - ws_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
web_sales
,warehouse
,ship_mode
,web_site
,date_dim
where
d_month_seq between 1223 and 1223 + 11
and ws_ship_date_sk = d_date_sk
and ws_warehouse_sk = w_warehouse_sk
and ws_ship_mode_sk = sm_ship_mode_sk
and ws_web_site_sk = web_site_sk
group by
substr(w_warehouse_name,1,20)
,sm_type
,web_name
order by substr(w_warehouse_name,1,20)
,sm_type
,web_name
;

-- start query 63 in stream 0 using template query63.tpl
select top 100 *
from (select i_manager_id
,sum(ss_sales_price) sum_sales
,avg(sum(ss_sales_price)) over (partition by i_manager_id) avg_monthly_sales
from item
,store_sales
,date_dim
,store
where ss_item_sk = i_item_sk
and ss_sold_date_sk = d_date_sk
and ss_store_sk = s_store_sk
and d_month_seq in (1222,1222+1,1222+2,1222+3,1222+4,1222+5,1222+6,1222+7,1222+8,1222+9,1222+10,1222+11)
and (( i_category in ('Books','Children','Electronics')
and i_class in ('personal','portable','reference','self-help')
and i_brand in ('scholaramalgamalg #14','scholaramalgamalg #7',
'exportiunivamalg #9','scholaramalgamalg #9'))
or( i_category in ('Women','Music','Men')
and i_class in ('accessories','classical','fragrances','pants')
and i_brand in ('amalgimporto #1','edu packscholar #1','exportiimporto #1',
'importoamalg #1')))
group by i_manager_id, d_moy) tmp1
where case when avg_monthly_sales > 0 then abs (sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1
order by i_manager_id
,avg_monthly_sales
,sum_sales
;

-- start query 64 in stream 0 using template query64.tpl
with cs_ui as
(select cs_item_sk
,sum(cs_ext_list_price) as sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund
from catalog_sales
,catalog_returns
where cs_item_sk = cr_item_sk
and cs_order_number = cr_order_number
group by cs_item_sk
having sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)),
cross_sales as
(select i_product_name product_name
,i_item_sk item_sk
,s_store_name store_name
,s_zip store_zip
,ad1.ca_street_number b_street_number
,ad1.ca_street_name b_street_name
,ad1.ca_city b_city
,ad1.ca_zip b_zip
,ad2.ca_street_number c_street_number
,ad2.ca_street_name c_street_name
,ad2.ca_city c_city
,ad2.ca_zip c_zip
,d1.d_year as syear
,d2.d_year as fsyear
,d3.d_year s2year
,count(*) cnt
,sum(ss_wholesale_cost) s1
,sum(ss_list_price) s2
,sum(ss_coupon_amt) s3
FROM store_sales
,store_returns
,cs_ui
,date_dim d1
,date_dim d2
,date_dim d3
,store
,customer
,customer_demographics cd1
,customer_demographics cd2
,promotion
,household_demographics hd1
,household_demographics hd2
,customer_address ad1
,customer_address ad2
,income_band ib1
,income_band ib2
,item
WHERE ss_store_sk = s_store_sk AND
ss_sold_date_sk = d1.d_date_sk AND
ss_customer_sk = c_customer_sk AND
ss_cdemo_sk= cd1.cd_demo_sk AND
ss_hdemo_sk = hd1.hd_demo_sk AND
ss_addr_sk = ad1.ca_address_sk and
ss_item_sk = i_item_sk and
ss_item_sk = sr_item_sk and
ss_ticket_number = sr_ticket_number and
ss_item_sk = cs_ui.cs_item_sk and
c_current_cdemo_sk = cd2.cd_demo_sk AND
c_current_hdemo_sk = hd2.hd_demo_sk AND
c_current_addr_sk = ad2.ca_address_sk and
c_first_sales_date_sk = d2.d_date_sk and
c_first_shipto_date_sk = d3.d_date_sk and
ss_promo_sk = p_promo_sk and
hd1.hd_income_band_sk = ib1.ib_income_band_sk and
hd2.hd_income_band_sk = ib2.ib_income_band_sk and
cd1.cd_marital_status <> cd2.cd_marital_status and
i_color in ('orange','lace','lawn','misty','blush','pink') and
i_current_price between 48 and 48 + 10 and
i_current_price between 48 + 1 and 48 + 15
group by i_product_name
,i_item_sk
,s_store_name
,s_zip
,ad1.ca_street_number
,ad1.ca_street_name
,ad1.ca_city
,ad1.ca_zip
,ad2.ca_street_number
,ad2.ca_street_name
,ad2.ca_city
,ad2.ca_zip
,d1.d_year
,d2.d_year
,d3.d_year
)
select cs1.product_name
,cs1.store_name
,cs1.store_zip
,cs1.b_street_number
,cs1.b_street_name
,cs1.b_city
,cs1.b_zip
,cs1.c_street_number
,cs1.c_street_name
,cs1.c_city
,cs1.c_zip
,cs1.syear
,cs1.cnt
,cs1.s1 as s11
,cs1.s2 as s21
,cs1.s3 as s31
,cs2.s1 as s12
,cs2.s2 as s22
,cs2.s3 as s32
,cs2.syear
,cs2.cnt
from cross_sales cs1,cross_sales cs2
where cs1.item_sk=cs2.item_sk and
cs1.syear = 1999 and
cs2.syear = 1999 + 1 and
cs2.cnt <= cs1.cnt and
cs1.store_name = cs2.store_name and
cs1.store_zip = cs2.store_zip
order by cs1.product_name
,cs1.store_name
,cs2.cnt
,cs1.s1
,cs2.s1
;

-- start query 65 in stream 0 using template query65.tpl
select top 100
s_store_name,
i_item_desc,
sc.revenue,
i_current_price,
i_wholesale_cost,
i_brand
from store, item,
(select ss_store_sk, avg(revenue) as ave
from
(select ss_store_sk, ss_item_sk,
sum(ss_sales_price) as revenue
from store_sales, date_dim
where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
group by ss_store_sk, ss_item_sk) sa
group by ss_store_sk) sb,
(select ss_store_sk, ss_item_sk, sum(ss_sales_price) as revenue
from store_sales, date_dim
where ss_sold_date_sk = d_date_sk and d_month_seq between 1176 and 1176+11
group by ss_store_sk, ss_item_sk) sc
where sb.ss_store_sk = sc.ss_store_sk and
sc.revenue <= 0.1 * sb.ave and
s_store_sk = sc.ss_store_sk and
i_item_sk = sc.ss_item_sk
order by s_store_name, i_item_desc
;

-- start query 66 in stream 0 using template query66.tpl
select top 100
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,ship_carriers
,year
,sum(jan_sales) as jan_sales
,sum(feb_sales) as feb_sales
,sum(mar_sales) as mar_sales
,sum(apr_sales) as apr_sales
,sum(may_sales) as may_sales
,sum(jun_sales) as jun_sales
,sum(jul_sales) as jul_sales
,sum(aug_sales) as aug_sales
,sum(sep_sales) as sep_sales
,sum(oct_sales) as oct_sales
,sum(nov_sales) as nov_sales
,sum(dec_sales) as dec_sales
,sum(jan_sales/w_warehouse_sq_ft) as jan_sales_per_sq_foot
,sum(feb_sales/w_warehouse_sq_ft) as feb_sales_per_sq_foot
,sum(mar_sales/w_warehouse_sq_ft) as mar_sales_per_sq_foot
,sum(apr_sales/w_warehouse_sq_ft) as apr_sales_per_sq_foot
,sum(may_sales/w_warehouse_sq_ft) as may_sales_per_sq_foot
,sum(jun_sales/w_warehouse_sq_ft) as jun_sales_per_sq_foot
,sum(jul_sales/w_warehouse_sq_ft) as jul_sales_per_sq_foot
,sum(aug_sales/w_warehouse_sq_ft) as aug_sales_per_sq_foot
,sum(sep_sales/w_warehouse_sq_ft) as sep_sales_per_sq_foot
,sum(oct_sales/w_warehouse_sq_ft) as oct_sales_per_sq_foot
,sum(nov_sales/w_warehouse_sq_ft) as nov_sales_per_sq_foot
,sum(dec_sales/w_warehouse_sq_ft) as dec_sales_per_sq_foot
,sum(jan_net) as jan_net
,sum(feb_net) as feb_net
,sum(mar_net) as mar_net
,sum(apr_net) as apr_net
,sum(may_net) as may_net
,sum(jun_net) as jun_net
,sum(jul_net) as jul_net
,sum(aug_net) as aug_net
,sum(sep_net) as sep_net
,sum(oct_net) as oct_net
,sum(nov_net) as nov_net
,sum(dec_net) as dec_net
from (
select
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
,d_year as year
,sum(case when d_moy = 1
then ws_ext_sales_price* ws_quantity else 0 end) as jan_sales
,sum(case when d_moy = 2
then ws_ext_sales_price* ws_quantity else 0 end) as feb_sales
,sum(case when d_moy = 3
then ws_ext_sales_price* ws_quantity else 0 end) as mar_sales
,sum(case when d_moy = 4
then ws_ext_sales_price* ws_quantity else 0 end) as apr_sales
,sum(case when d_moy = 5
then ws_ext_sales_price* ws_quantity else 0 end) as may_sales
,sum(case when d_moy = 6
then ws_ext_sales_price* ws_quantity else 0 end) as jun_sales
,sum(case when d_moy = 7
then ws_ext_sales_price* ws_quantity else 0 end) as jul_sales
,sum(case when d_moy = 8
then ws_ext_sales_price* ws_quantity else 0 end) as aug_sales
,sum(case when d_moy = 9
then ws_ext_sales_price* ws_quantity else 0 end) as sep_sales
,sum(case when d_moy = 10
then ws_ext_sales_price* ws_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then ws_ext_sales_price* ws_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then ws_ext_sales_price* ws_quantity else 0 end) as dec_sales
,sum(case when d_moy = 1
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jan_net
,sum(case when d_moy = 2
then ws_net_paid_inc_ship * ws_quantity else 0 end) as feb_net
,sum(case when d_moy = 3
then ws_net_paid_inc_ship * ws_quantity else 0 end) as mar_net
,sum(case when d_moy = 4
then ws_net_paid_inc_ship * ws_quantity else 0 end) as apr_net
,sum(case when d_moy = 5
then ws_net_paid_inc_ship * ws_quantity else 0 end) as may_net
,sum(case when d_moy = 6
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jun_net
,sum(case when d_moy = 7
then ws_net_paid_inc_ship * ws_quantity else 0 end) as jul_net
,sum(case when d_moy = 8
then ws_net_paid_inc_ship * ws_quantity else 0 end) as aug_net
,sum(case when d_moy = 9
then ws_net_paid_inc_ship * ws_quantity else 0 end) as sep_net
,sum(case when d_moy = 10
then ws_net_paid_inc_ship * ws_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then ws_net_paid_inc_ship * ws_quantity else 0 end) as nov_net
,sum(case when d_moy = 12
then ws_net_paid_inc_ship * ws_quantity else 0 end) as dec_net
from
web_sales
,warehouse
,date_dim
,time_dim
,ship_mode
where
ws_warehouse_sk = w_warehouse_sk
and ws_sold_date_sk = d_date_sk
and ws_sold_time_sk = t_time_sk
and ws_ship_mode_sk = sm_ship_mode_sk
and d_year = 2001
and t_time between 42970 and 42970+28800
and sm_carrier in ('ORIENTAL','BOXBUNDLES')
group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,d_year
union all
select
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,'ORIENTAL' || ',' || 'BOXBUNDLES' as ship_carriers
,d_year as year
,sum(case when d_moy = 1
then cs_ext_list_price* cs_quantity else 0 end) as jan_sales
,sum(case when d_moy = 2
then cs_ext_list_price* cs_quantity else 0 end) as feb_sales
,sum(case when d_moy = 3
then cs_ext_list_price* cs_quantity else 0 end) as mar_sales
,sum(case when d_moy = 4
then cs_ext_list_price* cs_quantity else 0 end) as apr_sales
,sum(case when d_moy = 5
then cs_ext_list_price* cs_quantity else 0 end) as may_sales
,sum(case when d_moy = 6
then cs_ext_list_price* cs_quantity else 0 end) as jun_sales
,sum(case when d_moy = 7
then cs_ext_list_price* cs_quantity else 0 end) as jul_sales
,sum(case when d_moy = 8
then cs_ext_list_price* cs_quantity else 0 end) as aug_sales
,sum(case when d_moy = 9
then cs_ext_list_price* cs_quantity else 0 end) as sep_sales
,sum(case when d_moy = 10
then cs_ext_list_price* cs_quantity else 0 end) as oct_sales
,sum(case when d_moy = 11
then cs_ext_list_price* cs_quantity else 0 end) as nov_sales
,sum(case when d_moy = 12
then cs_ext_list_price* cs_quantity else 0 end) as dec_sales
,sum(case when d_moy = 1
then cs_net_paid * cs_quantity else 0 end) as jan_net
,sum(case when d_moy = 2
then cs_net_paid * cs_quantity else 0 end) as feb_net
,sum(case when d_moy = 3
then cs_net_paid * cs_quantity else 0 end) as mar_net
,sum(case when d_moy = 4
then cs_net_paid * cs_quantity else 0 end) as apr_net
,sum(case when d_moy = 5
then cs_net_paid * cs_quantity else 0 end) as may_net
,sum(case when d_moy = 6
then cs_net_paid * cs_quantity else 0 end) as jun_net
,sum(case when d_moy = 7
then cs_net_paid * cs_quantity else 0 end) as jul_net
,sum(case when d_moy = 8
then cs_net_paid * cs_quantity else 0 end) as aug_net
,sum(case when d_moy = 9
then cs_net_paid * cs_quantity else 0 end) as sep_net
,sum(case when d_moy = 10
then cs_net_paid * cs_quantity else 0 end) as oct_net
,sum(case when d_moy = 11
then cs_net_paid * cs_quantity else 0 end) as nov_net
,sum(case when d_moy = 12
then cs_net_paid * cs_quantity else 0 end) as dec_net
from
catalog_sales
,warehouse
,date_dim
,time_dim
,ship_mode
where
cs_warehouse_sk = w_warehouse_sk
and cs_sold_date_sk = d_date_sk
and cs_sold_time_sk = t_time_sk
and cs_ship_mode_sk = sm_ship_mode_sk
and d_year = 2001
and t_time between 42970 AND 42970+28800
and sm_carrier in ('ORIENTAL','BOXBUNDLES')
group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,d_year
) x
group by
w_warehouse_name
,w_warehouse_sq_ft
,w_city
,w_county
,w_state
,w_country
,ship_carriers
,year
order by w_warehouse_name
;

-- start query 67 in stream 0 using template query67.tpl
select top 100 *
from (select i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sumsales
,rank() over (partition by i_category order by sumsales desc) rk
from (select i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sum(coalesce(ss_sales_price*ss_quantity,0)) sumsales
from store_sales
,date_dim
,store
,item
where ss_sold_date_sk=d_date_sk
and ss_item_sk=i_item_sk
and ss_store_sk = s_store_sk
and d_month_seq between 1217 and 1217+11
group by rollup(i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy,s_store_id))dw1) dw2
where rk <= 100
order by i_category
,i_class
,i_brand
,i_product_name
,d_year
,d_qoy
,d_moy
,s_store_id
,sumsales
,rk
;

-- start query 68 in stream 0 using template query68.tpl
select top 100 c_last_name
,c_first_name
,ca_city
,bought_city
,ss_ticket_number
,extended_price
,extended_tax
,list_price
from (select ss_ticket_number
,ss_customer_sk
,ca_city bought_city
,sum(ss_ext_sales_price) extended_price
,sum(ss_ext_list_price) list_price
,sum(ss_ext_tax) extended_tax
from store_sales
,date_dim
,store
,household_demographics
,customer_address
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and store_sales.ss_addr_sk = customer_address.ca_address_sk
and date_dim.d_dom between 1 and 2
and (household_demographics.hd_dep_count = 3 or
household_demographics.hd_vehicle_count= 4)
and date_dim.d_year in (1998,1998+1,1998+2)
and store.s_city in ('Fairview','Midway')
group by ss_ticket_number
,ss_customer_sk
,ss_addr_sk,ca_city) dn
,customer
,customer_address current_addr
where ss_customer_sk = c_customer_sk
and customer.c_current_addr_sk = current_addr.ca_address_sk
and current_addr.ca_city <> bought_city
order by c_last_name
,ss_ticket_number
;

-- start query 69 in stream 0 using template query69.tpl
select top 100
cd_gender,
cd_marital_status,
cd_education_status,
count(*) cnt1,
cd_purchase_estimate,
count(*) cnt2,
cd_credit_rating,
count(*) cnt3
from
customer c,customer_address ca,customer_demographics
where
c.c_current_addr_sk = ca.ca_address_sk and
ca_state in ('IL','TX','ME') and
cd_demo_sk = c.c_current_cdemo_sk and
exists (select *
from store_sales,date_dim
where c.c_customer_sk = ss_customer_sk and
ss_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 1 and 1+2) and
(not exists (select *
from web_sales,date_dim
where c.c_customer_sk = ws_bill_customer_sk and
ws_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 1 and 1+2) and
not exists (select *
from catalog_sales,date_dim
where c.c_customer_sk = cs_ship_customer_sk and
cs_sold_date_sk = d_date_sk and
d_year = 2002 and
d_moy between 1 and 1+2))
group by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating
order by cd_gender,
cd_marital_status,
cd_education_status,
cd_purchase_estimate,
cd_credit_rating
;

-- start query 70 in stream 0 using template query70.tpl
select top 100
sum(ss_net_profit) as total_sum
,s_state
,s_county
,grouping(s_state)+grouping(s_county) as lochierarchy
,rank() over (
partition by grouping(s_state)+grouping(s_county),
case when grouping(s_county) = 0 then s_state end
order by sum(ss_net_profit) desc) as rank_within_parent
from
store_sales
,date_dim d1
,store
where
d1.d_month_seq between 1220 and 1220+11
and d1.d_date_sk = ss_sold_date_sk
and s_store_sk = ss_store_sk
and s_state in
( select s_state
from (select s_state as s_state,
rank() over ( partition by s_state order by sum(ss_net_profit) desc) as ranking
from store_sales, store, date_dim
where d_month_seq between 1220 and 1220+11
and d_date_sk = ss_sold_date_sk
and s_store_sk = ss_store_sk
group by s_state
) tmp1
where ranking <= 5
)
group by rollup(s_state,s_county)
order by
lochierarchy desc
,case when lochierarchy = 0 then s_state end
,rank_within_parent
;

-- start query 71 in stream 0 using template query71.tpl
select i_brand_id brand_id, i_brand brand,t_hour,t_minute,
sum(ext_price) ext_price
from item, (select ws_ext_sales_price as ext_price,
ws_sold_date_sk as sold_date_sk,
ws_item_sk as sold_item_sk,
ws_sold_time_sk as time_sk
from web_sales,date_dim
where d_date_sk = ws_sold_date_sk
and d_moy=12
and d_year=2002
union all
select cs_ext_sales_price as ext_price,
cs_sold_date_sk as sold_date_sk,
cs_item_sk as sold_item_sk,
cs_sold_time_sk as time_sk
from catalog_sales,date_dim
where d_date_sk = cs_sold_date_sk
and d_moy=12
and d_year=2002
union all
select ss_ext_sales_price as ext_price,
ss_sold_date_sk as sold_date_sk,
ss_item_sk as sold_item_sk,
ss_sold_time_sk as time_sk
from store_sales,date_dim
where d_date_sk = ss_sold_date_sk
and d_moy=12
and d_year=2002
) tmp,time_dim
where
sold_item_sk = i_item_sk
and i_manager_id=1
and time_sk = t_time_sk
and (t_meal_time = 'breakfast' or t_meal_time = 'dinner')
group by i_brand, i_brand_id,t_hour,t_minute
order by ext_price desc, i_brand_id
;

-- start query 72 in stream 0 using template query72.tpl
select top 100 i_item_desc
,w_warehouse_name
,d1.d_week_seq
,sum(case when p_promo_sk is null then 1 else 0 end) no_promo
,sum(case when p_promo_sk is not null then 1 else 0 end) promo
,count(*) total_cnt
from catalog_sales
join inventory on (cs_item_sk = inv_item_sk)
join warehouse on (w_warehouse_sk=inv_warehouse_sk)
join item on (i_item_sk = cs_item_sk)
join customer_demographics on (cs_bill_cdemo_sk = cd_demo_sk)
join household_demographics on (cs_bill_hdemo_sk = hd_demo_sk)
join date_dim d1 on (cs_sold_date_sk = d1.d_date_sk)
join date_dim d2 on (inv_date_sk = d2.d_date_sk)
join date_dim d3 on (cs_ship_date_sk = d3.d_date_sk)
left outer join promotion on (cs_promo_sk=p_promo_sk)
left outer join catalog_returns on (cr_item_sk = cs_item_sk and cr_order_number = cs_order_number)
where d1.d_week_seq = d2.d_week_seq
and inv_quantity_on_hand < cs_quantity
and d3.d_date > d1.d_date + 5
and hd_buy_potential = '1001-5000'
and d1.d_year = 1998
and cd_marital_status = 'S'
group by i_item_desc,w_warehouse_name,d1.d_week_seq
order by total_cnt desc, i_item_desc, w_warehouse_name, d1.d_week_seq
;

-- start query 73 in stream 0 using template query73.tpl
select c_last_name
,c_first_name
,c_salutation
,c_preferred_cust_flag
,ss_ticket_number
,cnt from
(select ss_ticket_number
,ss_customer_sk
,count(*) cnt
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and date_dim.d_dom between 1 and 2
and (household_demographics.hd_buy_potential = '1001-5000' or
household_demographics.hd_buy_potential = '5001-10000')
and household_demographics.hd_vehicle_count > 0
and case when household_demographics.hd_vehicle_count > 0 then
household_demographics.hd_dep_count/ household_demographics.hd_vehicle_count else null end > 1
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_county in ('Williamson County','Williamson County','Williamson County','Williamson County')
group by ss_ticket_number,ss_customer_sk) dj,customer
where ss_customer_sk = c_customer_sk
and cnt between 1 and 5
order by cnt desc, c_last_name asc;

-- start query 74 in stream 0 using template query74.tpl
with year_total as (
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,d_year as year
,max(ss_net_paid) year_total
,'s' sale_type
from customer
,store_sales
,date_dim
where c_customer_sk = ss_customer_sk
and ss_sold_date_sk = d_date_sk
and d_year in (1999,1999+1)
group by c_customer_id
,c_first_name
,c_last_name
,d_year
union all
select c_customer_id customer_id
,c_first_name customer_first_name
,c_last_name customer_last_name
,d_year as year
,max(ws_net_paid) year_total
,'w' sale_type
from customer
,web_sales
,date_dim
where c_customer_sk = ws_bill_customer_sk
and ws_sold_date_sk = d_date_sk
and d_year in (1999,1999+1)
group by c_customer_id
,c_first_name
,c_last_name
,d_year
)
select top 100
t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name
from year_total t_s_firstyear
,year_total t_s_secyear
,year_total t_w_firstyear
,year_total t_w_secyear
where t_s_secyear.customer_id = t_s_firstyear.customer_id
and t_s_firstyear.customer_id = t_w_secyear.customer_id
and t_s_firstyear.customer_id = t_w_firstyear.customer_id
and t_s_firstyear.sale_type = 's'
and t_w_firstyear.sale_type = 'w'
and t_s_secyear.sale_type = 's'
and t_w_secyear.sale_type = 'w'
and t_s_firstyear.year = 1999
and t_s_secyear.year = 1999+1
and t_w_firstyear.year = 1999
and t_w_secyear.year = 1999+1
and t_s_firstyear.year_total > 0
and t_w_firstyear.year_total > 0
and case when t_w_firstyear.year_total > 0 then t_w_secyear.year_total / t_w_firstyear.year_total else null end
> case when t_s_firstyear.year_total > 0 then t_s_secyear.year_total / t_s_firstyear.year_total else null end
order by 1,3,2
;

-- start query 75 in stream 0 using template query75.tpl
WITH all_sales AS (
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,SUM(sales_cnt) AS sales_cnt
,SUM(sales_amt) AS sales_amt
FROM (SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,cs_quantity - COALESCE(cr_return_quantity,0) AS sales_cnt
,cs_ext_sales_price - COALESCE(cr_return_amount,0.0) AS sales_amt
FROM catalog_sales JOIN item ON i_item_sk=cs_item_sk
JOIN date_dim ON d_date_sk=cs_sold_date_sk
LEFT JOIN catalog_returns ON (cs_order_number=cr_order_number
AND cs_item_sk=cr_item_sk)
WHERE i_category='Sports'
UNION
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,ss_quantity - COALESCE(sr_return_quantity,0) AS sales_cnt
,ss_ext_sales_price - COALESCE(sr_return_amt,0.0) AS sales_amt
FROM store_sales JOIN item ON i_item_sk=ss_item_sk
JOIN date_dim ON d_date_sk=ss_sold_date_sk
LEFT JOIN store_returns ON (ss_ticket_number=sr_ticket_number
AND ss_item_sk=sr_item_sk)
WHERE i_category='Sports'
UNION
SELECT d_year
,i_brand_id
,i_class_id
,i_category_id
,i_manufact_id
,ws_quantity - COALESCE(wr_return_quantity,0) AS sales_cnt
,ws_ext_sales_price - COALESCE(wr_return_amt,0.0) AS sales_amt
FROM web_sales JOIN item ON i_item_sk=ws_item_sk
JOIN date_dim ON d_date_sk=ws_sold_date_sk
LEFT JOIN web_returns ON (ws_order_number=wr_order_number
AND ws_item_sk=wr_item_sk)
WHERE i_category='Sports') sales_detail
GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id)
SELECT top 100 prev_yr.d_year AS prev_year
,curr_yr.d_year AS year
,curr_yr.i_brand_id
,curr_yr.i_class_id
,curr_yr.i_category_id
,curr_yr.i_manufact_id
,prev_yr.sales_cnt AS prev_yr_cnt
,curr_yr.sales_cnt AS curr_yr_cnt
,curr_yr.sales_cnt-prev_yr.sales_cnt AS sales_cnt_diff
,curr_yr.sales_amt-prev_yr.sales_amt AS sales_amt_diff
FROM all_sales curr_yr, all_sales prev_yr
WHERE curr_yr.i_brand_id=prev_yr.i_brand_id
AND curr_yr.i_class_id=prev_yr.i_class_id
AND curr_yr.i_category_id=prev_yr.i_category_id
AND curr_yr.i_manufact_id=prev_yr.i_manufact_id
AND curr_yr.d_year=2002
AND prev_yr.d_year=2002-1
AND CAST(curr_yr.sales_cnt AS DECIMAL(17,2))/CAST(prev_yr.sales_cnt AS DECIMAL(17,2))<0.9
ORDER BY sales_cnt_diff,sales_amt_diff
;

-- start query 76 in stream 0 using template query76.tpl
select top 100 channel, col_name, d_year, d_qoy, i_category, COUNT(*) sales_cnt, SUM(ext_sales_price) sales_amt FROM (
SELECT 'store' as channel, 'ss_customer_sk' col_name, d_year, d_qoy, i_category, ss_ext_sales_price ext_sales_price
FROM store_sales, item, date_dim
WHERE ss_customer_sk IS NULL
AND ss_sold_date_sk=d_date_sk
AND ss_item_sk=i_item_sk
UNION ALL
SELECT 'web' as channel, 'ws_promo_sk' col_name, d_year, d_qoy, i_category, ws_ext_sales_price ext_sales_price
FROM web_sales, item, date_dim
WHERE ws_promo_sk IS NULL
AND ws_sold_date_sk=d_date_sk
AND ws_item_sk=i_item_sk
UNION ALL
SELECT 'catalog' as channel, 'cs_bill_customer_sk' col_name, d_year, d_qoy, i_category, cs_ext_sales_price ext_sales_price
FROM catalog_sales, item, date_dim
WHERE cs_bill_customer_sk IS NULL
AND cs_sold_date_sk=d_date_sk
AND cs_item_sk=i_item_sk) foo
GROUP BY channel, col_name, d_year, d_qoy, i_category
ORDER BY channel, col_name, d_year, d_qoy, i_category
;

-- start query 77 in stream 0 using template query77.tpl
with ss as
(select s_store_sk,
sum(ss_ext_sales_price) as sales,
sum(ss_net_profit) as profit
from store_sales,
date_dim,
store
where ss_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
and ss_store_sk = s_store_sk
group by s_store_sk)
,
sr as
(select s_store_sk,
sum(sr_return_amt) as returns,
sum(sr_net_loss) as profit_loss
from store_returns,
date_dim,
store
where sr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
and sr_store_sk = s_store_sk
group by s_store_sk),
cs as
(select cs_call_center_sk,
sum(cs_ext_sales_price) as sales,
sum(cs_net_profit) as profit
from catalog_sales,
date_dim
where cs_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
group by cs_call_center_sk
),
cr as
(select cr_call_center_sk,
sum(cr_return_amount) as returns,
sum(cr_net_loss) as profit_loss
from catalog_returns,
date_dim
where cr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
group by cr_call_center_sk
),
ws as
( select wp_web_page_sk,
sum(ws_ext_sales_price) as sales,
sum(ws_net_profit) as profit
from web_sales,
date_dim,
web_page
where ws_sold_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
and ws_web_page_sk = wp_web_page_sk
group by wp_web_page_sk),
wr as
(select wp_web_page_sk,
sum(wr_return_amt) as returns,
sum(wr_net_loss) as profit_loss
from web_returns,
date_dim,
web_page
where wr_returned_date_sk = d_date_sk
and d_date between cast('2000-08-10' as date)
and (date_add(cast('2000-08-10' as date),interval 30 day))
and wr_web_page_sk = wp_web_page_sk
group by wp_web_page_sk)
select top 100 channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, ss.s_store_sk as id
, sales
, coalesce(returns, 0) as returns
, (profit - coalesce(profit_loss,0)) as profit
from ss left join sr
on ss.s_store_sk = sr.s_store_sk
union all
select 'catalog channel' as channel
, cs_call_center_sk as id
, sales
, returns
, (profit - profit_loss) as profit
from cs
, cr
union all
select 'web channel' as channel
, ws.wp_web_page_sk as id
, sales
, coalesce(returns, 0) returns
, (profit - coalesce(profit_loss,0)) as profit
from ws left join wr
on ws.wp_web_page_sk = wr.wp_web_page_sk
) x
group by rollup (channel, id)
order by channel
,id
;

-- start query 78 in stream 0 using template query78.tpl
with ws as
(select d_year AS ws_sold_year, ws_item_sk,
ws_bill_customer_sk ws_customer_sk,
sum(ws_quantity) ws_qty,
sum(ws_wholesale_cost) ws_wc,
sum(ws_sales_price) ws_sp
from web_sales
left join web_returns on wr_order_number=ws_order_number and ws_item_sk=wr_item_sk
join date_dim on ws_sold_date_sk = d_date_sk
where wr_order_number is null
group by d_year, ws_item_sk, ws_bill_customer_sk
),
cs as
(select d_year AS cs_sold_year, cs_item_sk,
cs_bill_customer_sk cs_customer_sk,
sum(cs_quantity) cs_qty,
sum(cs_wholesale_cost) cs_wc,
sum(cs_sales_price) cs_sp
from catalog_sales
left join catalog_returns on cr_order_number=cs_order_number and cs_item_sk=cr_item_sk
join date_dim on cs_sold_date_sk = d_date_sk
where cr_order_number is null
group by d_year, cs_item_sk, cs_bill_customer_sk
),
ss as
(select d_year AS ss_sold_year, ss_item_sk,
ss_customer_sk,
sum(ss_quantity) ss_qty,
sum(ss_wholesale_cost) ss_wc,
sum(ss_sales_price) ss_sp
from store_sales
left join store_returns on sr_ticket_number=ss_ticket_number and ss_item_sk=sr_item_sk
join date_dim on ss_sold_date_sk = d_date_sk
where sr_ticket_number is null
group by d_year, ss_item_sk, ss_customer_sk
)
select top 100
ss_customer_sk,
round(ss_qty/(coalesce(ws_qty,0)+coalesce(cs_qty,0)),2) ratio,
ss_qty store_qty, ss_wc store_wholesale_cost, ss_sp store_sales_price,
coalesce(ws_qty,0)+coalesce(cs_qty,0) other_chan_qty,
coalesce(ws_wc,0)+coalesce(cs_wc,0) other_chan_wholesale_cost,
coalesce(ws_sp,0)+coalesce(cs_sp,0) other_chan_sales_price
from ss
left join ws on (ws_sold_year=ss_sold_year and ws_item_sk=ss_item_sk and ws_customer_sk=ss_customer_sk)
left join cs on (cs_sold_year=ss_sold_year and cs_item_sk=ss_item_sk and cs_customer_sk=ss_customer_sk)
where (coalesce(ws_qty,0)>0 or coalesce(cs_qty, 0)>0) and ss_sold_year=1998
order by
ss_customer_sk,
ss_qty desc, ss_wc desc, ss_sp desc,
other_chan_qty,
other_chan_wholesale_cost,
other_chan_sales_price,
ratio
;

-- start query 79 in stream 0 using template query79.tpl
select top 100
c_last_name,c_first_name,substr(s_city,1,30),ss_ticket_number,amt,profit
from
(select ss_ticket_number
,ss_customer_sk
,store.s_city
,sum(ss_coupon_amt) amt
,sum(ss_net_profit) profit
from store_sales,date_dim,store,household_demographics
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_store_sk = store.s_store_sk
and store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk
and (household_demographics.hd_dep_count = 7 or household_demographics.hd_vehicle_count > -1)
and date_dim.d_dow = 1
and date_dim.d_year in (2000,2000+1,2000+2)
and store.s_number_employees between 200 and 295
group by ss_ticket_number,ss_customer_sk,ss_addr_sk,store.s_city) ms,customer
where ss_customer_sk = c_customer_sk
order by c_last_name,c_first_name,substr(s_city,1,30), profit
;

-- start query 80 in stream 0 using template query80.tpl
with ssr as
(select s_store_id as store_id,
sum(ss_ext_sales_price) as sales,
sum(coalesce(sr_return_amt, 0)) as returns,
sum(ss_net_profit - coalesce(sr_net_loss, 0)) as profit
from store_sales left outer join store_returns on
(ss_item_sk = sr_item_sk and ss_ticket_number = sr_ticket_number),
date_dim,
store,
item,
promotion
where ss_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
and (date_add(cast('2002-08-14' as date),interval 30 day))
and ss_store_sk = s_store_sk
and ss_item_sk = i_item_sk
and i_current_price > 50
and ss_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by s_store_id)
,
csr as
(select cp_catalog_page_id as catalog_page_id,
sum(cs_ext_sales_price) as sales,
sum(coalesce(cr_return_amount, 0)) as returns,
sum(cs_net_profit - coalesce(cr_net_loss, 0)) as profit
from catalog_sales left outer join catalog_returns on
(cs_item_sk = cr_item_sk and cs_order_number = cr_order_number),
date_dim,
catalog_page,
item,
promotion
where cs_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
and (date_add(cast('2002-08-14' as date),interval 30 day))
and cs_catalog_page_sk = cp_catalog_page_sk
and cs_item_sk = i_item_sk
and i_current_price > 50
and cs_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by cp_catalog_page_id)
,
wsr as
(select web_site_id,
sum(ws_ext_sales_price) as sales,
sum(coalesce(wr_return_amt, 0)) as returns,
sum(ws_net_profit - coalesce(wr_net_loss, 0)) as profit
from web_sales left outer join web_returns on
(ws_item_sk = wr_item_sk and ws_order_number = wr_order_number),
date_dim,
web_site,
item,
promotion
where ws_sold_date_sk = d_date_sk
and d_date between cast('2002-08-14' as date)
and (date_add(cast('2002-08-14' as date),interval 30 day))
and ws_web_site_sk = web_site_sk
and ws_item_sk = i_item_sk
and i_current_price > 50
and ws_promo_sk = p_promo_sk
and p_channel_tv = 'N'
group by web_site_id)
select top 100 channel
, id
, sum(sales) as sales
, sum(returns) as returns
, sum(profit) as profit
from
(select 'store channel' as channel
, 'store' || store_id as id
, sales
, returns
, profit
from ssr
union all
select 'catalog channel' as channel
, 'catalog_page' || catalog_page_id as id
, sales
, returns
, profit
from csr
union all
select 'web channel' as channel
, 'web_site' || web_site_id as id
, sales
, returns
, profit
from wsr
) x
group by rollup (channel, id)
order by channel
,id
;

-- start query 81 in stream 0 using template query81.tpl
with customer_total_return as
(select cr_returning_customer_sk as ctr_customer_sk
,ca_state as ctr_state,
sum(cr_return_amt_inc_tax) as ctr_total_return
from catalog_returns
,date_dim
,customer_address
where cr_returned_date_sk = d_date_sk
and d_year =2001
and cr_returning_addr_sk = ca_address_sk
group by cr_returning_customer_sk
,ca_state )
select top 100 c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
,ca_location_type,ctr_total_return
from customer_total_return ctr1
,customer_address
,customer
where ctr1.ctr_total_return > (select avg(ctr_total_return)*1.2
from customer_total_return ctr2
where ctr1.ctr_state = ctr2.ctr_state)
and ca_address_sk = c_current_addr_sk
and ca_state = 'TN'
and ctr1.ctr_customer_sk = c_customer_sk
order by c_customer_id,c_salutation,c_first_name,c_last_name,ca_street_number,ca_street_name
,ca_street_type,ca_suite_number,ca_city,ca_county,ca_state,ca_zip,ca_country,ca_gmt_offset
,ca_location_type,ctr_total_return
;

-- start query 82 in stream 0 using template query82.tpl
select top 100 i_item_id
,i_item_desc
,i_current_price
from item, inventory, date_dim, store_sales
where i_current_price between 58 and 58+30
and inv_item_sk = i_item_sk
and d_date_sk=inv_date_sk
and d_date between cast('2001-01-13' as date) and (date_add(cast('2001-01-13' as date),interval 60 day))
and i_manufact_id in (259,559,580,485)
and inv_quantity_on_hand between 100 and 500
and ss_item_sk = i_item_sk
group by i_item_id,i_item_desc,i_current_price
order by i_item_id
;

-- start query 83 in stream 0 using template query83.tpl
with sr_items as
(select i_item_id item_id,
sum(sr_return_quantity) sr_item_qty
from store_returns,
item,
date_dim
where sr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
and sr_returned_date_sk = d_date_sk
group by i_item_id),
cr_items as
(select i_item_id item_id,
sum(cr_return_quantity) cr_item_qty
from catalog_returns,
item,
date_dim
where cr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
and cr_returned_date_sk = d_date_sk
group by i_item_id),
wr_items as
(select i_item_id item_id,
sum(wr_return_quantity) wr_item_qty
from web_returns,
item,
date_dim
where wr_item_sk = i_item_sk
and d_date in
(select d_date
from date_dim
where d_week_seq in
(select d_week_seq
from date_dim
where d_date in ('2001-07-13','2001-09-10','2001-11-16')))
and wr_returned_date_sk = d_date_sk
group by i_item_id)
select top 100 sr_items.item_id
,sr_item_qty
,sr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 sr_dev
,cr_item_qty
,cr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 cr_dev
,wr_item_qty
,wr_item_qty/(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 * 100 wr_dev
,(sr_item_qty+cr_item_qty+wr_item_qty)/3.0 average
from sr_items
,cr_items
,wr_items
where sr_items.item_id=cr_items.item_id
and sr_items.item_id=wr_items.item_id
order by sr_items.item_id
,sr_item_qty
;

-- start query 84 in stream 0 using template query84.tpl
select top 100 c_customer_id as customer_id
, coalesce(c_last_name,'') || ', ' || coalesce(c_first_name,'') as customername
from customer
,customer_address
,customer_demographics
,household_demographics
,income_band
,store_returns
where ca_city = 'Woodland'
and c_current_addr_sk = ca_address_sk
and ib_lower_bound >= 60306
and ib_upper_bound <= 60306 + 50000
and ib_income_band_sk = hd_income_band_sk
and cd_demo_sk = c_current_cdemo_sk
and hd_demo_sk = c_current_hdemo_sk
and sr_cdemo_sk = cd_demo_sk
order by c_customer_id
;

-- start query 85 in stream 0 using template query85.tpl
select top 100 substr(r_reason_desc,1,20)
,avg(ws_quantity)
,avg(wr_refunded_cash)
,avg(wr_fee)
from web_sales, web_returns, web_page, customer_demographics cd1,
customer_demographics cd2, customer_address, date_dim, reason
where ws_web_page_sk = wp_web_page_sk
and ws_item_sk = wr_item_sk
and ws_order_number = wr_order_number
and ws_sold_date_sk = d_date_sk and d_year = 1998
and cd1.cd_demo_sk = wr_refunded_cdemo_sk
and cd2.cd_demo_sk = wr_returning_cdemo_sk
and ca_address_sk = wr_refunded_addr_sk
and r_reason_sk = wr_reason_sk
and
(
(
cd1.cd_marital_status = 'D'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'Primary'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 100.00 and 150.00
)
or
(
cd1.cd_marital_status = 'S'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'College'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 50.00 and 100.00
)
or
(
cd1.cd_marital_status = 'U'
and
cd1.cd_marital_status = cd2.cd_marital_status
and
cd1.cd_education_status = 'Advanced Degree'
and
cd1.cd_education_status = cd2.cd_education_status
and
ws_sales_price between 150.00 and 200.00
)
)
and
(
(
ca_country = 'United States'
and
ca_state in ('NC', 'TX', 'IA')
and ws_net_profit between 100 and 200
)
or
(
ca_country = 'United States'
and
ca_state in ('WI', 'WV', 'GA')
and ws_net_profit between 150 and 300
)
or
(
ca_country = 'United States'
and
ca_state in ('OK', 'VA', 'KY')
and ws_net_profit between 50 and 250
)
)
group by r_reason_desc
order by substr(r_reason_desc,1,20)
,avg(ws_quantity)
,avg(wr_refunded_cash)
,avg(wr_fee)
;

-- start query 86 in stream 0 using template query86.tpl
select top 100
sum(ws_net_paid) as total_sum
,i_category
,i_class
,grouping(i_category)+grouping(i_class) as lochierarchy
,rank() over (
partition by grouping(i_category)+grouping(i_class),
case when grouping(i_class) = 0 then i_category end
order by sum(ws_net_paid) desc) as rank_within_parent
from
web_sales
,date_dim d1
,item
where
d1.d_month_seq between 1186 and 1186+11
and d1.d_date_sk = ws_sold_date_sk
and i_item_sk = ws_item_sk
group by rollup(i_category,i_class)
order by
lochierarchy desc,
case when lochierarchy = 0 then i_category end,
rank_within_parent
;

-- start query 87 in stream 0 using template query87.tpl
select count(*)
from ((select distinct c_last_name, c_first_name, d_date
from store_sales, date_dim, customer
where store_sales.ss_sold_date_sk = date_dim.d_date_sk
and store_sales.ss_customer_sk = customer.c_customer_sk
and d_month_seq between 1202 and 1202+11)
except
(select distinct c_last_name, c_first_name, d_date
from catalog_sales, date_dim, customer
where catalog_sales.cs_sold_date_sk = date_dim.d_date_sk
and catalog_sales.cs_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1202 and 1202+11)
except
(select distinct c_last_name, c_first_name, d_date
from web_sales, date_dim, customer
where web_sales.ws_sold_date_sk = date_dim.d_date_sk
and web_sales.ws_bill_customer_sk = customer.c_customer_sk
and d_month_seq between 1202 and 1202+11)
) cool_cust
;

-- start query 88 in stream 0 using template query88.tpl
select *
from
(select count(*) h8_30_to_9
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 8
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s1,
(select count(*) h9_to_9_30
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 9
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s2,
(select count(*) h9_30_to_10
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 9
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s3,
(select count(*) h10_to_10_30
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 10
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s4,
(select count(*) h10_30_to_11
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 10
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s5,
(select count(*) h11_to_11_30
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 11
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s6,
(select count(*) h11_30_to_12
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 11
and time_dim.t_minute >= 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s7,
(select count(*) h12_to_12_30
from store_sales, household_demographics , time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 12
and time_dim.t_minute < 30
and ((household_demographics.hd_dep_count = 0 and household_demographics.hd_vehicle_count<=0+2) or
(household_demographics.hd_dep_count = -1 and household_demographics.hd_vehicle_count<=-1+2) or
(household_demographics.hd_dep_count = 3 and household_demographics.hd_vehicle_count<=3+2))
and store.s_store_name = 'ese') s8
;

-- start query 89 in stream 0 using template query89.tpl
select top 100 *
from(
select i_category, i_class, i_brand,
s_store_name, s_company_name,
d_moy,
sum(ss_sales_price) sum_sales,
avg(sum(ss_sales_price)) over
(partition by i_category, i_brand, s_store_name, s_company_name)
avg_monthly_sales
from item, store_sales, date_dim, store
where ss_item_sk = i_item_sk and
ss_sold_date_sk = d_date_sk and
ss_store_sk = s_store_sk and
d_year in (2001) and
((i_category in ('Books','Children','Electronics') and
i_class in ('history','school-uniforms','audio')
)
or (i_category in ('Men','Sports','Shoes') and
i_class in ('pants','tennis','womens')
))
group by i_category, i_class, i_brand,
s_store_name, s_company_name, d_moy) tmp1
where case when (avg_monthly_sales <> 0) then (abs(sum_sales - avg_monthly_sales) / avg_monthly_sales) else null end > 0.1
order by sum_sales - avg_monthly_sales, s_store_name
;

-- start query 90 in stream 0 using template query90.tpl
select top 100 cast(amc as decimal(15,4))/cast(pmc as decimal(15,4)) am_pm_ratio
from ( select count(*) amc
from web_sales, household_demographics , time_dim, web_page
where ws_sold_time_sk = time_dim.t_time_sk
and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
and ws_web_page_sk = web_page.wp_web_page_sk
and time_dim.t_hour between 12 and 12+1
and household_demographics.hd_dep_count = 6
and web_page.wp_char_count between 5000 and 5200) at,
( select count(*) pmc
from web_sales, household_demographics , time_dim, web_page
where ws_sold_time_sk = time_dim.t_time_sk
and ws_ship_hdemo_sk = household_demographics.hd_demo_sk
and ws_web_page_sk = web_page.wp_web_page_sk
and time_dim.t_hour between 14 and 14+1
and household_demographics.hd_dep_count = 6
and web_page.wp_char_count between 5000 and 5200) pt
order by am_pm_ratio
;

-- start query 91 in stream 0 using template query91.tpl
select
cc_call_center_id Call_Center,
cc_name Call_Center_Name,
cc_manager Manager,
sum(cr_net_loss) Returns_Loss
from
call_center,
catalog_returns,
date_dim,
customer,
customer_address,
customer_demographics,
household_demographics
where
cr_call_center_sk = cc_call_center_sk
and cr_returned_date_sk = d_date_sk
and cr_returning_customer_sk= c_customer_sk
and cd_demo_sk = c_current_cdemo_sk
and hd_demo_sk = c_current_hdemo_sk
and ca_address_sk = c_current_addr_sk
and d_year = 2000
and d_moy = 12
and ( (cd_marital_status = 'M' and cd_education_status = 'Unknown')
or(cd_marital_status = 'W' and cd_education_status = 'Advanced Degree'))
and hd_buy_potential like 'Unknown%'
and ca_gmt_offset = -7
group by cc_call_center_id,cc_name,cc_manager,cd_marital_status,cd_education_status
order by sum(cr_net_loss) desc
;

-- start query 92 in stream 0 using template query92.tpl
select top 100
sum(ws_ext_discount_amt) as "Excess Discount Amount"
from
web_sales
,item
,date_dim
where
i_manufact_id = 714
and i_item_sk = ws_item_sk
and d_date between '2000-02-01' and
(date_add(cast('2000-02-01' as date),interval 90 day))
and d_date_sk = ws_sold_date_sk
and ws_ext_discount_amt
> (
SELECT
1.3 * avg(ws_ext_discount_amt)
FROM
web_sales
,date_dim
WHERE
ws_item_sk = i_item_sk
and d_date between '2000-02-01' and
(date_add(cast('2000-02-01' as date),interval 90 day))
and d_date_sk = ws_sold_date_sk
)
order by sum(ws_ext_discount_amt)
;

-- start query 93 in stream 0 using template query93.tpl
select top 100 ss_customer_sk
,sum(act_sales) sumsales
from (select ss_item_sk
,ss_ticket_number
,ss_customer_sk
,case when sr_return_quantity is not null then (ss_quantity-sr_return_quantity)*ss_sales_price
else (ss_quantity*ss_sales_price) end act_sales
from store_sales left outer join store_returns on (sr_item_sk = ss_item_sk
and sr_ticket_number = ss_ticket_number)
,reason
where sr_reason_sk = r_reason_sk
and r_reason_desc = 'reason 58') t
group by ss_customer_sk
order by sumsales, ss_customer_sk
;

-- start query 94 in stream 0 using template query94.tpl
select top 100
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
from
web_sales ws1
,date_dim
,customer_address
,web_site
where
d_date between '2002-5-01' and
(date_add(cast('2002-5-01' as date),interval 60 day))
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'OK'
and ws1.ws_web_site_sk = web_site_sk
and web_company_name = 'pri'
and exists (select *
from web_sales ws2
where ws1.ws_order_number = ws2.ws_order_number
and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
and not exists(select *
from web_returns wr1
where ws1.ws_order_number = wr1.wr_order_number)
order by count(distinct ws_order_number)
;

-- start query 95 in stream 0 using template query95.tpl
with ws_wh as
(select ws1.ws_order_number,ws1.ws_warehouse_sk wh1,ws2.ws_warehouse_sk wh2
from web_sales ws1,web_sales ws2
where ws1.ws_order_number = ws2.ws_order_number
and ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk)
select top 100
count(distinct ws_order_number) as "order count"
,sum(ws_ext_ship_cost) as "total shipping cost"
,sum(ws_net_profit) as "total net profit"
from
web_sales ws1
,date_dim
,customer_address
,web_site
where
d_date between '2001-4-01' and
(date_add(cast('2001-4-01' as date),interval 60 day))
and ws1.ws_ship_date_sk = d_date_sk
and ws1.ws_ship_addr_sk = ca_address_sk
and ca_state = 'VA'
and ws1.ws_web_site_sk = web_site_sk
and web_company_name = 'pri'
and ws1.ws_order_number in (select ws_order_number
from ws_wh)
and ws1.ws_order_number in (select wr_order_number
from web_returns,ws_wh
where wr_order_number = ws_wh.ws_order_number)
order by count(distinct ws_order_number)
;

-- start query 96 in stream 0 using template query96.tpl
select top 100 count(*)
from store_sales
,household_demographics
,time_dim, store
where ss_sold_time_sk = time_dim.t_time_sk
and ss_hdemo_sk = household_demographics.hd_demo_sk
and ss_store_sk = s_store_sk
and time_dim.t_hour = 8
and time_dim.t_minute >= 30
and household_demographics.hd_dep_count = 0
and store.s_store_name = 'ese'
order by count(*)
;

-- start query 97 in stream 0 using template query97.tpl
with ssci as (
select ss_customer_sk customer_sk
,ss_item_sk item_sk
from store_sales,date_dim
where ss_sold_date_sk = d_date_sk
and d_month_seq between 1199 and 1199 + 11
group by ss_customer_sk
,ss_item_sk),
csci as(
select cs_bill_customer_sk customer_sk
,cs_item_sk item_sk
from catalog_sales,date_dim
where cs_sold_date_sk = d_date_sk
and d_month_seq between 1199 and 1199 + 11
group by cs_bill_customer_sk
,cs_item_sk)
select top 100 sum(case when ssci.customer_sk is not null and csci.customer_sk is null then 1 else 0 end) store_only
,sum(case when ssci.customer_sk is null and csci.customer_sk is not null then 1 else 0 end) catalog_only
,sum(case when ssci.customer_sk is not null and csci.customer_sk is not null then 1 else 0 end) store_and_catalog
from ssci full outer join csci on (ssci.customer_sk=csci.customer_sk
and ssci.item_sk = csci.item_sk)
;

-- start query 98 in stream 0 using template query98.tpl
select i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
,sum(ss_ext_sales_price) as itemrevenue
,sum(ss_ext_sales_price)*100/sum(sum(ss_ext_sales_price)) over
(partition by i_class) as revenueratio
from
store_sales
,item
,date_dim
where
ss_item_sk = i_item_sk
and i_category in ('Men', 'Sports', 'Jewelry')
and ss_sold_date_sk = d_date_sk
and d_date between cast('1999-02-05' as date)
and (date_add(cast('1999-02-05' as date),interval 30 day))
group by
i_item_id
,i_item_desc
,i_category
,i_class
,i_current_price
order by
i_category
,i_class
,i_item_id
,i_item_desc
,revenueratio
;

-- start query 99 in stream 0 using template query99.tpl
select top 100
substr(w_warehouse_name,1,20)
,sm_type
,cc_name
,sum(case when (cs_ship_date_sk - cs_sold_date_sk <= 30 ) then 1 else 0 end) as "30 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 30) and
(cs_ship_date_sk - cs_sold_date_sk <= 60) then 1 else 0 end ) as "31-60 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 60) and
(cs_ship_date_sk - cs_sold_date_sk <= 90) then 1 else 0 end) as "61-90 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 90) and
(cs_ship_date_sk - cs_sold_date_sk <= 120) then 1 else 0 end) as "91-120 days"
,sum(case when (cs_ship_date_sk - cs_sold_date_sk > 120) then 1 else 0 end) as ">120 days"
from
catalog_sales
,warehouse
,ship_mode
,call_center
,date_dim
where
d_month_seq between 1194 and 1194 + 11
and cs_ship_date_sk = d_date_sk
and cs_warehouse_sk = w_warehouse_sk
and cs_ship_mode_sk = sm_ship_mode_sk
and cs_call_center_sk = cc_call_center_sk
group by
substr(w_warehouse_name,1,20)
,sm_type
,cc_name
order by substr(w_warehouse_name,1,20)
,sm_type
,cc_name
;