blob: 206432b8ea6b1374bd7d23aad0ea22a8ad5ce20f [file] [log] [blame]
-- start query 1 in stream 0 using template query50.tpl and seed 1819994127
select
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 = 1998
and d2.d_moy = 9
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
limit 100;
-- end query 1 in stream 0 using template query50.tpl