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SELECT
TOP 100
*
FROM (
SELECT
i_manager_id AS i_manager_id,
SUM(ss_sales_price) AS sum_sales,
AVG(SUM(ss_sales_price)) OVER (PARTITION BY i_manager_id) AS 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 (
1203,
1203 + 1,
1203 + 2,
1203 + 3,
1203 + 4,
1203 + 5,
1203 + 6,
1203 + 7,
1203 + 8,
1203 + 9,
1203 + 10,
1203 + 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
) AS 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;
Step details
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Green: scan · yellow: join · purple: row movement. Rows and costs are optimiser estimates; costs use model units.