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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 AS ss_ticket_number,
ss_customer_sk AS ss_customer_sk,
ca_city AS bought_city,
SUM(ss_ext_sales_price) AS extended_price,
SUM(ss_ext_list_price) AS list_price,
SUM(ss_ext_tax) AS 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 = 5
OR household_demographics.hd_vehicle_count = 4
)
AND date_dim.d_year IN (2000, 2000 + 1, 2000 + 2)
AND store.s_city IN ('Shiloh', 'Glenwood')
GROUP BY
ss_ticket_number,
ss_customer_sk,
ss_addr_sk,
ca_city
) AS dn, customer, customer_address AS 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;
Step details
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Green: scan · yellow: join · purple: row movement. Rows and costs are optimiser estimates; costs use model units.