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select min(i_item_sk)
,min(w_warehouse_name)
,min(d1.d_week_seq)
,min(cs_item_sk)
,min(cs_order_number)
,min(inv_item_sk)
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 > dateadd(day, 3, d1.d_date)
and hd_buy_potential = '501-1000'
and d1.d_year = 2002
and cd_marital_status = 'W'
and cd_dep_count between 3 and 5
and i_category IN ('Home', 'Sports', 'Women')
and cs_wholesale_cost BETWEEN 73 AND 93
;
Step details
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Green: scan · yellow: join · purple: row movement. Rows and costs are optimiser estimates; costs use model units.